Two CMake variable are marked as deprecated and "#TODO next release:
remove this". It is introduced in https://github.com/opencv/opencv/pull/11167
which is before the release of 4.0. Since it's deprecated almost six
years ago, I think it's OK to remove them.
- Added JavaDoc package build and publishing
- Added Source package build and publishing
- More metadata for publishing
- Disable native samples build with aar, because prefab is not complete yet
dnn onnx: support constaint inputs in einsum importer #24753
Merge with https://github.com/opencv/opencv_extra/pull/1132.
Resolves https://github.com/opencv/opencv/issues/24697
Credits to @LaurentBerger.
---
This is a workaround. I suggest to get input shapes and calculate the output shapes in `getMemoryShapes` so as to keep the best compatibility. It is not always robust getting shapes during the importer stage and we should avoid that as much as possible.
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Fix to convert float32 to int32/uint32 with rounding to nearest (ties to even). #24271
Fix https://github.com/opencv/opencv/issues/24163
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(carotene is BSD)
Fix mismatch and simplify code in ChessBoardDetector::findQuadNeighbors #24667
### Pull Request Readiness Checklist
Сode doesn't match comment.
If we want check `1:4` edges ratio and `edge_len` is squared edge length, then we should check
```
ediff > 15*edge_len
```
with constant `15`, not `32`, because
```
ediff > 15*edge_len2 <=> edge_len1 - edge_len2 > 15*edge_len2 <=> edge_len1 > 16*edge_len2 <=> 1:4 edges ratio
```
But for me it's better and simpler to directly check `edge_len1 > 16*edge_len2`
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Currently, if `PNG_FOUND`, cmake scripts will check include and parse
header while we can use `PNG_VERSION_STRING` conveniently. If
`BUILD_PNG`, parse version from `PNG_LIBPNG_VER_STRING` directly is more
convenient than parsing major, minor and patch and concatenate them.
The comment of png.h also supports this.
```
/* These should match the first 3 components of PNG_LIBPNG_VER_STRING: */
```
https://github.com/glennrp/libpng/blob/libpng16/png.h#L287
This patch also modifies `ocv_parse_header_version` macro to receive
another parameter to make it more general.
The reason why changing `PNG_VERSION` to `PNG_VERSION_STRING` is to be
consistent with cmake's FindPNG.
This patch removes `HAVE_LIBPNG_PNG_H` variable because `PNG_INCLUDE_DIR`
is where to find png.h, etc according to
https://cmake.org/cmake/help/latest/module/FindPNG.html.
This patch also removes `PNG_PNG_INCLUDE_DIR` variable which is an
advanced variable used in cmake's FindPNG and is not used in opencv.
Currently, if OpenJPEG is found, only version information in summary is
correct and the information right after `find_package(OpenJPEG)` is
wrong.
```
-- Found system OpenJPEG: openjp2 (found version "")
```
The reason is OpenJPEGConfig.cmake only sets `OPENJPEG_MAJOR_VERSION`,
`OPENJPEG_MINOR_VERSION` and `OPENJPEG_BUILD_VERSION` but not `OPENJPEG_VERSION`.
Fixes#22747. Support [crop] configuration for DarkNet #24384
Request for comments. This is my first PR.
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1112
resolves https://github.com/opencv/opencv/issues/22747
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Try to enable Winograd by default in FP32 mode and disable it by default in FP16 mode #24709
Hopefully, it will resolve regressions since 4.8.1 (see also https://github.com/opencv/opencv/pull/24587)
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Currently cmake scripttry to use regex to parse VER_MAJOR, VER_MINOR,
VER_REVISION from ZLIB_VERSION. However, ZLIB_VERSION is "1.3" which
means that there is no VER_REVISION.
You can reproduce using "-DBUILD_ZLIB=ON"
```
-- ZLib: zlib (ver 1.3.#define ZLIB_VERSION "1.3")
```
This patch add a new macro ocv_parse_header_version to extract version
information.
dnn: add attention layer #24476Resolves#24609
Merge with: https://github.com/opencv/opencv_extra/pull/1128.
Attention operator spec from onnxruntime: https://github.com/microsoft/onnxruntime/blob/v1.16.1/docs/ContribOperators.md#com.microsoft.Attention.
TODO:
- [x] benchmark (before this PR vs. with this PR vs. ORT).
- [x] Layer fusion: Take care Slice with end=INT64_MAX.
- [x] Layer fusion: match more potential attention (VIT) patterns.
- [x] Single-head attention is supported.
- [x] Test AttentionSubgraph fusion.
- [x] Add acc tests for VIT_B_32 and VitTrack
- [x] Add perf tests for VIT_B_32 and VitTrack
## Benchmarks
Platform: Macbook Air M1.
### Attention Subgraph
Input scale: [1, 197, 768].
| | mean (ms) | median (ms) | min (ms) |
| ---------------------- | --------- | ----------- | -------- |
| w/ Attention (this PR) | 3.75 | 3.68 | 3.22 |
| w/o Attention | 9.06 | 9.01 | 8.24 |
| ORT (python) | 4.32 | 2.63 | 2.50 |
### ViTs
All data in millisecond (ms).
| ViTs | With Attention | Without Attention | ORT |
| -------- | -------------- | ----------------- | ------ |
| vit_b_16 | 302.77 | 365.35 | 109.70 |
| vit_b_32 | 89.92 | 116.22 | 30.36 |
| vit_l_16 | 1593.32 | 1730.74 | 419.92 |
| vit_l_32 | 468.11 | 577.41 | 134.12 |
| VitTrack | 3.80 | 3.87 | 2.25 |
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Check Checkerboard Corners #24546
What I did was get you to pull out of findChessboardCorners cornres the whole part that "checks" and sorts the corners of the checkerboard if present.
The main reason for this is that findChessboardCorners is often very slow to find the corners and this depends in that the size the contrast etc of the checkerboards can be very different from each other and writing a function that works on all kinds of images is complicated.
So I find it very useful to have the ability to write your own code to process the image and then have a function that controls or orders the corners.
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Update Android OpenCL sample #24715
Update Android OpenCL sample and tutorial text.
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Add experimental support for Apple VisionOS platform #24136
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This is dependent on cmake support for VisionOs which is currently in progress.
Creating PR now to test that there are no regressions in iOS and macOS builds
Add support for external libspng. #24718
Fixes https://github.com/opencv/opencv/issues/24683
Related patch to libspng: https://github.com/randy408/libspng/pull/264
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Add blobrecttoimage #24539
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/14659
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dnn: refactor ONNX MatMul with fastGemm #24694
Done:
- [x] add backends
- [x] CUDA
- [x] OpenVINO
- [x] CANN
- [x] OpenCL
- [x] Vulkan
- [x] add perf tests
- [x] const B case
### Benchmark
Tests are done on M1. All data is in milliseconds (ms).
| Configuration | MatMul (Prepacked) | MatMul | InnerProduct |
| - | - | - | - |
| A=[12, 197, 197], B=[12, 197, 64], trans_a=0, trans_b=0 | **0.39** | 0.41 | 1.33 |
| A=[12, 197, 64], B=[12, 64, 197], trans_a=0, trans_b=0 | **0.42** | 0.42 | 1.17 |
| A=[12, 50, 64], B=[12, 64, 50], trans_a=0, trans_b=0 | **0.13** | 0.15 | 0.33 |
| A=[12, 50, 50], B=[12, 50, 64], trans_a=0, trans_b=0 | **0.11** | 0.13 | 0.22 |
| A=[16, 197, 197], B=[16, 197, 64], trans_a=0, trans_b=0 | **0.46** | 0.54 | 1.46 |
| A=[16, 197, 64], B=[16, 64, 197], trans_a=0, trans_b=0 | **0.46** | 0.95 | 1.74 |
| A=[16, 50, 64], B=[16, 64, 50], trans_a=0, trans_b=0 | **0.18** | 0.32 | 0.43 |
| A=[16, 50, 50], B=[16, 50, 64], trans_a=0, trans_b=0 | **0.15** | 0.25 | 0.25 |
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Add support for Orbbec Gemini2 and Gemini2 XL camera #24666
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The opencv zlib patch is still not merged. So I applied it to zlib-1.3.
Since zlib-1.3 didn't modify CMakeLists.txt, opencv's zlib
CMakeLists.txt doesn't need to be modified.
Android Tutorial for Windows Updated #24700
This PR updates Android tutorials parts related to Windows
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Fix path to ONNX Runtime include folder #24601
### Pull Request Readiness Checklist
Looks the `install` directory layout has been changed for `v1.16.3`
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Make default axis of softmax in onnx "-1" without opset option #24613
Try to solve problem: https://github.com/opencv/opencv/pull/24476#discussion_r1404821158
**ONNX**
`opset <= 11` use 1
`else` use -1
**TensorFlow**
`TF version = 2.x` use -1
`else` use 1
**Darknet, Caffe, Torch**
use 1 by definition
G-API: Support CoreML Execution Providers for ONNXRT Backend #24068
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G-API: Get input model layout from the IR if possible in OV 2.0 backend #24658
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Android sample for VideoWriter #24592
This PR:
* adds an Android sample for video recording with MediaNDK and built-in MJPEG.
* adds a flag `--no_media_ndk` for `build_sdk.py` script to disable MediaNDK linkage.
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Android camera tutorial update #24692
This PR extends the OpenCV 4 Android tutorial by a simple camera app based on existing code.
This part was accidentally removed during the #24653 preparation, this PR restores it and aligns it to the latest Android Studio.
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Classify and extend convolution and depthwise performance tests #24547
This PR aims to:
1. Extend the test cases from models: `YOLOv5`, `YOLOv8`, `EfficientNet`, `YOLOX`, `YuNet`, `SFace`, `MPPalm`, `MPHand`, `MPPose`, `ViTTrack`, `PPOCRv3`, `CRNN`, `PPHumanSeg`. (371 new test cases are added)
2. Classify the existing convolution performance test to below cases
- CONV_1x1
- CONV_3x3_S1_D1 (winograd)
- CONV
- DEPTHWISE
3. Reduce unnecessary test cases by follow 3 rules (366 test cases are pruned):
(i). For all tests, except for pad and bias related parameters, all other parameters are the same. Only one case can be reserved.
(ii). When the only difference is the channel of input shape, and other parameters are the same. Only one case can be reserved in each range `[1, 3], [4, 7], [8, 15], [16, 31], [32, 63], [64, 127], [128, 255], [256, 511], [512, 1023], [1024, 2047], [2048, 4095]`
(iii). When the only difference is the width and height of input shape, and other parameters are the same. Only one case can be reserved in each range `[1, 31], [32, 63], [64, 95]... `
> **Reproduced**: 1. follow step in https://github.com/alalek/opencv/commit/dnn_dump_conv_kernels to dump all convolution cases from new models. (declared flops may not right, need to be checked manually) 2 and 3. Use the script from python code [classify conv.txt](https://github.com/opencv/opencv/files/13522228/classify.conv.txt)
**Performance test result on Apple M2**
**Test result details**: [M2.md](https://github.com/opencv/opencv/files/13379189/M2.md)
**Additional test result details with FP16**: [m2_results_with_fp16.zip](https://github.com/opencv/opencv/files/13491070/m2_results_with_fp16.zip)
**Brief summary for 4.8.1 vs 4.7.0 or 4.6.0**:
1. `CONV_1x1_S1_D1` dropped significant with small or large input shape.
2. `DEPTHWISE_5x5 ` dropped a little compared with 4.7.0.
---
**Performance test result on [Intel Core i7-12700K](https://www.intel.com/content/www/us/en/products/sku/134594/intel-core-i712700k-processor-25m-cache-up-to-5-00-ghz/specifications.html)**: 8 Performance-cores (3.60 GHz, turbo up to 4.90 GHz), 4 Efficient-cores (2.70 GHz, turbo up to 3.80 GHz), 20 threads.
**Test result details**: [INTEL.md](https://github.com/opencv/opencv/files/13374093/INTEL.md)
**Brief summary for 4.8.1 vs 4.5.5**:
1. `CONV_5x5_S1_D1` dropped significant.
2. `CONV_1x1_S1_D1`, `CONV_3x3_S1_D1`, `DEPTHWISE_3x3_S1_D1`, `DEPTHWISW_3x3_S2_D1` dropped with small input shape.
---
TODO:
- [x] Perform tests on arm with each opencv version
- [x] Perform tests on x86 with each opencv version
- [x] Split each test classification with single test config
- [x] test enable fp16
doc: add crosscompile_with_multiarch #24629
Add cross compile tutorial for ubuntu/debian.
( I'm sorry to my poor English. )
Fix https://github.com/opencv/opencv/issues/24628
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Speed up ChessBoardDetector::findQuadNeighbors #24605
### Pull Request Readiness Checklist
Replaced brute-force algorithm with O(N^2) time complexity with kd-tree with something like O(N * log N) time complexity (maybe only in average case).
For example, on image from #23558 without quads filtering (by using `CALIB_CB_FILTER_QUADS` flag) finding chessboards corners took ~770 seconds on my laptop, of which finding quads neighbors took ~620 seconds.
Now finding chessboards corners takes ~155-160 seconds, of which finding quads neighbors takes only ~5-10 seconds.
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Add test for YoloX Yolo v6 and Yolo v8 #24611
This PR adds test for YOLOv6 model (which was absent before)
The onnx weights for the test are located in this PR [ #1126](https://github.com/opencv/opencv_extra/pull/1126)
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ht_dec.c: Improve MSVC arm64 popcount performance #24205
Use NEON instructions for ARM64 (implementation based on https://github.com/microsoft/STL/pull/2127, which is Apache licensed).
Godbolt output here: https://godbolt.org/z/q7GPTqT14
Related patch to openjpeg: https://github.com/uclouvain/openjpeg/pull/1479
### Pull Request Readiness Checklist
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dnn cuda: support Sub #24647
Related https://github.com/opencv/opencv/issues/24606#issuecomment-1837390257
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dnn onnx graph simplifier: handle optional inputs of Slice #24655
Resolves https://github.com/opencv/opencv/issues/24609
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Fix bug in ChessBoardDetector::findQuadNeighbors #24597
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I do not have more info on the platform as it is internal.
Without this fix, the error is:
core/src/arithm.simd.hpp:868:1: error: too few arguments provided to function-like macro invocation
868 | DEFINE_SIMD_ALL(cmp)
| ^
./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:93:5: note: expanded from macro 'DEFINE_SIMD_ALL'
93 | DEFINE_SIMD_NSAT(fun, __VA_ARGS__)
| ^
./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:89:5: note: expanded from macro 'DEFINE_SIMD_NSAT'
89 | DEFINE_SIMD_F64(fun, __VA_ARGS__)
| ^
./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:77:9: note: expanded from macro 'DEFINE_SIMD_F64'
77 | DEFINE_NOSIMD(__CV_CAT(fun, 64f), double, __VA_ARGS__)
| ^
./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:47:56: note: expanded from macro 'DEFINE_NOSIMD'
47 | DEFINE_NOSIMD_FUN(fun_name, c_type, __VA_ARGS__)
| ^
./third_party/OpenCV/public/modules/./core/src/arithm.simd.hpp:860:9: note: macro 'DEFINE_NOSIMD_FUN' defined here
860 | #define DEFINE_NOSIMD_FUN(fun, _T1, _Tvec, ...) \
G-API: Implement inference only mode for OV backend #24584
### Changes overview
Introduced `cv::gapi::wip::ov::benchmark_mode{}` compile argument which if enabled force `OpenVINO` backend to run only inference without populating input and copying back output tensors.
This mode is only relevant for measuring the performance of pure inference without data transfers. Similar approach is using on OpenVINO side in `benchmark_app`: https://github.com/openvinotoolkit/openvino/blob/master/samples/cpp/benchmark_app/benchmark_app.hpp#L134-L139
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Fix typo in ChessBoardDetector::generateQuads #24595
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Fix race condition in color_lab.cpp initLabTabs(). #24581
There is a race condition between when the static bool is initialized (which is thread safe) and its value check. This PR changes the static bool to a static lambda call to make it thread safe. The static_cast<void> in the end is to prevent unused variables warnings.
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Add support for custom padding in DNN preprocessing #24569
This PR add functionality for specifying value in padding.
It is required in many preprocessing pipelines in DNNs such as Yolox object detection model
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- Use the same tools and plugins for SDK build and AAR build
- Added script to test Gradle-based samples against local maven repo
- Various local fixes and debug prints
Fix graph fusion with commutative ops #24577
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24568
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1125
TODO:
- [x] replace recursive function to sequential
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Add yolov5n to tests #24553
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Fix out of image corners in cv::cornerSubPix #24527
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dnn: add openvino, opencl and cuda backends for layer normalization layer #24552
Merge after https://github.com/opencv/opencv/pull/24544.
Todo:
- [x] openvino
- [x] opencl
- [x] cuda
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This patch change lsx to baseline feature, and lasx to dispatch
feature. Additionally, the runtime detection methods for lasx and
lsx have been modified.
Replace double atomic in USAC #24499
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Reference to issue with atomic variable: #24281
Reference to bug with essential matrix: #24482
* add Winograd FP16 implementation
* fixed dispatching of FP16 code paths in dnn; use dynamic dispatcher only when NEON_FP16 is enabled in the build and the feature is present in the host CPU at runtime
* fixed some warnings
* hopefully fixed winograd on x64 (and maybe other platforms)
---------
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
dnn test: move layer norm tests into conformance tests #24544
Merge with https://github.com/opencv/opencv_extra/pull/1122
## Motivation
Some ONNX operators, such as `LayerNormalization`, `BatchNormalization` and so on, produce outputs for training (mean, stdev). So they have reference outputs of conformance tests for those training outputs as well. However, when it comes to inference, we do not need and produce those outputs for training here in dnn. Hence, output size does not match if we use dnn to infer those conformance models. This has become the barrier if we want to test these operators using their conformance tests.
<!--
| Operator | Inference needed | Outputs (required - total) | Optional outputs for training? |
| ----------------------- | ----------------------------------- | -------------------------- | ------------------------------ |
| BatchNormalization | Yes | 1 - 3 | Yes |
| Dropout | Maybe, can be eliminated via fusion | 1 - 2 | Yes |
| GRU | Yes | 0 - 2 | No |
| LSTM | Yes | 0 - 3 | No |
| LayerNormalization | Yes | 1 - 3 | Yes |
| MaxPool | Yes | 1 - 2 | Yes |
| RNN | Yes | 0 - 2 | No |
| SoftmaxCrossEntropyLoss | No | 1 - 2 | -- |
-->
**I checked all ONNX operators with optional outputs. Turns out there are only `BatchNormalization`, `Dropout`, `LayerNormalization` and `MaxPool` has optional outputs for training. All except `LayerNormalization` have models set for training mode and eval mode. Blame ONNX for that.**
## Solution
In this pull request, we remove graph outputs if the graph looks like the following:
```
[X] [Scale] [Bias] [X] [Scale] [Bias]
\ | / this patch \ | /
LayerNormalization -----------> LayerNormalization
/ | \ |
[Y] [Mean] [Stdev] [Y]
```
We can update conformance tests and turn on some cases as well if extending to more layers.
Notes:
1. This workaround does not solve expanded function operators if they are fused into a single operator, such as `$onnx/onnx/backend/test/data/node/test_layer_normalization_2d_axis1_expanded`, but they can be run without fusion. Note that either dnn or onnxruntime does not fuse those expanded function operators.
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Updated Android samples for modern Android studio. Added OpenCV from Maven support. #24473
Updated samples for recent Android studio:
- added namespace field that is required in build.gradle files
- replaced _switch_ by _if-else_ because it doesn't work with constants from resources
- added missed log library dependency in face-detection/jni/CMakeLists.txt
- use local.properties to define NDK location
Added support for OpenCV from Maven. Now you can choose 3 possible sources of OpenCV lib in settings.gradle: SDK path, local Maven repository, public Maven repository. (Creating Maven repository from SDK is added here #24456 )
There are differences in project configs for SDK and Maven versions:
- different dependencies in build.gradle
- different OpenCV library names in CMakeLists.txt
- SDK version requires OpenCV_DIR definition
Requires:
- https://github.com/opencv/ci-gha-workflow/pull/124
- https://github.com/opencv-infrastructure/opencv-gha-dockerfile/pull/26
Bugfix/qrcode version estimator #24364
Fixes https://github.com/opencv/opencv/issues/24366
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Fast gemm for einsum #24509
## This PR adds performance tests for Einsum Layer with FastGemm. See below results of performance test on different inputs
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Using cv2 dnn interface to run yolov8 model #24396
This is a sample code for using opencv dnn interface to run ultralytics yolov8 model for object detection.
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G-API: Advanced device selection for ONNX DirectML Execution Provider #24060
### Overview
Extend `cv::gapi::onnx::ep::DirectML` to accept `adapter name` as `ctor` parameter in order to select execution device by `name`.
E.g:
```
pp.cfgAddExecutionProvider(cv::gapi::onnx::ep::DirectML("Intel Graphics"));
```
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Handle huge images in IPP distanceTransform #24535
### Pull Request Readiness Checklist
* Do not use IPP for huge Mat (reproduced with https://github.com/opencv/opencv/issues/23895#issuecomment-1708132367 on `DIST_MASK_5`)
I have observed two types of errors on the reproducer from the issue:
1. When `temp` is not allocated:
```
Thread 1 "app" received signal SIGSEGV, Segmentation fault.
0x00007ffff65dc755 in icv_l9_ownDistanceTransform_5x5_8u32f_C1R_21B_g9e9 () from /home/dkurtaev/opencv_install/bin/../lib/libopencv_imgproc.so.408
(gdb) bt
#0 0x00007ffff65dc755 in icv_l9_ownDistanceTransform_5x5_8u32f_C1R_21B_g9e9 () from /home/dkurtaev/opencv_install/bin/../lib/libopencv_imgproc.so.408
#1 0x00007ffff659e8df in icv_l9_ippiDistanceTransform_5x5_8u32f_C1R () from /home/dkurtaev/opencv_install/bin/../lib/libopencv_imgproc.so.408
#2 0x00007ffff5c390f0 in cv::distanceTransform (_src=..., _dst=..., _labels=..., distType=2, maskSize=5, labelType=1) at /home/dkurtaev/opencv/modules/imgproc/src/distransform.cpp:854
#3 0x00007ffff5c396ef in cv::distanceTransform (_src=..., _dst=..., distanceType=2, maskSize=5, dstType=5) at /home/dkurtaev/opencv/modules/imgproc/src/distransform.cpp:903
#4 0x000055555555669e in main (argc=1, argv=0x7fffffffdef8) at /home/dkurtaev/main.cpp:18
```
2. When we keep `temp` allocated every time:
```
OpenCV(4.8.0-dev) Error: Assertion failed (udata < (uchar*)ptr && ((uchar*)ptr - udata) <= (ptrdiff_t)(sizeof(void*)+64)) in fastFree, file /home/dkurtaev/opencv/modules/core/src/alloc.cpp, line 191
terminate called after throwing an instance of 'cv::Exception'
what(): OpenCV(4.8.0-dev) /home/dkurtaev/opencv/modules/core/src/alloc.cpp:191: error: (-215:Assertion failed) udata < (uchar*)ptr && ((uchar*)ptr - udata) <= (ptrdiff_t)(sizeof(void*)+64) in function 'fastFree'
```
* Try enable IPP for 3x3 (see https://github.com/opencv/opencv/issues/15904)
* Reduce memory footprint with IPP
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Add weights yolov3 in models.yml #24496
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I don't know if this action is necessary, or the previous PR scale for the brach master.
Thanks.
Enable softmax layer vectorization on RISC-V RVV #24510
Related: https://github.com/opencv/opencv/pull/24466
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Fix some of the broken urls in docs #24521
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Commutative rules for DNN subgraphs fusion #24483
### Pull Request Readiness Checklist
related: https://github.com/opencv/opencv/pull/24463#issuecomment-1783033931
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Fix gstreamer backend with manual pipelines #24243
- Fix broken seeking in audio/video playback
- Fix broken audio playback
- Fix unreliable seeking
- Estimate frame count if it is not available directly
- Return -1 for frame count and fps if it is not available.
- Return 0 for fps if the video has variable frame rate
- Enable and fix tests
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1. Download two test videos:
```bash
wget https://github.com/ietf-wg-cellar/matroska-test-files/raw/master/test_files/test1.mkv
wget https://test-videos.co.uk/vids/jellyfish/mkv/360/Jellyfish_360_10s_5MB.mkv
```
2. I modified a OpenCV videoio sample to demonstrate the problem, here it is the patch: http://dpaste.com//C9MAT2K6W
3. Build the sample, on Ubuntu:
```bash
g++ -g videocapture_audio_combination.cpp -I/usr/include/opencv4 `pkg-config --libs --cflags opencv4` -o videocapture_audio_combination
```
4. Play an audio stream with seeking BEFORE the fix:
```bash
$ ./videocapture_audio_combination --audio "filesrc location=test1.mkv ! queue ! matroskademux name=demux demux.audio_0 ! decodebin ! audioconvert ! appsink"[ERROR:0@0.009] global cap.cpp:164 open VIDEOIO(GSTREAMER): raised OpenCV exception:
OpenCV(4.8.0-dev) ./modules/videoio/src/cap_gstreamer.cpp:153: error: (-215:Assertion failed) ptr in function 'get'
[ WARN:0@0.009] global cap.cpp:204 open VIDEOIO(GSTREAMER): backend is generally available but can't be used to capture by name
ERROR! Can't to open file: filesrc location=test1.mkv ! queue ! matroskademux name=demux demux.audio_0 ! decodebin ! audioconvert ! appsink
```
5. Play a video stream with seeking BEFORE the fix:
```bash
$ ./videocapture_audio_combination --audio "filesrc location=Jellyfish_360_10s_5MB.mkv ! queue ! matroskademux name=demux demux.video_0 ! decodebin ! videoconvert ! video/x-raw, format=BGR ! appsink drop=1"
[ WARN:0@0.034] global cap_gstreamer.cpp:1728 open OpenCV | GStreamer warning: Cannot query video position: status=1, value=22, duration=300
CAP_PROP_AUDIO_DATA_DEPTH: CV_16S
CAP_PROP_AUDIO_SAMPLES_PER_SECOND: 44100
CAP_PROP_AUDIO_TOTAL_CHANNELS: 0
CAP_PROP_AUDIO_TOTAL_STREAMS: [ WARN:0@0.034] global cap_gstreamer.cpp:1898 getProperty OpenCV | GStreamer: CAP_PROP_AUDIO_TOTAL_STREAMS property is not supported
0
[ WARN:0@0.034] global cap_gstreamer.cpp:1817 getProperty OpenCV | GStreamer: CAP_PROP_POS_MSEC property result may be unrealiable: https://github.com/opencv/opencv/issues/19025
Timestamp: 0.6218
Timestamp: 33.1085
Timestamp: 67.1274
Timestamp: 100.1182
Timestamp: 133.1204
Timestamp: 167.1195
Timestamp: 200.1161
Timestamp: 233.1147
Timestamp: 267.1194
Timestamp: 300.1202
[ WARN:0@0.338] global cap_gstreamer.cpp:1949 setProperty OpenCV | GStreamer warning: GStreamer: unable to seek
0:00:00.338215907 3892572 0x5592899c7580 WARN basesrc gstbasesrc.c:3127:gst_base_src_loop:<filesrc0> error: Internal data stream error.
0:00:00.338235884 3892572 0x5592899c7580 WARN basesrc gstbasesrc.c:3127:gst_base_src_loop:<filesrc0> error: streaming stopped, reason not-linked (-1)
0:00:00.338264287 3892572 0x5592899c7580 WARN queue gstqueue.c:992:gst_queue_handle_sink_event:<queue0> error: Internal data stream error.
0:00:00.338270329 3892572 0x5592899c7580 WARN queue gstqueue.c:992:gst_queue_handle_sink_event:<queue0> error: streaming stopped, reason not-linked (-1)
[ WARN:0@0.339] global cap_gstreamer.cpp:2784 handleMessage OpenCV | GStreamer warning: Embedded video playback halted; module filesrc0 reported: Internal data stream error.
[ WARN:0@0.339] global cap_gstreamer.cpp:1199 startPipeline OpenCV | GStreamer warning: unable to start pipeline
Number of audio samples: 0
Number of video frames: 10
[ WARN:0@0.339] global cap_gstreamer.cpp:1164 isPipelinePlaying OpenCV | GStreamer warning: GStreamer: pipeline have not been created
```
6. Play an audio stream with seeking AFTER the fix:
```bash
$ ./videocapture_audio_combination --audio "filesrc location=test1.mkv ! queue ! matroskademux name=demux demux.audio_0 ! decodebin ! audioconvert ! appsink"CAP_PROP_AUDIO_DATA_DEPTH: CV_16S
CAP_PROP_AUDIO_SAMPLES_PER_SECOND: 48000
CAP_PROP_AUDIO_TOTAL_CHANNELS: 2
CAP_PROP_AUDIO_TOTAL_STREAMS: [ WARN:0@0.025] global cap_gstreamer.cpp:1903 getProperty OpenCV | GStreamer: CAP_PROP_AUDIO_TOTAL_STREAMS property is not supported
0
Timestamp: 0.0000
Timestamp: 24.0000
Timestamp: 48.0000
Timestamp: 72.0000
Timestamp: 96.0000
Timestamp: 120.0000
Timestamp: 144.0000
Timestamp: 168.0000
Timestamp: 192.0000
Timestamp: 216.0000
Timestamp: 3500.0000
Timestamp: 3504.0000
Timestamp: 3528.0000
Timestamp: 3552.0000
Timestamp: 3576.0000
Timestamp: 3600.0000
Timestamp: 3624.0000
Timestamp: 3648.0000
Timestamp: 3672.0000
Timestamp: 3696.0000
Timestamp: 3720.0000
Timestamp: 3744.0000
Timestamp: 3768.0000
Timestamp: 3792.0000
Timestamp: 3816.0000
Timestamp: 3840.0000
Timestamp: 3864.0000
Timestamp: 3888.0000
Timestamp: 3912.0000
Timestamp: 3936.0000
```
7. Play a video stream with seeking AFTER the fix:
```bash
$ ./videocapture_audio_combination --audio "filesrc location=Jellyfish_360_10s_5MB.mkv ! queue ! matroskademux name=demux demux.video_0 ! decodebin ! videoconvert ! video/x-raw, format=BGR ! appsink drop=1"
[ WARN:0@0.033] global cap_gstreamer.cpp:1746 open OpenCV | GStreamer warning: Cannot query video position: status=1, value=22, duration=300
CAP_PROP_AUDIO_DATA_DEPTH: CV_16S
CAP_PROP_AUDIO_SAMPLES_PER_SECOND: 44100
CAP_PROP_AUDIO_TOTAL_CHANNELS: 0
CAP_PROP_AUDIO_TOTAL_STREAMS: [ WARN:0@0.034] global cap_gstreamer.cpp:1903 getProperty OpenCV | GStreamer: CAP_PROP_AUDIO_TOTAL_STREAMS property is not supported
0
Timestamp: 0.0000
Timestamp: 33.0000
Timestamp: 67.0000
Timestamp: 100.0000
Timestamp: 133.0000
Timestamp: 167.0000
Timestamp: 200.0000
Timestamp: 233.0000
Timestamp: 267.0000
Timestamp: 300.0000
0:00:00.335931693 3893501 0x55bbe76ad920 WARN matroskareadcommon matroska-read-common.c:759:gst_matroska_read_common_parse_skip:<demux:sink> Unknown CueTrackPositions subelement 0xf0 - ignoring
0:00:00.335952823 3893501 0x55bbe76ad920 WARN matroskareadcommon matroska-read-common.c:759:gst_matroska_read_common_parse_skip:<demux:sink> Unknown CueTrackPositions subelement 0xf0 - ignoring
0:00:00.335988029 3893501 0x55bbe76ad920 WARN basesrc gstbasesrc.c:1742:gst_base_src_perform_seek:<filesrc0> duplicate event found 184
Timestamp: 3467.0000
Timestamp: 3500.0000
Timestamp: 3533.0000
Timestamp: 3567.0000
Timestamp: 3600.0000
Timestamp: 3633.0000
Timestamp: 3667.0000
Timestamp: 3700.0000
Timestamp: 3733.0000
Timestamp: 3767.0000
Timestamp: 3800.0000
Timestamp: 3833.0000
Timestamp: 3867.0000
Timestamp: 3900.0000
Timestamp: 3933.0000
Timestamp: 3967.0000
Timestamp: 4000.0000
Timestamp: 4033.0000
Timestamp: 4067.0000
Timestamp: 4100.0000
```
dnn (onnx): add subgraph fusion tests #24500
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Added scripts for creating an AAR package and a local Maven repository with OpenCV library #24456
Added scripts for creating an AAR package and a local Maven repository with OpenCV library.
The build_java_shared_aar.py script creates AAR with Java + C++ shared libraries.
The build_static_aar.py script creates AAR with static C++ libraries.
The scripts use an Android project template. The project is almost a default Android AAR library project with empty Java code and one empty C++ library. Only build.gradle.template and CMakeLists.txt.template files contain significant changes.
See README.md for more information.
dnn onnx: add instance norm layer #24378
Resolves https://github.com/opencv/opencv/issues/24377
Relates https://github.com/opencv/opencv/pull/24092#discussion_r1349841644
| Perf | multi-thread | single-thread |
| - | - | - |
| x: [2, 64, 180, 240] | 3.95ms | 11.12ms |
Todo:
- [x] speed up by multi-threading
- [x] add perf
- [x] add backend: OpenVINO
- [x] add backend: CUDA
- [x] add backend: OpenCL (no fp16)
- [ ] add backend: CANN (will be done via https://github.com/opencv/opencv/pull/24462)
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```
force_builders=Linux OpenCL,Win64 OpenCL,Custom
buildworker:Custom=linux-4
build_image:Custom=ubuntu:18.04
modules_filter:Custom=none
disable_ipp:Custom=ON
```
Get the SSE2 condition match the emmintrin.h inclusion condition. #24495
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* improve and refactor softmax layer
* fix building error
* compatible region layer
* fix axisStep when disable SIMD
* fix dynamic array
* try to fix error
* use nlanes from VTraits
* move axisBias to srcOffset
* fix bug caused by axisBias
* remove macro
* replace #ifdef with #if for CV_SIMD
Added PyTorch fcnresnet101 segmentation conversion cases #24397
We write a sample code about transforming Pytorch fcnresnet101 to ONNX running on OpenCV.
The input source image was shooted by ourself.
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Backport to 4.x: patchNaNs() SIMD acceleration #24480
backport from #23098
connected PR in extra: [#1118@extra](https://github.com/opencv/opencv_extra/pull/1118)
### This PR contains:
* new SIMD code for `patchNaNs()`
* CPU perf test
<details>
<summary>Performance comparison</summary>
Geometric mean (ms)
|Name of Test|noopt|sse2|avx2|sse2 vs noopt (x-factor)|avx2 vs noopt (x-factor)|
|---|:-:|:-:|:-:|:-:|:-:|
|PatchNaNs::OCL_PatchNaNsFixture::(640x480, 32FC1)|0.019|0.017|0.018|1.11|1.07|
|PatchNaNs::OCL_PatchNaNsFixture::(640x480, 32FC4)|0.037|0.037|0.033|1.00|1.10|
|PatchNaNs::OCL_PatchNaNsFixture::(1280x720, 32FC1)|0.032|0.032|0.033|0.99|0.98|
|PatchNaNs::OCL_PatchNaNsFixture::(1280x720, 32FC4)|0.072|0.072|0.070|1.00|1.03|
|PatchNaNs::OCL_PatchNaNsFixture::(1920x1080, 32FC1)|0.051|0.051|0.050|1.00|1.01|
|PatchNaNs::OCL_PatchNaNsFixture::(1920x1080, 32FC4)|0.137|0.138|0.128|0.99|1.06|
|PatchNaNs::OCL_PatchNaNsFixture::(3840x2160, 32FC1)|0.137|0.128|0.129|1.07|1.06|
|PatchNaNs::OCL_PatchNaNsFixture::(3840x2160, 32FC4)|0.450|0.450|0.448|1.00|1.01|
|PatchNaNs::PatchNaNsFixture::(640x480, 32FC1)|0.149|0.029|0.020|5.13|7.44|
|PatchNaNs::PatchNaNsFixture::(640x480, 32FC2)|0.304|0.058|0.040|5.25|7.65|
|PatchNaNs::PatchNaNsFixture::(640x480, 32FC3)|0.448|0.086|0.059|5.22|7.55|
|PatchNaNs::PatchNaNsFixture::(640x480, 32FC4)|0.601|0.133|0.083|4.51|7.23|
|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC1)|0.451|0.093|0.060|4.83|7.52|
|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC2)|0.892|0.184|0.126|4.85|7.06|
|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC3)|1.345|0.311|0.230|4.32|5.84|
|PatchNaNs::PatchNaNsFixture::(1280x720, 32FC4)|1.831|0.546|0.436|3.35|4.20|
|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC1)|1.017|0.250|0.160|4.06|6.35|
|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC2)|2.077|0.646|0.605|3.21|3.43|
|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC3)|3.134|1.053|0.961|2.97|3.26|
|PatchNaNs::PatchNaNsFixture::(1920x1080, 32FC4)|4.222|1.436|1.288|2.94|3.28|
|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC1)|4.225|1.401|1.277|3.01|3.31|
|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC2)|8.310|2.953|2.635|2.81|3.15|
|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC3)|12.396|4.455|4.252|2.78|2.92|
|PatchNaNs::PatchNaNsFixture::(3840x2160, 32FC4)|17.174|5.831|5.824|2.95|2.95|
</details>
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dnn: add shared fastNorm kernel for mvn, instance norm and layer norm #24409
Relates https://github.com/opencv/opencv/pull/24378#issuecomment-1756906570
TODO:
- [x] add fastNorm
- [x] refactor layer norm with fastNorm
- [x] refactor mvn with fastNorm
- [ ] add onnx mvn in importer (in a new PR?)
- [ ] refactor instance norm with fastNorm (in another PR https://github.com/opencv/opencv/pull/24378, need to merge this one first though)
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Extend the signature of imdecodemulti() #24405
(Edited after addressing Reviewers' comments.)
Add an argument to `imdecodemulti()` to enable optional selection of pages of multi-page images.
Be default, all pages are decoded. If used, the additional argument may specify a continuous selection of pages to decode.
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Refactor ObjectiveC Range class #24454
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Fix for build issue in #24405
Video tracking (dnn): set backend and target for TrackerVit #24461Resolves#24460
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videoio: Add raw encoded video stream muxing to cv::VideoWriter with CAP_FFMPEG #24363
Allow raw encoded video streams (e.g. h264[5]) to be encapsulated by `cv::VideoWriter` to video containers (e.g. mp4/mkv).
Operates in a similar way to https://github.com/opencv/opencv/pull/15290 where encapsulation is enabled by setting the `VideoWriterProperties::VIDEOWRITER_PROP_RAW_VIDEO` flag when constructing `cv::VideoWriter` e.g.
```
VideoWriter container(fileNameOut, api, fourcc, fps, { width, height }, { VideoWriterProperties::VIDEOWRITER_PROP_RAW_VIDEO, 1 });
```
and each raw encoded frame is passed as single row of a `CV_8U` `cv::Mat`.
The main reason for this PR is to allow `cudacodec::VideoWriter` to output its encoded streams to a suitable container, see https://github.com/opencv/opencv_contrib/pull/3569.
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Ellipses supported added for Einsum Layer #24322
This PR added addresses issues not covered in #24037. Namely these are:
Test case for this patch is in this PR [#1106](https://github.com/opencv/opencv_extra/pull/1106) in opencv extra
Added:
- [x] Broadcasting reduction "...ii ->...I"
- [x] Add lazy shape deduction. "...ij, ...jk->...ik"
Features to add:
- [ ] Add implicit output computation support. "bij,bjk ->" (output subscripts should be "bik")
- [ ] Add support for CUDA backend
- [ ] BatchWiseMultiply optimize
- [ ] Performance test
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Pertaining Issue: https://github.com/opencv/opencv/issues/5697
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* Optimize some function with lasx.
Optimize some function with lasx. #23929
This patch optimizes some lasx functions and reduces the runtime of opencv_test_core from 662,238ms to 633603ms on the 3A5000 platform.
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dnn: fix HAVE_TIMVX macro definition in dnn test #24425
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Native ONNX to Inference Engine backend #21066Resolves#21052
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This pointer is called unconditionally in BarcodeImpl::initDecode
assuming the size of the image is outside the specified bounds. This
seems to not cause problems on optimized builds, I assume because the
optimizer sees through the processImageScale call to see that it can be
reduced to a resize call. Leaving it as is relies on undefined
behavior.
This was the least invasive change I could make, however, it might be
worthwhile to pull up the logic for a resize so that a SuperScale does
not need to be allocated, which seems to be the most common case.
Speed up line merging in INTER_AREA #24412
This provides a 10 to 20% speed-up.
Related perf test fix: https://github.com/opencv/opencv/pull/24417
This is a split of https://github.com/opencv/opencv/pull/23525 that will be updated to only deal with column merging.
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Enable multicore CUDA compilation #24382
CUDA source files are compiled single threaded. The option `--threads` was introduced in NVCC 11.2. The option specifies the number of threads to be used for compilation (see [NVIDIA NVCC Documentation](https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html#threads-number-t)).
With CMake 3.12 the environment variable `CMAKE_BUILD_PARALLEL_LEVEL` was introduced (see [CMake Documentation](https://cmake.org/cmake/help/latest/envvar/CMAKE_BUILD_PARALLEL_LEVEL.html)). This variable is used to set the NVCC `--threads` option.
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- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Supporting protobuf v22 and later(with abseil-cpp/C++17) #24372
fix https://github.com/opencv/opencv/issues/24369
related https://github.com/opencv/opencv/issues/23791
1. This patch supports external protobuf v22 and later, it required abseil-cpp and c++17.
Even if the built-in protobuf is upgraded to v22 or later,
the dependency on abseil-cpp and the requirement for C++17 will continue.
2. Some test for caffe required patched protobuf, so this patch disable them.
This patch is tested by following libraries.
- Protobuf: /usr/local/lib/libprotobuf.so (4.24.4)
- abseil-cpp: YES (20230125)
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
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* added more or less cross-platform (based on POSIX signal() semantics) method to detect various NEON extensions, such as FP16 SIMD arithmetics, BF16 SIMD arithmetics, SIMD dotprod etc. It could be propagated to other instruction sets if necessary.
* hopefully fixed compile errors
* continue to fix CI
* another attempt to fix build on Linux aarch64
* * reverted to the original method to detect special arm neon instructions without signal()
* renamed FP16_SIMD & BF16_SIMD to NEON_FP16 and NEON_BF16, respectively
* removed extra whitespaces
GSoC Add ONNX Support for GatherElements #24092
Merge with: https://github.com/opencv/opencv_extra/pull/1082
Adds support to the ONNX operator GatherElements [operator docs](https://github.com/onnx/onnx/blob/main/docs/Operators.md#GatherElements)
Added tests to opencv_extra at pull request https://github.com/opencv/opencv_extra/pull/1082
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Fixed CumSum layer inplace flag #24367
When exclusive is false:
dst[i] = dst[i-1] + src[i]
When exclusive is true:
dst[i] = dst[i-1] + src[i-1]
So CumSum layer can be inplace only when exclusive flag is false.
Encode QR code data to UTF-8 #24350
### Pull Request Readiness Checklist
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1105
resolves https://github.com/opencv/opencv/issues/23728
This is first PR in a series. Here we just return a raw Unicode. Later I will try expand QR codes decoding methods to use ECI assignment number and return a string with proper encoding, not only UTF-8 or raw unicode.
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Implement color conversion from RGB to YUV422 family #24333
Related PR for extra: https://github.com/opencv/opencv_extra/pull/1104
Hi,
This patch provides CPU and OpenCL implementations of color conversions from RGB/BGR to YUV422 family (such as UYVY and YUY2).
These features would come in useful for enabling standard RGB images to be supplied as input to algorithms or networks that make use of images in YUV422 format directly (for example, on resource constrained devices working with camera images captured in YUV422).
The code, tests and perf tests are all written following the existing pattern. There is also an example `bin/example_cpp_cvtColor_RGB2YUV422` that loads an image from disk, converts it from BGR to UYVY and then back to BGR, and displays the result as a visual check that the conversion works.
The OpenCL performance for the forward conversion implemented here is the same as the existing backward conversion on my hardware. The CPU implementation, unfortunately, isn't very optimized as I am not yet familiar with the SIMD code.
Please let me know if I need to fix something or can make other modifications.
Thanks!
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
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- [x] The feature is well documented and sample code can be built with the project CMake
* remove Conformance from test names
* integrate neon optimization into default
* quick fix: define CV_NEON_AARCH64 0 for non NEON platforms
* remove var batch that leads to memory leak
* put neon code back to fast_gemm_kernels.simd
* reorganize code to reduce duplicate code
Add HAL implementation hooks to cv::flip() and cv::rotate() functions from core module #24233
Hello,
This change proposes the addition of HAL hooks for cv::flip() and cv::rotate() functions from OpenCV core module.
Flip and rotation are functions commonly available from 2D hardware accelerators. This is convenient provision to enable custom optimized implementation of image flip/rotation on systems embedding such accelerator.
Thank you
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Rewrite Universal Intrinsic code: float related part #24325
The goal of this series of PRs is to modify the SIMD code blocks guarded by CV_SIMD macro: rewrite them by using the new Universal Intrinsic API.
The series of PRs is listed below:
#23885 First patch, an example
#23980 Core module
#24058 ImgProc module, part 1
#24132 ImgProc module, part 2
#24166 ImgProc module, part 3
#24301 Features2d and calib3d module
#24324 Gapi module
This patch (hopefully) is the last one in the series.
This patch mainly involves 3 parts
1. Add some modifications related to float (CV_SIMD_64F)
2. Use `#if (CV_SIMD || CV_SIMD_SCALABLE)` instead of `#if CV_SIMD || CV_SIMD_SCALABLE`,
then we can get the `CV_SIMD` module that is not enabled for `CV_SIMD_SCALABLE` by looking for `if CV_SIMD`
3. Summary of `CV_SIMD` blocks that remains unmodified: Updated comments
- Some blocks will cause test fail when enable for RVV, marked as `TODO: enable for CV_SIMD_SCALABLE, ....`
- Some blocks can not be rewrited directly. (Not commented in the source code, just listed here)
- ./modules/core/src/mathfuncs_core.simd.hpp (Vector type wrapped in class/struct)
- ./modules/imgproc/src/color_lab.cpp (Array of vector type)
- ./modules/imgproc/src/color_rgb.simd.hpp (Array of vector type)
- ./modules/imgproc/src/sumpixels.simd.hpp (fixed length algorithm, strongly ralated with `CV_SIMD_WIDTH`)
These algorithms will need to be redesigned to accommodate scalable backends.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [ ] I agree to contribute to the project under Apache 2 License.
- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Fix tests writing to current work dir #24343
Several tests were writing files in the current work directory and did not clean up after test. Moved all temporary files to the `/tmp` dir and added a cleanup code.
Fixed CumSum dnn layer #24353Fixes#20110
The algorithm had several errors, so I rewrote it.
Also the layer didn't work with non constant axis tensor. Fixed it.
Enabled CumSum layer tests from ONNX conformance.
OpenVINO backend for INT8 models #23987
### Pull Request Readiness Checklist
TODO:
- [x] DetectionOutput layer (https://github.com/opencv/opencv/pull/24069)
- [x] Less FP32 fallbacks (i.e. Sigmoid, eltwise sum)
- [x] Accuracy, performance tests (https://github.com/opencv/opencv/pull/24039)
- [x] Single layer tests (convolution)
- [x] ~~Fixes for OpenVINO 2022.1 (https://pullrequest.opencv.org/buildbot/builders/precommit_custom_linux/builds/100334)~~
Performace results for object detection model `coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite`:
| backend | performance (median time) |
|---|---|
| OpenCV | 77.42ms |
| OpenVINO 2023.0 | 10.90ms |
CPU: `11th Gen Intel(R) Core(TM) i5-1135G7 @ 2.40GHz`
Serialized model per-layer stats (note that Convolution should use `*_I8` primitives if they are quantized correctly): https://gist.github.com/dkurt/7772bbf1907035441bb5454f19f0feef
---
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Optimization for parallelization when large core number #24280
**Problem description:**
When the number of cores is large, OpenCV’s thread library may reduce performance when processing parallel jobs.
**The reason for this problem:**
When the number of cores (the thread pool initialized the threads, whose number is as same as the number of cores) is large, the main thread will spend too much time on waking up unnecessary threads.
When a parallel job needs to be executed, the main thread will wake up all threads in sequence, and then wait for the signal for the job completion after waking up all threads. When the number of threads is larger than the parallel number of a job slices, there will be a situation where the main thread wakes up the threads in sequence and the awakened threads have completed the job, but the main thread is still waking up the other threads. The threads woken up by the main thread after this have nothing to do, and the broadcasts made by the waking threads take a lot of time, which reduce the performance.
**Solution:**
Reduce the time for the process of main thread waking up the worker threads through the following two methods:
• The number of threads awakened by the main thread should be adjusted according to the parallel number of a job slices. If the number of threads is greater than the number of the parallel number of job slices, the total number of threads awakened should be reduced.
• In the process of waking up threads in sequence, if the main thread finds that all parallel job slices have been allocated, it will jump out of the loop in time and wait for the signal for the job completion.
**Performance Test:**
The tests were run in the manner described by https://github.com/opencv/opencv/wiki/HowToUsePerfTests.
At core number = 160, There are big performance gain in some cases.
Take the following cases in the video module as examples:
OpticalFlowPyrLK_self::Path_Idx_Cn_NPoints_WSize_Deriv::("cv/optflow/frames/VGA_%02d.png", 2, 1, (9, 9), 11, true)
Performance improves 191%:0.185405ms ->0.0636496ms
perf::DenseOpticalFlow_VariationalRefinement::(320x240, 10, 10)
Performance improves 112%:23.88938ms -> 11.2562ms
Among all the modules, the performance improvement is greatest on module video, and there are also certain improvements on other modules.
At core number = 160, the times labeled below are the geometric mean of the average time of all cases for one module. The optimization is available on each module.
overall | time(ms) | | | | | | |
-- | -- | -- | -- | -- | -- | -- | -- | --
module name | gapi | dnn | features2d | objdetect | core | imgproc | stitching | video
original | 0.185 | 1.586 | 9.998 | 11.846 | 0.205 | 0.215 | 164.409 | 0.803
optimized | 0.174 | 1.353 | 9.535 | 11.105 | 0.199 | 0.185 | 153.972 | 0.489
Performance improves | 6% | 17% | 5% | 7% | 3% | 16% | 7% | 64%
Meanwhile, It is found that adjusting the order of test cases will have an impact on some test cases. For example, we used option --gtest-shuffle to run opencv_perf_gapi, the performance of TestPerformance::CmpWithScalarPerfTestFluid/CmpWithScalarPerfTest::(compare_f, CMP_GE, 1920x1080, 32FC1, { gapi.kernel_package }) case had 30% changes compared to the case without shuffle. I would like to ask if you have also encountered such a situation and could you share your experience?
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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dnn: merge tests from test_halide_layers to test_backends #24283
Context: https://github.com/opencv/opencv/pull/24231#pullrequestreview-1628649980
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
cmake: Fix riscv-gnu toolchain file. #24305
cmake(3.22.1) failed without the keyword `PATHS` on my device when I manually set `TOOLCHAIN_COMPILER_LOCATION_HINT` in command. And this patch is going to fix this issue.
[CMake Doc](https://cmake.org/cmake/help/latest/command/find_program.html):
> find_program (
> <VAR>
> name | NAMES name1 [name2 ...] [NAMES_PER_DIR]
> [HINTS [path | ENV var]... ]
> [PATHS [path | ENV var]... ]
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [ ] I agree to contribute to the project under Apache 2 License.
- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Rewrite Universal Intrinsic code: features2d and calib3d module. #24301
The goal of this series of PRs is to modify the SIMD code blocks guarded by CV_SIMD macro: rewrite them by using the new Universal Intrinsic API.
This is the modification to the features2d module and calib3d module.
Test with clang 16 and QEMU v7.0.0. `AP3P.ctheta1p_nan_23607` failed beacuse of a small calculation error. But this patch does not touch the relevant code, and this error always reproduce on QEMU, regardless of whether the patch is applied or not. I think we can ignore it
```
[ RUN ] AP3P.ctheta1p_nan_23607
/home/hanliutong/project/opencv/modules/calib3d/test/test_solvepnp_ransac.cpp:2319: Failure
Expected: (cvtest::norm(res.colRange(0, 2), expected, NORM_INF)) <= (3e-16), actual: 3.33067e-16 vs 3e-16
[ FAILED ] AP3P.ctheta1p_nan_23607 (26 ms)
...
[==========] 148 tests from 64 test cases ran. (1147114 ms total)
[ PASSED ] 147 tests.
[ FAILED ] 1 test, listed below:
[ FAILED ] AP3P.ctheta1p_nan_23607
```
Note: There are 2 test cases failed with GCC 13.2.1 without this patch, seems like there are someting wrong with RVV part on GCC.
```
[----------] Global test environment tear-down
[==========] 148 tests from 64 test cases ran. (1511399 ms total)
[ PASSED ] 146 tests.
[ FAILED ] 2 tests, listed below:
[ FAILED ] Calib3d_StereoSGBM.regression
[ FAILED ] Calib3d_StereoSGBM_HH4.regression
```
The patch is partially auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter).
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [ ] I agree to contribute to the project under Apache 2 License.
- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Add Support for Einsum Layer #24037
### This PR adding support for [Einsum Layer](https://pytorch.org/docs/stable/generated/torch.einsum.html) (in progress).
This PR is currently not to be merged but only reviewed. Test cases are located in [#1090](https://github.com/opencv/opencv_extra/pull/1090)RP in OpenCV extra
**DONE**:
- [x] 2-5D GMM support added
- [x] Matrix transpose support added
- [x] Reduction type comupte 'ij->j'
- [x] 2nd shape computation - during forward
**Next PRs**:
- [ ] Broadcasting reduction "...ii ->...i"
- [ ] Add lazy shape deduction. "...ij, ...jk->...ik"
- [ ] Add implicit output computation support. "bij,bjk ->" (output subscripts should be "bik")
- [ ] Add support for CUDA backend
- [ ] BatchWiseMultiply optimize
**Later in 5.x version (requires support for 1D matrices)**:
- [ ] Add 1D vector multiplication support
- [ ] Inter product "i, i" (problems with 1D shapes)
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
* first commit
* turned C from input to constant; force C constant in impl; better handling 0d/1d cases
* integrate with gemm from ficus nn
* fix const inputs
* adjust threshold for int8 tryQuantize
* adjust threshold for int8 quantized 2
* support batched gemm and matmul; tune threshold for rcnn_ilsvrc13; update googlenet
* add gemm perf against innerproduct
* add perf tests for innerproduct with bias
* fix perf
* add memset
* renamings for next step
* add dedicated perf gemm
* add innerproduct in perf_gemm
* remove gemm and innerproduct perf tests from perf_layer
* add perf cases for vit sizes; prepack constants
* remove batched gemm; fix wrong trans; optimize KC
* remove prepacking for const A; several fixes for const B prepacking
* add todos and gemm expression
* add optimized branch for avx/avx2
* trigger build
* update macros and signature
* update signature
* fix macro
* fix bugs for neon aarch64 & x64
* add backends: cuda, cann, inf_ngraph and vkcom
* fix cuda backend
* test commit for cuda
* test cuda backend
* remove debug message from cuda backend
* use cpu dispatcher
* fix neon macro undef in dispatcher
* fix dispatcher
* fix inner kernel for neon aarch64
* fix compiling issue on armv7; try fixing accuracy issue on other platforms
* broadcast C with beta multiplied; improve func namings
* fix bug for avx and avx2
* put all platform-specific kernels in dispatcher
* fix typos
* attempt to fix compile issues on x64
* run old gemm when neon, avx, avx2 are all not available; add kernel for armv7 neon
* fix typo
* quick fix: add macros for pack4
* quick fix: use vmlaq_f32 for armv7
* quick fix for missing macro of fast gemm pack f32 4
* disable conformance tests when optimized branches are not supported
* disable perf tests when optimized branches are not supported
* decouple cv_try_neon and cv_neon_aarch64
* drop googlenet_2023; add fastGemmBatched
* fix step in fastGemmBatched
* cpu: fix initialization ofb; gpu: support batch
* quick followup fix for cuda
* add default kernels
* quick followup fix to avoid macro redef
* optmized kernels for lasx
* resolve mis-alignment; remove comments
* tune performance for x64 platform
* tune performance for neon aarch64
* tune for armv7
* comment time consuming tests
* quick follow-up fix
VIT track(gsoc realtime object tracking model) #24201
Vit tracker(vision transformer tracker) is a much better model for real-time object tracking. Vit tracker can achieve speeds exceeding nanotrack by 20% in single-threaded mode with ARM chip, and the advantage becomes even more pronounced in multi-threaded mode. In addition, on the dataset, vit tracker demonstrates better performance compared to nanotrack. Moreover, vit trackerprovides confidence values during the tracking process, which can be used to determine if the tracking is currently lost.
opencv_zoo: https://github.com/opencv/opencv_zoo/pull/194
opencv_extra: [https://github.com/opencv/opencv_extra/pull/1088](https://github.com/opencv/opencv_extra/pull/1088)
# Performance comparison is as follows:
NOTE: The speed below is tested by **onnxruntime** because opencv has poor support for the transformer architecture for now.
ONNX speed test on ARM platform(apple M2)(ms):
| thread nums | 1| 2| 3| 4|
|--------|--------|--------|--------|--------|
| nanotrack| 5.25| 4.86| 4.72| 4.49|
| vit tracker| 4.18| 2.41| 1.97| **1.46 (3X)**|
ONNX speed test on x86 platform(intel i3 10105)(ms):
| thread nums | 1| 2| 3| 4|
|--------|--------|--------|--------|--------|
| nanotrack|3.20|2.75|2.46|2.55|
| vit tracker|3.84|2.37|2.10|2.01|
opencv speed test on x86 platform(intel i3 10105)(ms):
| thread nums | 1| 2| 3| 4|
|--------|--------|--------|--------|--------|
| vit tracker|31.3|31.4|31.4|31.4|
preformance test on lasot dataset(AUC is the most important data. Higher AUC means better tracker):
|LASOT | AUC| P| Pnorm|
|--------|--------|--------|--------|
| nanotrack| 46.8| 45.0| 43.3|
| vit tracker| 48.6| 44.8| 54.7|
[https://youtu.be/MJiPnu1ZQRI](https://youtu.be/MJiPnu1ZQRI)
In target tracking tasks, the score is an important indicator that can indicate whether the current target is lost. In the video, vit tracker can track the target and display the current score in the upper left corner of the video. When the target is lost, the score drops significantly. While nanotrack will only return 0.9 score in any situation, so that we cannot determine whether the target is lost.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Rewrite Universal Intrinsic code: ImgProc (CV_SIMD_WIDTH related Part) #24166
Related PR: #24058, #24132. The goal of this series of PRs is to modify the SIMD code blocks in the opencv/modules/imgproc folder by using the new Universal Intrinsic API.
The modification of this PR mainly focuses on the code that uses the `CV_SIMD_WIDTH` macro. This macro is sometimes used for loop tail processing, such as `box_filter.simd.hpp` and `morph.simd.hpp`.
```cpp
#if CV_SIMD
int i = 0;
for (i < n - v_uint16::nlanes; i += v_uint16::nlanes) {
// some universal intrinsic code
// e.g. v_uint16...
}
#if CV_SIMD_WIDTH > 16
for (i < n - v_uint16x8::nlanes; i += v_uint16x8::nlanes) {
// handle loop tail by 128 bit SIMD
// e.g. v_uint16x8
}
#endif //CV_SIMD_WIDTH
#endif// CV_SIMD
```
The main contradiction is that the variable-length Universal Intrinsic backend cannot use 128bit fixed-length data structures. Therefore, this PR uses the scalar loop to handle the loop tail.
This PR is marked as draft because the modification of the `box_filter.simd.hpp` file caused a compilation error. The cause of the error is initially believed to be due to an internal error in the GCC compiler.
```bash
box_filter.simd.hpp:1162:5: internal compiler error: Segmentation fault
1162 | }
| ^
0xe03883 crash_signal
/wafer/share/gcc/gcc/toplev.cc:314
0x7ff261c4251f ???
./signal/../sysdeps/unix/sysv/linux/x86_64/libc_sigaction.c:0
0x6bde48 hash_set<rtl_ssa::set_info*, false, default_hash_traits<rtl_ssa::set_info*> >::iterator::operator*()
/wafer/share/gcc/gcc/hash-set.h:125
0x6bde48 extract_single_source
/wafer/share/gcc/gcc/config/riscv/riscv-vsetvl.cc:1184
0x6bde48 extract_single_source
/wafer/share/gcc/gcc/config/riscv/riscv-vsetvl.cc:1174
0x119ad9e pass_vsetvl::propagate_avl() const
/wafer/share/gcc/gcc/config/riscv/riscv-vsetvl.cc:4087
0x119ceaf pass_vsetvl::execute(function*)
/wafer/share/gcc/gcc/config/riscv/riscv-vsetvl.cc:4344
0x119ceaf pass_vsetvl::execute(function*)
/wafer/share/gcc/gcc/config/riscv/riscv-vsetvl.cc:4325
Please submit a full bug report, with preprocessed source (by using -freport-bug).
Please include the complete backtrace with any bug report.
```
This PR can be compiled with Clang 16, and `opencv_test_imgproc` is passed on QEMU.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
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Patch to opencv_extra has the same branch name.
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Python: support tuple src for cv::add()/subtract()/... #24074
fix https://github.com/opencv/opencv/issues/24057
### Pull Request Readiness Checklist
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Rewrite Universal Intrinsic code by using new API: ImgProc module Part 2 #24132
The goal of this series of PRs is to modify the SIMD code blocks guarded by CV_SIMD macro in the opencv/modules/imgproc folder: rewrite them by using the new Universal Intrinsic API.
This is the second part of the modification to the Imgproc module ( Part 1: #24058 ), And I tested this patch on RVV (QEMU) and AVX devices, `opencv_test_imgproc` is passed.
The patch is partially auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter).
### Pull Request Readiness Checklist
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Patch to opencv_extra has the same branch name.
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In the previous code, there was a memory leak issue where the
previously allocated memory was not freed upon a failed realloc
operation. This commit addresses the problem by releasing the old
memory before setting the pointer to NULL in case of a realloc failure.
This ensures that memory is properly managed and avoids potential
memory leaks.
Skip test on SkipTestException at fixture's constructor (version 2) #24250
### Pull Request Readiness Checklist
Another version of https://github.com/opencv/opencv/pull/24186 (reverted by https://github.com/opencv/opencv/pull/24223). Current implementation cannot handle skip exception at `static void SetUpTestCase` but works on `virtual void SetUp`.
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
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Patch to opencv_extra has the same branch name.
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Rewrite Universal Intrinsic code by using new API: ImgProc module. #24058
The goal of this series of PRs is to modify the SIMD code blocks guarded by CV_SIMD macro in the `opencv/modules/imgproc` folder: rewrite them by using the new Universal Intrinsic API.
For easier review, this PR includes a part of the rewritten code, and another part will be brought in the next PR (coming soon). I tested this patch on RVV (QEMU) and AVX devices, `opencv_test_imgproc` is passed.
The patch is partially auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter), related PR https://github.com/opencv/opencv/pull/23885 and https://github.com/opencv/opencv/pull/23980.
### Pull Request Readiness Checklist
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- [ ] I agree to contribute to the project under Apache 2 License.
- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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Fix undefined behavior arithmetic in copyMakeBorder and adjustROI. #24260
This is due to the undefined: negative int multiplied by size_t pointer increment.
To test, compile with:
```
mkdir build
cd build
cmake ../ -DCMAKE_C_FLAGS_INIT="-fsanitize=undefined" -DCMAKE_CXX_FLAGS_INIT="-fsanitize=undefined" -DCMAKE_C_COMPILER="/usr/bin/clang" -DCMAKE_CXX_COMPILER="/usr/bin/clang++" -DCMAKE_SHARED_LINKER_FLAGS="-fsanitize=undefined -lubsan"
```
And run:
```
make -j opencv_test_core && ./bin/opencv_test_core --gtest_filter=*UndefinedBehavior*
```
### Pull Request Readiness Checklist
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- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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Added default dimension value to tensorflow ArgMax and ArgMin layers #24266
Added default dimension value to tensorflow ArgMax and ArgMin layers.
Added exception when accessing layer's input with out of range index.
Fixes https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=48452
Modify the outputVideoFormat after changing the output format in MSMF backend #24142
After changing the output format, need to modify the outputVideoFormat, otherwise the outputVideoFormat is always CV_CAP_MODE_BGR, and an error will occur when converting the format in retrieveVideoFrame(), and will always enter "case CV_CAP_MODE_BGR:" process.
### Pull Request Readiness Checklist
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- [ ] I agree to contribute to the project under Apache 2 License.
- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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Co-authored-by: 李龙 <lilong@sobey.com>
Use ngraph::Output in OpenVINO backend wrapper #24196
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24102
* Use `ngraph::Output<ngraph::Node>>` insead of `std::shared_ptr<ngraph::Node>` as a backend wrapper. It lets access to multi-output nodes: https://github.com/opencv/opencv/blob/588ddf1b181aa7243144b27d65fc7690fb89e344/modules/dnn/src/net_openvino.cpp#L501-L504
* All layers can be customizable with OpenVINO >= 2022.1. nGraph reference code used for default layer implementation does not required CPU plugin also (might be tested by commenting CPU plugin at `/opt/intel/openvino/runtime/lib/intel64/plugins.xml`).
* Correct inference if only intermediate blobs requested.
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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Properly preserve chi_table license as mandated by BSD-3-Clause #24204
Amend reference to online hosted file with the full license quotation as mandated by the original license.
Fix distanceTransform for inputs with large step and height #24214
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23895
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
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Patch to opencv_extra has the same branch name.
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Minor optimization of two lines intersection #24216
### Pull Request Readiness Checklist
Not significant, but we can reduce number of multiplications while compute two lines intersection. Both methods are used heavily in their modules.
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
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- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
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Patch to opencv_extra has the same branch name.
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The address sanitizer highlighted this issue in our code base. It
looks like the code is currently grabbing a pointer to a temporary
object and then performing operations on it.
I printed some information right before the asan crash:
eigensolver address: 0x7f0ad95032f0
eigensolver size: 4528
eig_vecs_ ptr: 0x7f0ad95045e0
eig_vecs_ offset: 4848
This shows that `eig_vecs_` points past the end of `eigensolver`. In
other words, it points at the temporary object created by the
`eigensolver.eigenvectors()` call.
Compare the docs for `.eigenvalues()`:
https://eigen.tuxfamily.org/dox/classEigen_1_1EigenSolver.html#a0f507ad7ab14797882f474ca8f2773e7
to the docs for `.eigenvectors()`:
https://eigen.tuxfamily.org/dox/classEigen_1_1EigenSolver.html#a66288022802172e3ee059283b26201d7
The difference in return types is interesting. `.eigenvalues()`
returns a reference. But `.eigenvectors()` returns a matrix.
This patch here fixes the problem by saving the temporary object and
then grabbing a pointer into it.
This is a curated snippet of the original asan failure:
==12==ERROR: AddressSanitizer: stack-use-after-scope on address 0x7fc633704640 at pc 0x7fc64f7f1593 bp 0x7ffe8875fc90 sp 0x7ffe8875fc88
READ of size 8 at 0x7fc633704640 thread T0
#0 0x7fc64f7f1592 in cv::usac::EssentialMinimalSolverStewenius5ptsImpl::estimate(std::__1::vector<int, std::__1::allocator<int> > const&, std::__1::vector<cv::Mat, std::__1::allocator<cv::Mat> >&) const /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/essential_solver.cpp:181:48
#1 0x7fc64f915d92 in cv::usac::EssentialEstimatorImpl::estimateModels(std::__1::vector<int, std::__1::allocator<int> > const&, std::__1::vector<cv::Mat, std::__1::allocator<cv::Mat> >&) const /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/estimator.cpp:110:46
#2 0x7fc64fa74fb0 in cv::usac::Ransac::run(cv::Ptr<cv::usac::RansacOutput>&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/ransac_solvers.cpp:152:58
#3 0x7fc64fa6cd8e in cv::usac::run(cv::Ptr<cv::usac::Model const> const&, cv::_InputArray const&, cv::_InputArray const&, int, cv::Ptr<cv::usac::RansacOutput>&, cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/ransac_solvers.cpp:1010:16
#4 0x7fc64fa6fb46 in cv::usac::findEssentialMat(cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, int, double, double, cv::_OutputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/ransac_solvers.cpp:527:9
#5 0x7fc64f3b5522 in cv::findEssentialMat(cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, int, double, double, int, cv::_OutputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/five-point.cpp:437:16
#6 0x7fc64f3b7e00 in cv::findEssentialMat(cv::_InputArray const&, cv::_InputArray const&, cv::_InputArray const&, int, double, double, cv::_OutputArray const&) /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/five-point.cpp:486:12
...
Address 0x7fc633704640 is located in stack of thread T0 at offset 17984 in frame
#0 0x7fc64f7ed4ff in cv::usac::EssentialMinimalSolverStewenius5ptsImpl::estimate(std::__1::vector<int, std::__1::allocator<int> > const&, std::__1::vector<cv::Mat, std::__1::allocator<cv::Mat> >&) const /proc/self/cwd/external/com_github_opencv_opencv/modules/calib3d/src/usac/essential_solver.cpp:36
This frame has 63 object(s):
[32, 56) 'coefficients' (line 38)
[96, 384) 'ee' (line 55)
...
[13040, 17568) 'eigensolver' (line 142)
[17824, 17840) 'ref.tmp518' (line 143)
[17856, 17872) 'ref.tmp523' (line 144)
[17888, 19488) 'ref.tmp524' (line 144) <== Memory access at offset 17984 is inside this variable
[19616, 19640) 'ref.tmp532' (line 169)
...
The crash report says that we're accessing a temporary object from
line 144 when we shouldn't be. Line 144 looks like this:
https://github.com/opencv/opencv/blob/4.6.0/modules/calib3d/src/usac/essential_solver.cpp#L144
const auto * const eig_vecs_ = (double *) eigensolver.eigenvectors().real().data();
We are using version 4.6.0 for this, but the problem is present on the
4.x branch.
Note that I am dropping the .real() call here. I think that is safe because
of the code further down (line 277 in the most recent version):
const int eig_i = 20 * i + 12; // eigen stores imaginary values too
The code appears to expect to have to skip doubles for the imaginary parts
of the complex numbers.
Admittedly, I couldn't find a test case that exercised this code path to
validate correctness.
Fix crash in ap3p #23607
### Pull Request Readiness Checklist
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Patch to opencv_extra has the same branch name.
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G-API: Introduce a Queue Source #24178
- Added a new IStreamSource class: in fact, a wrapper over a concurrent queue;
- Added minimal example on how it can be used;
- Extended IStreamSource with optional "halt" interface to break the blocking calls in the emitter threads when required to stop.
- Introduced a QueueInput class which allows to pass the whole graph's input vector at once. In fact it is a thin wrapper atop of individual Queue Sources.
There is a hidden trap found with our type system as described in https://github.com/orgs/g-api-org/discussions/2
While it works even in this form, it should be addressed somewhere in the 5.0 timeframe.
### Pull Request Readiness Checklist
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* add broadcast_to with tests
* change name
* fix test
* fix implicit type conversion
* replace type of shape with InputArray
* add perf test
* add perf tests which takes care of axis
* v2 from ficus expand
* rename to broadcast
* use randu in place of declare
* doc improvement; smaller scale in perf
* capture get_index by reference
If building with -mcpu=native or any other setting which implies the current
CPU has FP16 but with intrinsics disabled, we mistakenly try to use it even
though convolution.hpp conditionally defines it correctly based on whether
we should *use it*. convolution.cpp on the other hand was mismatched and
trying to use it if the CPU supported it, even if not enabled in the build
system.
Make the guards match.
Bug: https://bugs.gentoo.org/913031
Signed-off-by: Sam James <sam@gentoo.org>
Skip test on SkipTestException at fixture's constructor
* Skip test on SkipTestException at fixture's constructor
* Add warning supression
* Skip Python tests if no test file found
* Skip instances of test fixture with exception at SetUpTestCase
* Skip test with exception at SetUp method
* Try remove warning disable
* Add CV_NORETURN
* Remove FAIL assertion
* Use findDataFile to throw Skip exception
* Throw exception conditionally
* core:add OPENCV_IPP_MEAN/MINMAX/SUM option to enable IPP optimizations
* fix: to use guard HAVE_IPP and ocv_append_source_file_compile_definitions() macro.
* support OPENCV_IPP_ENABLE_ALL
* add document for OPENCV_IPP_ENABLE_ALL
* fix OPENCV_IPP_ENABLE_ALL comment
Fixed an off-by-1 buffer resize, the space for the null termination was forgotten.
Prefer snprintf, which can never overflow (if given the right size).
In one case I cheated and used strcpy, because I cannot figure out the buffer size at that point in the code.
OCL_FP16 MatMul with large batch
* Workaround FP16 MatMul with large batch
* Fix OCL reinitialization
* Higher thresholds for INT8 quantization
* Try fix gemm_buffer_NT for half (columns)
* Fix GEMM by rows
* Add batch dimension to InnerProduct layer test
* Fix Test_ONNX_conformance.Layer_Test/test_basic_conv_with_padding
* Batch 16
* Replace all vload4
* Version suffix for MobileNetSSD_deploy Caffe model
Rewrite Universal Intrinsic code by using new API: Core module. #23980
The goal of this PR is to match and modify all SIMD code blocks guarded by `CV_SIMD` macro in the `opencv/modules/core` folder and rewrite them by using the new Universal Intrinsic API.
The patch is almost auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter), related PR #23885.
Most of the files have been rewritten, but I marked this PR as draft because, the `CV_SIMD` macro also exists in the following files, and the reasons why they are not rewrited are:
1. ~~code design for fixed-size SIMD (v_int16x8, v_float32x4, etc.), need to manually rewrite.~~ Rewrited
- ./modules/core/src/stat.simd.hpp
- ./modules/core/src/matrix_transform.cpp
- ./modules/core/src/matmul.simd.hpp
2. Vector types are wrapped in other class/struct, that are not supported by the compiler in variable-length backends. Can not be rewrited directly.
- ./modules/core/src/mathfuncs_core.simd.hpp
```cpp
struct v_atan_f32
{
explicit v_atan_f32(const float& scale)
{
...
}
v_float32 compute(const v_float32& y, const v_float32& x)
{
...
}
...
v_float32 val90; // sizeless type can not used in a class
v_float32 val180;
v_float32 val360;
v_float32 s;
};
```
3. The API interface does not support/does not match
- ./modules/core/src/norm.cpp
Use `v_popcount`, ~~waiting for #23966~~ Fixed
- ./modules/core/src/has_non_zero.simd.hpp
Use illegal Universal Intrinsic API: For float type, there is no logical operation `|`. Further discussion needed
```cpp
/** @brief Bitwise OR
Only for integer types. */
template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> operator|(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n>& operator|=(v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
```
```cpp
#if CV_SIMD
typedef v_float32 v_type;
const v_type v_zero = vx_setzero_f32();
constexpr const int unrollCount = 8;
int step = v_type::nlanes * unrollCount;
int len0 = len & -step;
const float* srcSimdEnd = src+len0;
int countSIMD = static_cast<int>((srcSimdEnd-src)/step);
while(!res && countSIMD--)
{
v_type v0 = vx_load(src);
src += v_type::nlanes;
v_type v1 = vx_load(src);
src += v_type::nlanes;
....
src += v_type::nlanes;
v0 |= v1; //Illegal ?
....
//res = v_check_any(((v0 | v4) != v_zero));//beware : (NaN != 0) returns "false" since != is mapped to _CMP_NEQ_OQ and not _CMP_NEQ_UQ
res = !v_check_all(((v0 | v4) == v_zero));
}
v_cleanup();
#endif
```
### Pull Request Readiness Checklist
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- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
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Fix python sample code (tst_scene_render) #24116
Fix bug of python sample code (samples/python/tst_scene_render.py) when backGr or fgr is None (#24114)
1) pass shape tuple to np.zeros arguments instead of integers
2) change np.int to int
### Pull Request Readiness Checklist
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- [o] The PR is proposed to the proper branch
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- [o] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
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dnn: cleanup of tengine backend #24122🚀 Cleanup for OpenCV 5.0. Tengine backend is added for convolution layer speedup on ARM CPUs, but it is not maintained and the convolution layer on our default backend has reached similar performance to that of Tengine.
Tengine backend related PRs:
- https://github.com/opencv/opencv/pull/16724
- https://github.com/opencv/opencv/pull/18323
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Invalid memory access fix for ONNX split layer parser #24076#24101
### Pull Request Readiness Checklist
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TFLite models on different backends (tests and improvements) #24039
### Pull Request Readiness Checklist
* MaxUnpooling with OpenVINO
* Fully connected with transposed inputs/weights with OpenVINO
* Enable backends tests for TFLite (related to https://github.com/opencv/opencv/issues/23992#issuecomment-1640691722)
* Increase existing tests thresholds
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Resolve uncovered CUDA dnn layer #24080
### Pull Request Readiness Checklist
* Gelu activation layer on CUDA
* Try to relax GEMM from ONNX
resolves https://github.com/opencv/opencv/issues/24064
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Remove legacy nGraph logic #24072
### Pull Request Readiness Checklist
TODO:
- [x] Test with OpenVINO 2021.4 (tested locally)
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DetectionOutput layer on OpenVINO without limitations #24069
### Pull Request Readiness Checklist
required for https://github.com/opencv/opencv/pull/23987
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G-API: Support CUDA & TensoRT Execution Providers for ONNXRT Backend #24059
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PReLU with element-wise scales #24056
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/24051
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Update opencv dnn to support cann version >=6.3 #23936
1.modify the search path of "libopsproto.so" in OpenCVFindCANN.cmake
2.add the search path of "libgraph_base.so" in OpenCVFindCANN.cmake
3.automatic check Ascend socVersion,and test on Ascend310/Ascend310B/Ascend910B well
Python typing refinement for dnn_registerLayer/dnn_unregisterLayer functions #24066
This patch introduces typings generation for `dnn_registerLayer`/`dnn_unregisterLayer` manually defined in [`cv2/modules/dnn/misc/python/pyopencv_dnn.hpp`](https://github.com/opencv/opencv/blob/4.x/modules/dnn/misc/python/pyopencv_dnn.hpp)
Updates:
- Add `LayerProtocol` to `cv2/dnn/__init__.pyi`:
```python
class LayerProtocol(Protocol):
def __init__(
self, params: dict[str, DictValue],
blobs: typing.Sequence[cv2.typing.MatLike]
) -> None: ...
def getMemoryShapes(
self, inputs: typing.Sequence[typing.Sequence[int]]
) -> typing.Sequence[typing.Sequence[int]]: ...
def forward(
self, inputs: typing.Sequence[cv2.typing.MatLike]
) -> typing.Sequence[cv2.typing.MatLike]: ...
```
- Add `dnn_registerLayer` function to `cv2/__init__.pyi`:
```python
def dnn_registerLayer(layerTypeName: str,
layerClass: typing.Type[LayerProtocol]) -> None: ...
```
- Add `dnn_unregisterLayer` function to `cv2/__init__.pyi`:
```python
def dnn_unregisterLayer(layerTypeName: str) -> None: ...
```
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Fix harmless ASAN error. #24042
For an empty radius, &v[0] would be accessed (though the called functions would not use it due to v.size() being 0). Also add checks for emptyness and fix the first element checks, in case we get INT_MAX to compare to.
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G-API: Support DirectML Execution Provider for ONNXRT Backend #24045
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feat: add cuda_Stream and cuda_GpuMat to simple types mapping #24029
This patch fixes usage of `cuda::Stream` in function arguments.
Affected modules: `cudacodec`:
[`using namespace cuda`](https://github.com/opencv/opencv_contrib/blob/9dfe233020f669f17021dfc456fe77531e776b74/modules/cudacodec/include/opencv2/cudacodec.hpp#L62) in public `cudacodec.hpp` header can be removed after merge of the patch.
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Fix FLANN python bindings #24028
As a side-effect this patch improves reporting errors by FLANN `get_param`.
resolves#21642
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G-API: Support OpenVINO Execution Provider for ONNXRT Backend #24024
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[TFLite] Pack layer and other fixes for SSD from Keras #24004
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23992
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1076
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Details here: https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=58006
runtime error: call to function (unknown) through pointer to incorrect function type 'void (*)(const unsigned char **, const int *, unsigned char **, const int *, int, int)'
Python typing magic constants #24023
This patch adds typing stubs generation for `__all__` and `__version__` constants.
Introduced `__all__` is intentionally empty for all generated modules stubs.
Type hints won't work for star imports
resolves#23950
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Fix python typing stubs generation for CUDA modules #24022resolves#23946resolves#23945resolvesopencv/opencv-python#871
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C++20 made it invalid to use simple-template-ids for constructors and destructors: https://eel.is/c++draft/diff.cpp17.class#2
GCC 11 and later throw an error on this, with the unhelpful message `expected unqualified-id before ')' token`. This PR fixes the problem.
DNN: optimize the speed of general Depth-wise #23952
Try to solve the issue: https://github.com/opencv/opencv/issues/23941
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Add V4L2_PIX_FMT_Y16_BE pixel format #18498
Address #18495
relates to #23944
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- [ ] Test using Melexis MLX90640
Fix imgwarp at borders when transparent. #23922
I believe this is a proper fix to #23562
The PR #23754 overwrites data while that should not be the case with transparent data. The original test is failing because points at the border do not get computed because they do not have 4 neighbors to be computed. Still ,we can approximate their computation with whatever neighbors that are available.
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Fix checkSignature not thread safe for AVIF. #23943
A common decoder cannot be shared with checkSignature which is used like a static function (on a static ist of decoders).
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Adds missing typing stubs:
- Matrix depths: `CV_8U`, `CV_8S` and etc.
- Matrix type constants: `CV_8UC1`, `CV_32FC3` and etc.
- Matrix type factory functions: `CV_*(channels) -> int` and `CV_MAKETYPE`
Fixing typos in usac #23900
Just read and correct some typos in `usac`
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G-API: Fix async inference for OpenVINO backend #23884
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- Fixed width and height swap in board size
- Fixed defaults in command line hint
- Fixed board visualization for Charuco case
- Used matchImagePoints method to handle partially detected Charuco boards
dnn: disable warning when loading a fp16 model #23853
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Add charuco board check #23647
Added charuco board checking to avoid detection of incorrect board.
Fixes#23517
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Fix detect diamonds api #23848
`detectDiamonds` cannot be called from python, reproducer:
```
import numpy as np
import cv2 as cv
detector = cv.aruco.CharucoDetector(
cv.aruco.CharucoBoard(
(3, 3), 200.0, 100.0,
cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_250)
)
)
image = np.zeros((640, 480, 1), dtype=np.uint8)
res = detector.detectDiamonds(image)
print(res)
```
The error in `detectDiamonds` API fixed by replacing `InputOutputArrayOfArrays markerIds` with `InputOutputArray markerIds`.
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Python binding for RotatedRect #23702
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related: https://github.com/opencv/opencv/issues/23546#issuecomment-1562894602
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G-API: Fix incorrect OpaqueKind for Kernel outputs #23843
### Pull Request Readiness Checklist
#### Overview
The PR is going to fix several problems:
1. Major: `GKernel` doesn't hold `kind` for its outputs. Since `GModelBuilder` traverse graph from outputs to inputs once it reaches any output of the operation it will use its `kind` to create `Data` meta for all operation outputs. Since it essential for `python` to know `GTypeInfo` (which is `shape` and `kind`) it will be confused.
Consider this operation:
```
@cv.gapi.op('custom.square_mean', in_types=[cv.GArray.Int], out_types=[cv.GOpaque.Float, cv.GArray.Int])
class GSquareMean:
@staticmethod
def outMeta(desc):
return cv.empty_gopaque_desc(), cv.empty_array_desc()
```
Even though `GOpaque` is `Float`, corresponding metadata might have `Int` kind because it might be taken from `cv.GArray.Int`
so it will be a problem if one of the outputs of these operation is graph output because python will cast it to the wrong type based on `Data` meta.
2. Minor: Some of the OpenVINO `IR`'s doesn't any layout information for input. It's usually true only for `IRv10` but since `OpenVINO 2.0` need this information to correctly configure resize we need to put default layout if there no such assigned in `ov::Model`.
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Fix broken links and outdated information for documentation of Orbbec camera #23829
Resolves the documentation issue from https://github.com/opencv/opencv/issues/23579.
Orbbec is moving to support UVC directly so they do not provide the old `install.sh` for OpenNI SDK >= 2.3.0.86. Also in their new release of OpenNI SDK, paths of include headers and libraries are changed. Changing our cmake script for this change does not make sense since we cannot make this kind of change everytime they update. So just added a subsection providing `install.sh` for users as a workaround on our side.
@Lecrapouille You may also take a look at this pull request.
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G-API: Implement InferROI, InferList, InferList2 for OpenVINO backend #23799
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G-API: Align IE Backend with the latest OpenVINO version #23796
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Fix distransform to work with large images #22798
This attempts to fix the following bug which was caused by storing squares of large integers into 32-bit floating point variables:
https://github.com/opencv/opencv/issues/22732
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Export enums ALL_CAPS version to typing stub files #23816
- Export ALL_CAPS versions alongside from normal names for enum constants, since both versions are available in runtime
- Change enum names entries comments to documentary strings
Before patch
```python
RMat_Access_R: int
RMat_Access_W: int
RMat_Access = int # One of [R, W]
```
After patch
```python
RMat_Access_R: int
RMAT_ACCESS_R: int
RMat_Access_W: int
RMAT_ACCESS_W: int
RMat_Access = int
"""One of [RMat_Access_R, RMAT_ACCESS_R, RMat_Access_W, RMAT_ACCESS_W]"""
```
Resolves: #23776
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Build Java without ANT #23724
### Pull Request Readiness Checklist
Enables a path of building Java bindings without ANT
* Able to build OpenCV JAR and Docs without ANT
```
-- Java:
-- ant: NO
-- JNI: /usr/lib/jvm/default-java/include /usr/lib/jvm/default-java/include/linux /usr/lib/jvm/default-java/include
-- Java wrappers: YES
-- Java tests: NO
```
* Possible to build OpenCV JAR without ANT but tests still require ANT
**Merge with**: https://github.com/opencv/opencv_contrib/pull/3502
Notes:
- Use `OPENCV_JAVA_IGNORE_ANT=1` to force "Java" flow for building Java bindings
- Java tests still require Apache ANT
- JAR doesn't include `.java` source code files.
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Keep inliers for linear remap with BORDER_TRANSPARENT #23754
Address https://github.com/opencv/opencv/issues/23562
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23562
I do think that this is a bug because with `INTER_CUBIC + BORDER_TRANSPARENT` the last column and row are preserved. So same should be done for `INTER_LINEAR`
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Update USAC #23078
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added Aruco MIP dictionaries #23785
added Aruco MIP dictionaries: DICT_ARUCO_MIP_16h3, DICT_ARUCO_MIP_25h7, DICT_ARUCO_MIP_36h12 from [Aruco.js](https://github.com/damianofalcioni/js-aruco2), converted in opencv format using https://github.com/damianofalcioni/js-aruco2/blob/master/src/dictionaries/utils/dic2opencv.js
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G-API: Expose explicit preprocessing for IE Backend #23786
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G-API: Refine Semantic Segmentation Demo #23766
### Overview
* Supported demo working with camera id (e.g `--input=0`)
* Supported 3d output segmentation models (e.g `deeplabv3`)
* Supported `desync` execution
* Supported higher camera resolution
* Changed the color map to pascal voc (https://cloud.githubusercontent.com/assets/4503207/17803328/1006ca80-65f6-11e6-9ff6-36b7ef5b9ac6.png)
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Although acceptible to Intel CPUs, it's still undefined behaviour according to the C++ standard.
It can be replaced with memcpy, which makes the code simpler, and it generates the same assembly code with gcc and clang with -O2 (verified with godbolt).
Also expanded the test to include other little endian CPUs by testing for __LITTLE_ENDIAN__.
Add AVIF support through libavif. #23596
This is to fix https://github.com/opencv/opencv/issues/19271
Extra: https://github.com/opencv/opencv_extra/pull/1069
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DNN: fix bug for X86 Winograd #23763
Address https://github.com/opencv/opencv/issues/23760
The patch aims to add a runtime check for X86 platform without AVX(2).
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Assertion Fix in Split Layer #23746
### Pull Request Readiness Checklist
This PR fixes issue mentioned in [#23663](https://github.com/opencv/opencv/issues/23663)
Merge with https://github.com/opencv/opencv_extra/pull/1067
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imgproc: add contour values check to IntelligentScissorsMB tests
Preparation for the #21959 changes as per @asmorkalov's https://github.com/opencv/opencv/pull/21959#issuecomment-1560511500 suggestion.
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[G-API] Implement OpenVINO 2.0 backend #23595
### Pull Request Readiness Checklist
Implemented basic functionality for `OpenVINO` 2.0 G-API backend.
#### Overview
- [x] Implement `Infer` kernel with some of essential configurable parameters + IR/Blob models format support.
- [ ] Implement the rest of kernels: `InferList`, `InferROI`, `Infer2` + other configurable params (e.g reshape)
- [x] Asyncrhonous execution support
- [ ] Remote context support
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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GAPI Fluid SIMD:Add support of new several types for the Merge3
- Support of the new several types was added.
- Fixes for the Split/Merge and ConvertTo issues.
G-API: Integration branch for ONNX & Python-related changes #23597
# Changes overview
## 1. Expose ONNX backend's Normalization and Mean-value parameters in Python
* Since Python G-API bindings rely on `Generic` infer to express Inference, the `Generic` specialization of `onnx::Params` was extended with new methods to control normalization (`/255`) and mean-value; these methods were exposed in the Python bindings
* Found some questionable parts in the existing API which I'd like to review/discuss (see comments)
UPD:
1. Thanks to @TolyaTalamanov normalization inconsistencies have been identified with `squeezenet1.0-9` ONNX model itself; tests using these model were updated to DISABLE normalization and NOT using mean/value.
2. Questionable parts were removed and tests still pass.
### Details (taken from @TolyaTalamanov's comment):
`squeezenet1.0.*onnx` - doesn't require scaling to [0,1] and mean/std because the weights of the first convolution already scaled. ONNX documentation is broken. So the correct approach to use this models is:
1. ONNX: apply preprocessing from the documentation: https://github.com/onnx/models/blob/main/vision/classification/imagenet_preprocess.py#L8-L44 but without normalization step:
```
# DON'T DO IT:
# mean_vec = np.array([0.485, 0.456, 0.406])
# stddev_vec = np.array([0.229, 0.224, 0.225])
# norm_img_data = np.zeros(img_data.shape).astype('float32')
# for i in range(img_data.shape[0]):
# norm_img_data[i,:,:] = (img_data[i,:,:]/255 - mean_vec[i]) / stddev_vec[i]
# # add batch channel
# norm_img_data = norm_img_data.reshape(1, 3, 224, 224).astype('float32')
# return norm_img_data
# INSTEAD
return img_data.reshape(1, 3, 224, 224)
```
2. G-API: Convert image from BGR to RGB and then pass to `apply` as-is with configuring parameters:
```
net = cv.gapi.onnx.params('squeezenet', model_filename)
net.cfgNormalize('data_0', False)
```
**Note**: Results might be difference because `G-API` doesn't apply central crop but just do resize to model resolution.
---
`squeezenet1.1.*onnx` - requires scaling to [0,1] and mean/std - onnx documentation is correct.
1. ONNX: apply preprocessing from the documentation: https://github.com/onnx/models/blob/main/vision/classification/imagenet_preprocess.py#L8-L44
2. G-API: Convert image from BGR to RGB and then pass to `apply` as-is with configuring parameters:
```
net = cv.gapi.onnx.params('squeezenet', model_filename)
net.cfgNormalize('data_0', True) // default
net.cfgMeanStd('data_0', [0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
```
**Note**: Results might be difference because `G-API` doesn't apply central crop but just do resize to model resolution.
## 2. Expose Fluid & kernel package-related functionality in Python
* `cv::gapi::combine()`
* `cv::GKernelPackage::size()` (mainly for testing purposes)
* `cv::gapi::imgproc::fluid::kernels()`
Added a test for the above.
## 3. Fixed issues with Python stateful kernel handling
Fixed error message when `outMeta()` of custom python operation fails.
## 4. Fixed various issues in Python tests
1. `test_gapi_streaming.py` - fixed behavior of Desync test to avoid sporadic issues
2. `test_gapi_infer_onnx.py` - fixed model lookup (it was still using the ONNX Zoo layout but was NOT using the proper env var we use to point to one).
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better accuracy for _rotatedRectangleIntersection() (proposal for #23546) #23690
_rotatedRectangleIntersection() can be (statically) customized to use double instead of float for better accuracy
this is a proposal for experimentation around #23546
for better accuracy, _rotatedRectangleIntersection() could use double. It will still return cv::Point2f list for backward compatibility, but the inner computations are controlled by a typedef
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imgproc: add basic IntelligentScissorsMB performance test #23698
Adding basic performance test that can be used before and after the #21959 changes etc. as per @asmorkalov's https://github.com/opencv/opencv/pull/21959#issuecomment-1565240926 comment.
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Pointer arithmetic overflow is always undefined, whether signed or unsigned.
It warned here:
`Addition of unsigned offset to 0x00017fd31b97 overflowed to 0x00017fd30c97`
Convert the offset to a signed number, so that we can offset either forward or backwards.
In my own use of OpenCV at least, this is the only case of pointer arithmetic overflow.
Import and export np.float16 in Python #23691
### Pull Request Readiness Checklist
* Also, fixes `cv::norm` with `NORM_INF` and `CV_16F`
resolves https://github.com/opencv/opencv/issues/23687
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Python typing stub generation #20370
Add stub generation to `gen2.py`, addressing #14590.
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Android: don't require deprecated tools #21736
Checking for these deprecated is no longer necessary, and infact broken on fresh Android SDK installs. Remove the check.
resolves#21735
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Python bindings for CV_8UC(n) and other types macros #23679
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resolves https://github.com/opencv/opencv/issues/23628#issuecomment-1562468327
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Support ONNX operator QLinearSoftmax in dnn #23655
Resolves https://github.com/opencv/opencv/issues/23636.
Merge with https://github.com/opencv/opencv_extra/pull/1064.
This PR maps the QLinearSoftmax (from com.microsoft domain) to SoftmaxInt8 in dnn along with some speed optimization.
Todo:
- [x] support QLinearSoftmax with opset = 13
- [x] add model and test data for QLinearSoftmax with opset = 13
- [x] ensure all models have dims >= 3.
- [x] add the script to generate model and test data
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CV_MAKETYPE Python binding #23674
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/23628
```python
import cv2 as cv
t = cv.CV_MAKETYPE(cv.CV_32F, 4)
```
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Fix truncated sentenced in boxPoints documentation #22975#23662Resolves#22975
Completed the sentence as per the suggestion given in the issue #22975
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fix: traincascade, use C++ persistence API #23594
This pull allows to compile traincascade application with OpenCV 4.6. Changes uses new persistence C++ API in place of legacy one.
QRCodeDetector: don't floodFill with outside-of-image seedPoint #23612Fixes#21532.
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/build/build_cuda/3p/opencv/linux-x64/ubuntu22.04/Debug/modules/dnn/src/layers/cpu_kernels/convolution.cpp: In function 'void cv::dnn::packData8(char*&, float*&, int&, int&, int&, const int*, int, int, int)':
/build/build_cuda/3p/opencv/linux-x64/ubuntu22.04/Debug/modules/dnn/src/layers/cpu_kernels/convolution.cpp:448:43: error: 'CONV_NR' was not declared in this scope; did you mean 'CONV_3D'?
448 | vx_store(inpbufC_FP32 + k*CONV_NR, vx_load(inptrInC + k1));
| ^~~~~~~
| CONV_3D
add ChArUco board pattern into calib3d/camera_calibration #23575
Added opportunity to calibrate camera using ChArUco board pattern in /samples/cpp/tutorial_code/calib3d/camera_calibration/caera_calibration.cpp
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Fix even input dimensions for INTER_NEAREST_EXACT #23634
### Pull Request Readiness Checklist
resolves https://github.com/opencv/opencv/issues/22204
related: https://github.com/opencv/opencv/issues/9096#issuecomment-1551306017
/cc @Yosshi999
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Added charuco board generation to gen_pattern.py #23363
added charuco board generation in gen_pattern.py
moved aruco_dict_utils.cpp to samples from opencv_contrib (https://github.com/opencv/opencv_contrib/pull/3464)
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LSTM ONNX Layout Attribute Support #23614
### Explanation
This PR contains necessary changes to support `layout` attribute. This attributes is present in [ONNX](https://github.com/onnx/onnx/blob/main/docs/Operators.md#lstm) and [Torch](https://pytorch.org/docs/stable/generated/torch.nn.LSTM.html#lstm) (in touch it is name as `batch_first=True`) libraries. When `layout = 1` input to LSTM layer is expected to have batch dimension first -> `[batch_size, sequence_length, features]` vs `layout = 0` - default `[sequence_length, batch_size, features]`
### Test Data
Test data and data generator for PR located here [#1063](https://github.com/opencv/opencv_extra/pull/1063)
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Added charuco pattern into calibrate.py #23587
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videoio/FFmpeg: increased packet read attempt limit, allow configuring it
resolves#9455
related #3225
* Use different counters for wrong packets recieved by demuxer and errors from decoder
* Allow modifying these counters via environment variables `OPENCV_FFMPEG_READ_ATTEMPTS`/`OPENCV_FFMPEG_DECODE_ATTEMPTS`
* Added logging when reading breaks at one of error limits
Notes:
* I've been able to reproduce original issue with a video file with 14 total streams (video + audio + subtitles), at some point in the video only packets from the last stream are being sent by the demuxer, thus exceeding our limit. For my specific video total number of packets from wrong stream was about 2700. I've chosen 4096 as default value.
* Default limit of decoding attempts is quite low, because I'm not sure in which cases it can be exceeded (network stream?). I tried to read 8k video from the disk, but it did not cause break at decode point.
Build DNN without Protobuf
DNN module can be built without Protobuf for Darknet, TFLite, OpenVINO, Torch (not PyTorch) models.
```
cmake \
-DCMAKE_BUILD_TYPE=Release \
-DBUILD_LIST=dnn \
-DWITH_PROTOBUF=OFF \
-DWITH_OPENCL=OFF
7.1M lib/libopencv_dnn.so.4.7.0
```
```
cmake \
-DCMAKE_BUILD_TYPE=Release \
-DBUILD_LIST=dnn \
-DWITH_OPENCL=OFF
3.9M lib/libopencv_dnn.so.4.7.0
```
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Improve document of cv::RotatedRect for #23335#23342fix#23335
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don't ignore documentation for cv::format in doxygen #23555
Issue https://github.com/opencv/opencv/issues/23553
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AGP 8.0 build.gradle namespace and aidl buildFeature requirement added #23447
Hello,
Android Gradle Plugin version 8.0 is asking for namespace. This is become mandatory and after I update my AGP to 8.0, I got this error
```
Namespace not specified. Please specify a namespace in the module's build.gradle file like so:
android {
namespace 'com.example.namespace'
}
If the package attribute is specified in the source AndroidManifest.xml, it can be migrated automatically to the namespace value in the build.gradle file using the AGP Upgrade Assistant; please refer to https://developer.android.com/studio/build/agp-upgrade-assistant for more information.
```
This change fix this future releases. However I am not sure how opencv wants to user namespace I used "org.opencv" if there is a different namespace please let me know so I can changed that too. Also should I add namepsace into "opencv/modules/java/android_sdk/android_gradle_lib/build.gradle" here ?
### Sources
Android developer link: https://developer.android.com/studio/preview/features#namespace-dsl
Issue Tracker Google: https://issuetracker.google.com/issues/191813691?pli=1#comment19
### Pull Request Readiness Checklist
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Fixed a typo in `documentation.yml` and `feature_request.yml` #23538
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Add charuco pattern into calibration.cpp #23486
Added charuco pattern into calibration.cpp. Added charuco pattern with predefined aruco dictionary and with dictionary from file.
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Import and inference INT8 quantized TFLite model #23409
### Pull Request Readiness Checklist
* Support quantized TFLite models
* Enable fused activations (FP32, INT8)
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1048

on the image, green boxes are from TFLite and red boxes from OpenCV
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Fix ONNX parser for single-layer LSTM hidden and cell states #23475
### Fix ONNX parser for single-layer LSTM hidden and cell states
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This PR addresses #21118 [issue](https://github.com/opencv/opencv/issues/21118). The problem is that the ONNX parser is unable to read the hidden state and cell state for single-layer LSTMs. This PR fixes the issue by updating the parser to correctly read hidden and cell states.
Add python sample of how to use Orbbec camera. #23531
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DNN: Add New API blobFromImageParam #22750
The purpose of this PR:
1. Add new API `blobFromImageParam` to extend `blobFromImage` API. It can support the different data layout (NCHW or NHWC), and letter_box.
2. ~~`blobFromImage` can output `CV_16F`~~
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dnn: Support more operators in CANN backend #23401
This PR adds the support of following layers:
- [x] Sub
- [x] PRelu
- [x] DeConv
- [x] Also warn users if backend is switched back to default if some of the layers are not supported.
- [ ] [Dropped] LSTM: some hacks (adding layers) were introduced which makes it even harder to build the graph for CANN backend.
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Added LSTM and GRU tests for various batch and input length sizes #23501
Added tests with various sequence length and batch sizes
Test data: https://github.com/opencv/opencv_extra/pull/1057
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* Replaced most remaining sprintf with snprintf
* Deprecated encodeFormat and introduced new method that takes the buffer length
* Also increased buffer size at call sites to be a little bigger, in case int is 64 bit
Added explicit cast to unsigned before doing the left shift.
This was caught by UBSan which reported things like:
drawing.cpp:361:22: runtime error: left shift of negative value -26214
drawing.cpp:383:22: runtime error: left shift of negative value -78642
Fix python bindings for setCharucoParameters #23436
setCharucoParameters fails in python
Fixes: https://github.com/opencv/opencv/issues/23440
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Add scrollWheel to Cocoa #23394
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Add notes for the output format of FaceDetectorYN.detect()
Resolves https://github.com/opencv/opencv/pull/23020#issuecomment-1499010015
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imgcodecs: tiff: Support to encode for CV_32S with compression params
Fix https://github.com/opencv/opencv/issues/23416
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Fix identifying initializers in ONNX graph simplification #23296
Fixes https://github.com/opencv/opencv/issues/23295
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**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1050
For 32 bits per pixel with 3 or 4 channel destination images, apply scale factor and mask to parse BMP files correctly
closes#23445
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Fix image loading in tutorials code #23442
Fixes https://github.com/opencv/opencv/issues/23378
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This makes LineSegmentDetector deterministic by using stable_sort for ordering points by norm. Without this change the region growing in LSD is non-determinstic and thus the returned lines are changing between invocations.
This is a replacement for https://github.com/opencv/opencv/pull/23370
Propagate inputs info for ONNX and TFLite models
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Needed for generic applications such as benchmarking pipelines. So OpenCV can tell about the default input shapes specified in the models.
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Support VideoCapture CAP_PROP_AUTO_WB and CV_CAP_PROP_WHITE_BALANCE_BLUE_U for DShow
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https://github.com/opencv/opencv/issues/19621https://github.com/opencv/opencv/issues/21408
### Before apply this pull request console output.
before AWB setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1
after AWB disable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1
after AWB enable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1
after Manual WB(and Disable AWB) setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1
### After apply this pull request console output.
before AWB setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: 0
after AWB disable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 4000
CAP_PROP_AUTO_WB: 0
after AWB enable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 4000
CAP_PROP_AUTO_WB: 1
after Manual WB(and Disable AWB) setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: 0
### Test Code
[OpenCvVideoCapTest.zip](https://github.com/opencv/opencv/files/10825399/OpenCvVideoCapTest.zip)
Added argument to print notice in `roiSelector.cpp`
Related Issue : https://github.com/opencv/opencv/issues/23175
I've added a printNotice argument to `selectROI` (and it's overload) and `selectROIs` functions.
I've also updated the function declarations in `highgui.hpp`.
Tested by building locally.
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Patch to opencv_extra has the same branch name.
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Fixed potential memory leak in flann
Issue #22426
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4 failed tests in open_test_dnn listed below:
* Test_Caffe_layers.Conv_Elu/0, where GetParam() = OCV/CPU
* Test_ONNX_layers.ConvResizePool1d/0, where GetParam() = OCV/CPU
* Test_TensorFlow_layers.tf_reshape_nhwc/0, where GetParam() = OCV/CPU
* Test_Torch_layers.net_inception_block/0, where GetParam() = OCV/CPU
In winofunc_AtXA_8x8_f32 and winofunc_BtXB_8x8_f32
implementation, incorrect input parameters cause tests failure.
Add four new different variables for the last four input parameters of
v_transpose4x4 to fix bugs, and update related comments.
Signed-off-by: tingbo.liao <tingbo.liao@starfivetech.com>
Related issue: https://github.com/opencv/opencv_zoo/issues/136
Features added:
- Support operators with multiple output: ONNX Split.
- Support Slice without steps.
Bugs fixed:
- Wrong settings in ClipByValue (Relu6).
- Wrong calculation of pads in convolution layer (It is wrong generally but only fixed specifically for CANN for now).
### Pull Request Readiness Checklist
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Fixed strict type in slerp and spline; Fixed nlerp usage condition
Fixes#23293
The PR is fixing the issue described in [Issue #23293 ](https://github.com/opencv/opencv/issues/23293)
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Resolves https://github.com/opencv/opencv/issues/23304
Fixes the incorrect pixel grid
Switches type to double to avoid precision loss as all callers use doubles
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In case of huge (and probably invalid) input, make sure we do not
rely only on the while loops for truncation.
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Make the GTK+3 API the default one by wrapping the missing GTK+2 functions in defines
Make sure to always guard with GTK_VERSION2 or GTK_VERSION3 to allow future addition
of Gtk4
* different interpolation by double image
* fixing scaling mapping
* fixing a test
* added an option to enable previous interpolation
* added doxygen entries for the new parameter
* ASSERT_TRUE -> ASSERT_EQ
* changed log message when using old upscale mode
Fix misaligned-pointer-use in intrin_sse.hpp
* Fix misaligned-pointer-use in intrin_sse.hpp
* Use _mm_loadu_si32() instead of memcpy()
* Use CV_DECL_ALIGNED instead of _mm_loadu_si32()
Fix rect_nfa (lsd)
* Fix missing log_gamma in nfa()
Comparing the nfa function with the function in the binomial_nfa repository (https://github.com/rafael-grompone-von-gioi/binomial_nfa/blob/main/C99/log_binomial_nfa.c#L152), the first log_gamma call is missing.
* Fix rect_nfa pixel index
* Replace std::rotate
* Rename tmp to v_tmp
* Replace auto and std::min_element
* Change slope equality check to int
* Fix left limit check
dnn: add layer normalization for vision transformers
* add layer norm onnx parser, impl and tests
* add onnx graph simplifier for layer norm expanded
* handle the case when constants are of type Initializer
* add test case for layer norm expanded with initializers
* use CV_Assert & CV_CheckType in place of CV_Assert_N; use forward_fallback for OCL_FP16
* use const ref / ref in parameters of invoker::run; extract inner const if from nested loop; use size_t in place of ull
* template hasBias
* remove trailing whitespace
* use pointer parameter with null check; move normSize division & mean_square division outside of loop; use std::max to ensure positive value before std::sqrt
* refactor implementation, optimize parallel_for
* disable layer norm expanded
* remove the removal of layer norm optional outputs
Omit the first check of the double-checked locking pattern in
recordException() in parallel.cpp when CV_THREAD_SANITIZER is defined.
This should only slow recordException() down when the thread sanitizer
is used, and avoids the TSAN data race warning.
Adding HEVC/H265 FourCC support to MSMF video writer
* Adding HEVC/H265 fourcc to MSMF video writer
Adding HEVC/H265 fourcc to MSMF video writer. I have verified it with my own video input stream, and it works well on my workstation.
* Update video io testing
* Adding macro fence to get rid of compiler error
H265/HEVC encoder is only available in Windows or later. https://learn.microsoft.com/en-us/windows/win32/medfound/h-265---hevc-video-encoder
* Update test_video_io.cpp
Backport of #22992 to 3.4
### Pull Request Readiness Checklist
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Patch to opencv_extra has the same branch name.
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Add `estimateSE2(...)`, `estimateSE3(...)`, `estimateSIM2(...)`, `estimateSIM3(...)` for estimating an geometric transformation with rotation and translation (with scaling for SIM) using USAC: as alternative for `estimateAffinePartial2D` and `estimateAffine3D`.
Modified test module.
Remove unused variables.
Remove initializer of unused variable.
Add interfaces to accept UsacParams() and corresponding test codes.
Revise test code.
PartialNd removed
Umeyama rewritten for code quality & speed
comments & minors
rise number of points
fix, and +30% faster!
only one number should be that big
remove USAC code, leave fix only
big number
* fix openmp include and link issue on macos
* turn off have_openmp if OpenMP_CXX_INCLUDE_DIRS is empty
* test commit
* use condition HAVE_OPENMP and OpenMP_CXX_LIBRARIES for linking
* remove trailing whitespace
* remove notes
* update conditions
* use OpenMP_CXX_LIBRARIES for linking
Fix broken paper link for fastNlMeansDenoising
* Fix broken link
* Move citation to `opencv.bib`
* Cite researchgate reference
* Correct citation label
* Use semantic scholar BibTex
Usage of imread(): magic number 0, unchecked result
* docs: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* samples, apps: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* tests: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* doc/py_tutorials: check imread() result
https://bugs.chromium.org/p/oss-fuzz/issues/detail?id=47342
The read overflow triggered by reading `src[j]` in
```cpp
for (j = 0; j < max; ++j) {
dst[j] = src[j];
}
```
The max is calculated as `new_comps[pcol].w * new_comps[pcol].h`, however the `src = old_comps[cmp].data;` which may have different `w` and `h` dimensions.
merge with https://github.com/opencv/opencv_contrib/pull/3394
move Charuco API from contrib to main repo:
- add CharucoDetector:
```
CharucoDetector::detectBoard(InputArray image, InputOutputArrayOfArrays markerCorners, InputOutputArray markerIds,
OutputArray charucoCorners, OutputArray charucoIds) const // detect charucoCorners and/or markerCorners
CharucoDetector::detectDiamonds(InputArray image, InputOutputArrayOfArrays _markerCorners,
InputOutputArrayOfArrays _markerIds, OutputArrayOfArrays _diamondCorners,
OutputArray _diamondIds) const
```
- add `matchImagePoints()` for `CharucoBoard`
- remove contrib aruco dependencies from interactive-calibration tool
- move almost all aruco tests to objdetect
### Pull Request Readiness Checklist
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Switch to new OpenVINO API after 2022.1 release
* Pass Layer_Test_Convolution_DLDT.Accuracy/0 test
* Pass test Test_Caffe_layers.Softmax
* Failed 136 tests
* Fix Concat. Failed 120 tests
* Custom nGraph ops. 19 failed tests
* Set and get properties from Core
* Read model from buffer
* Change MaxPooling layer output names. Restore reshape
* Cosmetic changes
* Cosmetic changes
* Override getOutputsInfo
* Fixes for OpenVINO < 2022.1
* Async inference for 2021.4 and less
* Compile model with config
* Fix serialize for 2022.1
* Asynchronous inference with 2022.1
* Handle 1d outputs
* Work with model with dynamic output shape
* Fixes with 1d output for old API
* Control outputs by nGraph function for all OpenVINO versions
* Refer inputs in PrePostProcessor by indices
* Fix cycled dependency between InfEngineNgraphNode and InfEngineNgraphNet.
Add InferRequest callback only for async inference. Do not capture InferRequest object.
* Fix tests thresholds
* Fix HETERO:GPU,CPU plugin issues with unsupported layer
This change replaces references to a number of deprecated NumPy
type aliases (np.bool, np.int, np.float, np.complex, np.object,
np.str) with their recommended replacement (bool, int, float,
complex, object, str).
Those types were deprecated in 1.20 and are removed in 1.24,
cf https://github.com/numpy/numpy/pull/22607.
Parallelize implementation of HDR MergeMertens.
* Parallelize MergeMertens.
* Added performance tests for HDR.
* Ran clang-format.
* Optimizations.
* Fix data path for Windows.
* Remove compiiation warning on Windows.
* Remove clang-format for existing file.
* Addressing reviewer comments.
* Ensure correct summation order.
* Add test for determinism.
* Move result pyramid into sync struct.
* Reuse sync for first loop as well.
* Use OpenCV's threading primitives.
* Remove cout.
**Merge with contrib**: https://github.com/opencv/opencv_contrib/pull/3003
### Pull Request Readiness Checklist
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* cann backend impl v1
* cann backend impl v2: use opencv parsers to build models for cann
* adjust fc according to the new transA and transB
* put cann net in cann backend node and reuse forwardLayer
* use fork() to create a child process and compile cann model
* remove legacy code
* remove debug code
* fall bcak to CPU backend if there is one layer not supoorted by CANN backend
* fix netInput forward
G-API: replace GAPI_Assert() with 'false' and '0' to GAPI_Error()
* gapi: GAPI_Error() macro
* gapi: replace GAPI_Assert() with 'false' and '0' to GAPI_Error()
* build: eliminate 'unreachable code' after CV_Error() (MSVC 2015)
* build: eliminate 'unreachable code' warning for MSVS 2015/2017
- observed in constructors stubs with throwing exception
Megre together with https://github.com/opencv/opencv_contrib/pull/3325
1. Move aruco_detector, aruco_board, aruco_dictionary, aruco_utils to objdetect
1.1 add virtual Board::draw(), virtual ~Board()
1.2 move `testCharucoCornersCollinear` to Board classes (and rename to `checkCharucoCornersCollinear`)
1.3 add wrappers to keep the old api working
3. Reduce inludes
4. Fix java tests (add objdetect import)
5. Refactoring
### Pull Request Readiness Checklist
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```
**WIP**
force_builders=linux,win64,docs,Linux x64 Debug,Custom
Xbuild_contrib:Docs=OFF
build_image:Custom=ubuntu:22.04
build_worker:Custom=linux-1
```
videoio: add Orbbec Gemini 2 and Astra 2 camera support
### Test Result
| OS | Compiler | Camera | Result |
|-----|-----------|---------|--------|
|Windows11| (VS2022)MSVC17.3|Orbbec Gemini 2|Pass|
|Windows11| (VS2022)MSVC17.3|Orbbec Astra 2|Pass|
|Ubuntu22.04|GCC9.2|Orbbec Gemini 2|Pass|
|Ubuntu22.04|GCC9.2|Orbbec Astra 2|Pass|
### Pull Request Readiness Checklist
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* Update windows_install.markdown
Fixing Issue - #22053 Inaccuracy in the tutorial for installation for Windows
* Update windows_install.markdown #22907
Changed all changes mentioned in the comments
* Update windows_install.markdown #22907
* fix whitespace, update configurations order (64-bit goes first)
- x86 is optional and not available by default in packages
Address https://github.com/opencv/opencv/issues/22868
Used the same defaults as it's done for FFmpeg
### Pull Request Readiness Checklist
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```
force_builders=Custom
build_image:Custom=gstreamer:16.04
buildworker:Custom=linux-1
```
Add Python bindings for VideoCapture::waitAny #21826
### Pull Request Readiness Checklist
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Adds the option to enable delay loading of CUDA DLLs on Windows. This is particularly useful to use the same binary on systems with and without CUDA support without distributing the CUDA DLLs to systems that cannot use them at all due to missing CUDA-supported hardware.
Resolves#13509
DNN: reduce the memory used in convolution layer
* reduce the memory in winograd and disabel the test when usage memory is larger than 2gb.
* remove VERY_LOG tag
[teset data in opencv_extra](https://github.com/opencv/opencv_extra/pull/1016)
NanoTrack is an extremely lightweight and fast object-tracking model.
The total size is **1.1 MB**.
And the FPS on M1 chip is **150**, on Raspberry Pi 4 is about **30**. (Float32 CPU only)
With this model, many users can run object tracking on the edge device.
The author of NanoTrack is @HonglinChu.
The original repo is https://github.com/HonglinChu/NanoTrack.
### Pull Request Readiness Checklist
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Patch to opencv_extra has the same branch name.
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The current implementation overwrites the result rotation and translation in every iteration.
If SOLVEPNP_ITERATIVE was run as a refinement it will start from the incorrect initial
transformation thus degrading the final outcome.
The old documentation implies that the call is only valid for the next parallel region and must be called again if addtional regions should be affected as well.
Modify the SIMD loop in color_hsv.
* Modify the SIMD loops in color_hsv.
* Add FP supporting in bit logic.
* Add temporary compatibility code.
* Use max_nlanes instead of vlanes for array declaration.
* Use "CV_SIMD || CV_SIMD_SCALABLE".
* Revert the modify of the Universal Intrinsic API
* Fix warnings.
* Use v_select instead of bits manipulation.
Minor refactoring
Partially address review comments
Move DX-related stuff from the sample to a default source
Simplify the default OneVPL config
Address minor review comments
Add class for the default VPL source
WIP: Add initial stub for tests with description
Removing default vpl source and minor refactoring
Refactor default files
Fix build and application crash
Address review comments
Add test on VPL + OCL interaction compared to CPU behavior
Fix test
Introduce libavdevice to make v4l2 available to the ffmpeg backend
* introduce libavdevice to make v4l2 available to the ffmpeg backend
* downgrade the min required libavdevice version to 53.2.0
* make libavdevice optional
* create OCV_OPTION OPENCV_FFMPEG_ENABLE_LIBAVDEVICE and add definition through ocv_add_external_target
* move OCV_OPTION 'OPENCV_FFMPEG_ENABLE_LIBAVDEVICE' to detect_ffmpeg.cmake
OpenEXR encoder: add capability to set the DWA compression level
* OpenEXR encoder: add capability to set the DWA compression level from outside
* Do not try to call `header.dwaCompressionLevel()` if OpenEXR is not version 3 or later
* Minor cleanup
DNN: let Quant and Dequant of ONNX_importer support the Constant input.
* let Quant and Dequant support the Constant input.
* fix negative value of axis.
Setting CAP_PROP_AUTO_EXPOSURE on VideoCapture with backend DSHOW does not change anything. Now with this implementation the property can be used with value 1 for availability.
added blob contours to blob detector
* added blob contours
* Fixed Java regression test after new parameter addition to SimpleBlobDetector.
* Added stub implementation of SimpleBlobDetector::getBlobContours to presume source API compatibility.
* cmake: Fix DirectX detection in mingw
The pragma comment directive is valid for MSVC only. So, the DirectX detection
fails in mingw. The failure is fixed by adding the required linking library
(here d3d11) in the try_compile() function in OpenCVDetectDirectX.cmake file.
Also add a message if the first DirectX check fails.
* gapi: Fix compilation with mingw
These changes remove MSVC specific pragma directive. The compilation fails at
linking time due to absence of proper linking library. The required libraries
are added in corresponding CMakeLists.txt file.
* samples: Fix compilation with mingw
These changes remove MSVC specific pragma directive. The compilation fails at
linking time due to absence of proper linking library. The required libraries
are added in corresponding CMakeLists.txt file.
fix a 3rd party blur3x3 function(the 7th value in tcurr should be set to the 5th value in old tcurr, which will be be overwritten by the 3rd value in old tcurr)
* Allow the number of threads FFMpeg uses to be selected during VideoCapture::open().
Reset interupt timer in grab if
err = avformat_find_stream_info(ic, NULL);
is interupted but open is successful.
* Correct the returned number of threads and amend test cases.
* Update container test case.
* Reverse changes added to existing videoio_container test case and include test combining thread change and raw read in the newly added videoio_read test case.
In some situations the last value was missing from the discrete theta
values. Now, the last value is chosen such that it is close to the
user-provided maximum theta, while the distance to pi remains always
at least theta_step/2. This should avoid duplicate detections.
A better way would probably be to use max_theta as is and adjust the
resolution (theta_step) instead, such that the discretization would
always be uniform (in a circular sense) when full angle range is used.
Add -imshow-scale flag to resize the image when displaying the results.
Add -enable-k3 flag to enable or disable the estimation of the K3 distortion coefficient.
Add flags to set the camera intrinsic parameters as an initial guess (can allow converging to the correct camera intrinsic parameters).
Add -imshow-scale flag to resize the image when displaying the results.
Add -enable-k3 flag to enable or disable the estimation of the K3 distortion coefficient.
This fixes the following error with mingw toolchain:
opencv/modules/videoio/src/cap_msmf.cpp:1020: error: 'wstring_convert' is not a member of 'std'
1020 | std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> conv;
| ^~~~~~~~~~~~~~~
opencv/modules/videoio/src/cap_ffmpeg_hw.hpp:230:26: error: 'wstring_convert' is not a member of 'std'
230 | std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> conv;
| ^~~~~~~~~~~~~~~
The locale header is required according to C++ standard.
See https://en.cppreference.com/w/cpp/locale/wstring_convert
This fixes the following error with mingw toolchain:
opencv/modules/videoio/src/cap_obsensor/obsensor_stream_channel_msmf.hpp:160:10: error: 'condition_variable' in namespace 'std' does not name a type
160 | std::condition_variable streamStateCv_;
| ^~~~~~~~~~~~~~~~~~
libstdc++ that comes with gcc 4.8 doesn't
define `getline(basic_istream<char>&&, std::string&)`
even if it's part of the c++11 standard.
However we can still use the following:
`getline(basic_istream<char>&, std::string&)`.
* videoio: add support for obsensor (Orbbec RGB-D Camera )
* obsensor: code format issues fixed and some code optimized
* obsensor: fix typo and format issues
* obsensor: fix crosses initialization error
[GSoC] New universal intrinsic backend for RVV
* Add new rvv backend (partially implemented).
* Modify the framework of Universal Intrinsic.
* Add CV_SIMD macro guards to current UI code.
* Use vlanes() instead of nlanes.
* Modify the UI test.
* Enable the new RVV (scalable) backend.
* Remove whitespace.
* Rename and some others modify.
* Update intrin.hpp but still not work on AVX/SSE
* Update conditional compilation macros.
* Use static variable for vlanes.
* Use max_nlanes for array defining.
Reimplementation of Element-wise layers with broadcasting support
* init
* semi-working initial version
* add small_vector
* wip
* remove smallvec
* add nary function
* replace auto with Mat in lambda expr used in transform
* uncomment asserts
* autobuffer shape_buf & step_buf
* fix a missing bracket
* fixed a missing addLayer in parseElementWise
* solve one-dimensional broadcast
* remove pre_broadcast_transform for the case of two constants; fix missing constBlobsExtraInfo when addConstant is called
* one autobuffer for step & shape
* temporal fix for the missing original dimension information
* fix parseUnsqueeze when it gets a 1d tensor constant
* support sum/mean/min/max with only one input
* reuse old code to handle cases of two non-constant inputs
* add condition to handle div & mul of two non-constant inputs
* use || instead of or
* remove trainling spaces
* enlarge buf in binary_forward to contain other buffer
* use autobuffer in nary_forward
* generate data randomly and add more cases for perf
* add op and, or & xor
* update perf_dnn
* remove some comments
* remove legacy; add two ONNX conformance tests in filter
* move from cpu_denylist to all_denylist
* adjust parsing for inputs>=2
Co-authored-by: fengyuentau <yuantao.feng@opencv.org.cn>
- Add conditional compilation directives to replace deprecated std::random_shuffle with new std::shuffle when C++11 is available.
- Set random seed to a fixed value before shuffling containers to ensure reproducibility.
Resolvesopencv/opencv#22209.
Add conditional compilation directives to enable uses of std::chrono on supported compilers. Use std::chrono::steady_clock as a source to retrieve current tick count and clock frequency.
Fixesopencv/opencv#6902.
Add per_tensor_quantize to int8 quantize
* add per_tensor_quantize to dnn int8 module.
* change api flag from perTensor to perChannel, and recognize quantize type and onnx importer.
* change the default to hpp
It's not clear how ranges argument should be used in the overload of
calcHist that accepts std::vector. The main overload uses array of
arrays there, while std::vector overload uses a plain array. The code
interprets the vector as a flattened array and rebuilds array of arrays
from it. This is not obvious interpretation, so documentation has been
added to explain the expected usage.
DNN: Accelerating convolution
* Fast Conv of ARM, X86 and universal intrinsics.
* improve code style.
* error fixed.
* improve the License
* optimize memory allocated and Adjust the threshold.
* change FasterRCNN_vgg16 to 2GB memory.
Replaced sprintf with safer snprintf
* Straightforward replacement of sprintf with safer snprintf
* Trickier replacement of sprintf with safer snprintf
Some functions were changed to take another parameter: the size of the buffer, so that they can pass that size on to snprintf.
Fix issue 22015, let Clip layer support 1-3 inputs
* Fix issue 22015.
Let layer Clip support 1-3 inputs.
* Resolve other problems caused by modifications
* Update onnx_importer.cpp
added extra checks to min/max handling in Clip
* Add assertions to check the size of the input
* Add test for clip with min and max initializers
* Separate test for "clip_init_min_max". Change the check method for input_size to provide a clearer message in case of problem.
* Add tests for clip with min or max initializers
* Change the implementation of getting input
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
Fix sampling for version multiplying factor
* reduce experimentalFrequencyElem and listFrequencyElem
* fix large resize
* fix tile in postIntermediate
* add getMinSideLen(), add corrected_index
* add test decode_regression_21929 author Kumataro, add test decode_regression_version_25
* objdetect: qrcode_encoder: fix to missing timing pattern
* objdetect: qrcode_encoder: Add SCOPED_TRACE() and replace CV_Assert() to ASSERT_EQ().
- Add SCOPED_TRACE() for version loop.
- Replace CV_Assert() to ASSERT_EQ().
- Rename expect_msg to msg.
The Emscripten library is not guaranteed to be fully loaded during the
script element's onload event. Module.onRuntimeInitialized seems to be
more reliable.
Some GStreamer elements may produce buffers with very non
standard strides, offsets and/or even transport each plane
in different, non-contiguous pointers. This non-standard
layout is communicated via GstVideoMeta structures attached
to the buffers. Given this, when a GstVideoMeta is available,
one should parse the layout from it instead of generating
a generic one from the caps.
The GstVideoFrame utility does precisely this: if the buffer
contains a video meta, it uses that to fill the format and
memory layout. If there is no meta available, the layout is
inferred from the caps.
* Added support for 4B RGB V4L2 pixel formats
Added support for V4L2_PIX_FMT_XBGR32 and V4L2_PIX_FMT_ABGR32 pixel
formats.
* Added workaround for missing V4L2_PIX_FMT_ABGR32 and V4L2_PIX_FMT_XBGR32
defines
Extended DNN testing in GHA
* Extended DNN testing in GHA for 3.4 branch
* Updated docker images in Linux GitHub Actions
* Added OPENCV_DOWNLOAD_PATH flag for ARM build to use pre-downloaded binaries
Fixes and optimizations for the SQPnP solver
* Fixes and optimizations
- optimized the calculation of qa_sum by moving equal elements outside the loop
- unrolled copying of the lower triangle of omega
- substituted SVD with eigendecomposition in the factorization of omega (2-3 times faster)
- fixed the initialization of lambda in FOAM
- added a cheirality test that checks a solution on all 3D points rather than on their mean. The old test rejected valid poses in some cases
- fixed some typos & errors in comments
* reverted to SVD
Eigen decomposition seems to yield larger errors in certain tests, reverted to SVD
* nearestRotationMatrixSVD
Added nearestRotationMatrixSVD()
Previous nearestRotationMatrix() renamed to nearestRotationMatrixFOAM() and reverts to nearestRotationMatrixSVD() for singular matrices
* fixed checks order
Fixed the order of checks in PoseSolver::solveInternal()
Add undistortImagePoints function
* Add undistortImagePoints function
undistortPoints has unclear interface and additional functionality. New function computes only undistorted image points position
* Add undistortImagePoints test
* Add TermCriteria
* Fix layout
If there will be measurement before the next predict, `statePost` would be assigned to updated value. So I guess these steps are meant to handle when no measurement and KF only do the predict step.
```cpp
statePre.copyTo(statePost);
errorCovPre.copyTo(errorCovPost);
```
In test_imgproc.js, the test_filter suite's last test assigns a variable
to `size` without declaring it with `let`, polluting the global scope.
This commit adds `let` to the statement, so that the variable is scoped
to the test block.
Added workflow for Github Actions to build and test OpenCV on Windows for 3.4 branch
* Added workflow for Github Actions to build and test OpenCV on Windows
* Updated Github Actions for 3.4 branch on Windows using self-hosted runner
* Fixed url for a fork in Windows workflow (3.4 branch)
* opencv_extra fork usage in Github Actions
Added workflow for Github Actions to build and test OpenCV on Linux for 4.x
* Added workflow for Github Actions to build and test OpenCV
* Merged a build and tests jobs into one, split tests by steps, renamed job names
Added workflow for Github Actions to build and test OpenCV on Linux
* Added workflow for Github Actions to build and test OpenCV
* Merged a build and tests in one job, changed naming
* Renamed job names, split workflows by branch, removed and added some cmake flags, save unit tests results as a html file
* Split tests by steps, removed workflows for 4.x and 5.x branches
Add distort/undistort test for fisheye::undistortPoints()
* Add distort/undistort test for fisheye::undistortPoints()
Lack of test has allowed error described in 19138 to be unnoticed.
In addition to random points, four corners and principal center
added to point set
* Add random distortion coefficients set
* Move undistortPoints test to google test, refactor
* Add fisheye::undistortPoints() perf test
* Add negative distortion coefficients to undistortPoints test, increase value
* Move to theRNG()
* Change test check from cvtest::norm(L2) to EXPECT_MAT_NEAR()
* Layout fix
* Add points number parameters, comments
[GAPI] Support basic inference in OAK backend
* Combined commit which enables basic inference and other extra capabilities of OAK backend
* Remove unnecessary target options from the cmakelist
Fixed out-of-bounds read in parallel version of ippGaussianBlur()
* Fixed out-of-memory read in parallel version of ippGaussianBlur()
* Fixed check
* Revert changes in CMakeLists.txt
Fixed handling of new stream, especially for stateful OCV kernels
* Fixed handling of new stream, especially for stateful OCV kernels
* Removed duplication from StateInitOnce tests
* Addressed review comments for PR #21731
- Fixed explanation comments
- Expanded test for stateful OCV kernels in Regular mode
* Addressed review comments for PR #21731
- Moved notification about new stream to the constructor
- Added test on state reset for Regular mode
* Addresed review comments
* Addressed review comments
Co-authored-by: Ruslan Garnov <ruslan.garnov@intel.com>
python binding for matches and inliers_mask attributes of cv2.detail_MatchesInfo class
* making matches and inliers_mask attributes of cv2.detail_MatchesInfo class accessible from python interface
* binding test for cv2.detail_MatchesInfo class
CI for TIM-VX backend
* github actions for TIM-VX backend https://github.com/opencv/opencv/pull/21036
* add reference to yuentau/ocv_ubuntu:20.04; remove extra quotes; enable BUILD_TESTS
* rename to timvx_backend_tests.yml
* add image source prefix
* remove if condition for x86_64 simulator
[G-API] Handle exceptions in streaming executor
* Handle exceptions in streaming executor
* Rethrow exception in non-streaming executor
* Clean up
* Put more tests
* Handle exceptions in IE backend
* Handle exception in IE callbacks
* Handle exception in GExecutor
* Handle all exceptions in IE backend
* Not only (std::exception& e)
* Fix comments to review
* Handle input exception in generic way
* Fix comment
* Clean up
* Apply review comments
* Put more comments
* Fix alignment
* Move test outside of HAVE_NGRAPH
* Fix compilation
/wrkdirs/usr/ports/graphics/opencv/work/opencv-4.5.5/modules/core/include/opencv2/core/vsx_utils.hpp:352:12: warning: 'vec_permi' macro redefined [-Wmacro-redefined]
# define vec_permi(a, b, c) vec_xxpermdi(b, a, (3 ^ (((c) & 1) << 1 | (c) >> 1)))
^
/usr/lib/clang/13.0.0/include/altivec.h:13077:9: note: previous definition is here
#define vec_permi(__a, __b, __c) \
^
/wrkdirs/usr/ports/graphics/opencv/work/opencv-4.5.5/modules/core/include/opencv2/core/vsx_utils.hpp:370:25: error: redefinition of 'vec_promote'
VSX_FINLINE(vec_dword2) vec_promote(long long a, int b)
^
/usr/lib/clang/13.0.0/include/altivec.h:14604:1: note: previous definition is here
vec_promote(signed long long __a, int __b) {
^
/wrkdirs/usr/ports/graphics/opencv/work/opencv-4.5.5/modules/core/include/opencv2/core/vsx_utils.hpp:377:26: error: redefinition of 'vec_promote'
VSX_FINLINE(vec_udword2) vec_promote(unsigned long long a, int b)
^
/usr/lib/clang/13.0.0/include/altivec.h:14611:1: note: previous definition is here
vec_promote(unsigned long long __a, int __b) {
^
/wrkdirs/usr/ports/graphics/opencv/work/opencv-4.5.5/modules/core/include/opencv2/core/hal/intrin_vsx.hpp:1045:22: error: call to 'vec_rsqrt' is ambiguous
{ return v_float32x4(vec_rsqrt(x.val)); }
^~~~~~~~~
/usr/lib/clang/13.0.0/include/altivec.h:8472:34: note: candidate function
static vector float __ATTRS_o_ai vec_rsqrt(vector float __a) {
^
/wrkdirs/usr/ports/graphics/opencv/work/opencv-4.5.5/modules/core/include/opencv2/core/vsx_utils.hpp:362:29: note: candidate function
VSX_FINLINE(vec_float4) vec_rsqrt(const vec_float4& a)
^
/wrkdirs/usr/ports/graphics/opencv/work/opencv-4.5.5/modules/core/include/opencv2/core/hal/intrin_vsx.hpp:1047:22: error: call to 'vec_rsqrt' is ambiguous
{ return v_float64x2(vec_rsqrt(x.val)); }
^~~~~~~~~
/usr/lib/clang/13.0.0/include/altivec.h:8477:35: note: candidate function
static vector double __ATTRS_o_ai vec_rsqrt(vector double __a) {
^
/wrkdirs/usr/ports/graphics/opencv/work/opencv-4.5.5/modules/core/include/opencv2/core/vsx_utils.hpp:365:30: note: candidate function
VSX_FINLINE(vec_double2) vec_rsqrt(const vec_double2& a)
^
1 warning and 4 errors generated.
The specific functions were added to altivec.h in LLVM's 1ff93618e58df210def48d26878c20a1b414d900, c3da07d216dd20fbdb7302fd085c0a59e189ae3d and 10cc5bcd868c433f9a781aef82178b04e98bd098.
Support downloading 3rdparty resources from Gitcode & Gitlab-style mirrors
* replace github.com with gitcode.net for ocv_download
* replace raw.githubusercontent.com with gitcode.net for ocv_download
* rename funtions and remove some comments
* add options for custom mirrors, which simply replace domain github.com & githubusercontent.com
* run ocv_init_download once; replace DL_URL with mirrored one when calling ocv_download
* fix for empty download links when not using mirror
* fix bugs: set(.. .. PARENT_SCOPE) for ocv_init_download; correct macro names for replace github archives and raw githubusercontent
* adjusted mirror swapping impl: replace with mirrored link before each ocv_download; update md5sum for archives
* fix a bug: macro invoked with incorrect arguments by non-set vars
* enclose if statement
* workable impl
* shorten the var names of two key options
* scalable implementation of downloading from mirror and using custom mirror
* improve ocv_init_download help message
* fix the different extracted directory name in case of ADE & TBB which are downloaded from release page
* improve help message printing
* Download ADE & TBB using commit ids instead of from release pages
* support custom mirrors on downloading archives
* improve hints
* add missing parentheses
* reset ocv_download calls
* mirror support implementation using ocv_cmake_hook & ocv_cmake_hook_append
* move ocv_init_download into cmake/OpenCVDownload.cmake
* move ocv_cmake_hook before checking CMake cache
* improve hints when not fetching as git repo
* add WORKING_DIRECTORY in execute_process in ocv_init_download
* use OPENCV_DOWNLOAD_MIRROR_ID
* add custom.cmake for custom mirror
* detect github origin
* fix broken var name
* download from github by default if custom tbb is set
* add checksum checks for gitcode.cmake before replacing urls and checksums
* add checksum checks for custom.cmake before replacing urls and checkusms
* use description specify instead of set for messages in custom.cmake; use warning message for warnings
* updates and fixes
* better accuracy of _rotatedRectangleIntersection
instead of just migrating to double-precision (which would work), some computations are scaled by a factor that depends on the length of the smallest vectors.
There is a better accuracy even with floats, so this is certainly better for very sensitive cases
* Update intersection.cpp
use L2SQR norm to tune the numeric scale
* Update intersection.cpp
adapt samePointEps with L2 norm
* Update intersection.cpp
move comment
* Update intersection.cpp
fix wrong numericalScalingFactor usage
* added tests
* fixed warnings returned by buildbot
* modifications suggested by reviewer
renaming numericalScaleFctor to normalizationScale
refactor some computations
more "const"
* modifications as suggested by reviewer
Fix LSTM support in ONNX
* fix LSTM and add peephole support
* disable old tests
* turn lambdas into functions
* more hacks for c++98
* add assertions
* slice fixes
* backport of cuda-related fixes
* address review comments
Add 10-12-14bit (integer) TIFF decoding support
* Add 12bit (integer) TIFF decoding support
An (slow) unpacking step is inserted when the native bpp is not equal to the dst_bpp
Currently, I do not know if there can be several packing flavours in TIFF data.
* added tests
* move sample files to opencv_extra
* added 10b and 14b unpacking
* fix compilation for non MSVC compilers by using more standard typedefs
* yet another typdef usage change to fix buildbot Mac compilation
* fixed unpacking of partial packets
* fixed warnings returned by buildbot
* modifications as suggested by reviewer
* add apply softmax option to ClassificationModel
* remove default arguments of ClassificationModel::setSoftMax()
* fix build for python
* fix docs warning for setSoftMax()
* add impl for ClassficationModel()
* fix failed build for docs by trailing whitespace
* move to implement classify() to ClassificationModel_Impl
* move to implement softmax() to ClassificationModel_Impl
* remove softmax from public method in ClassificationModel
### Critical bugs fixed:
- `seam_finder.find()` returns None and overwrites `masks_warped`
- `indices` is only 1-dimensional
### Nice-to-have bugs fixed:
- avoid invalid value in sqrt and subsequent runtime warning
- avoid printing help string on each run (use argparse builtin behavior)
### New features:
- added graphcut seam finder support
### Test Summary:
Tested on Ubuntu 20.04 with python 3.8.10 and opencv-python-contrib 4.5.5.62
All classes are registered in the scope that corresponds to C++
namespace or exported class.
Example:
`cv::ml::Boost` is exported as `cv.ml.Boost`
`cv::SimpleBlobDetector::Params` is exported as
`cv.SimpleBlobDetector.Params`
For backward compatibility all classes are registered in the global
module with their mangling name containing scope information.
Example:
`cv::ml::Boost` has `cv.ml_Boost` alias to `cv.ml.Boost` type
Optimize cv::applyColorMap() for simple case
* Optimize cv::applyColorMap() for simple case
PR for 21640
For regular cv::Mat CV_8UC1 src, applying the colormap is simpler than calling the cv::LUT() mechanism.
* add support for src as CV_8UC3
src as CV_8UC3 is handled with a BGR2GRAY conversion, the same optimized code being used afterwards
* code style
rely on cv::Mat.ptr() to index data
* Move new implementation to ColorMap::operator()
Changes as suggested by reviewer
* style
improvements suggsted by reviewer
* typo
* tune parallel work
* better usage of parallel_for_
use nstripes parameter of parallel_for_
assume _lut is continuous to bring faster pixel indexing
optimize src/dst access by contiguous rows of pixels
do not locally copy the LUT any more, it is no more relevant with the new optimizations
* Added NEON support in builds for Windows on ARM
* Fixed `HAVE_CPU_NEON_SUPPORT` display broken during compiler test
* Fixed a build error prior to Visual Studio 2022
4.x: submodule or a class scope for exported classes
* feature: submodule or a class scope for exported classes
All classes are registered in the scope that corresponds to C++
namespace or exported class.
Example:
`cv::ml::Boost` is exported as `cv.ml.Boost`
`cv::SimpleBlobDetector::Params` is exported as
`cv.SimpleBlobDetector.Params`
For backward compatibility all classes are registered in the global
module with their mangling name containing scope information.
Example:
`cv::ml::Boost` has `cv.ml_Boost` alias to `cv.ml.Boost` type
* refactor: remove redundant GAPI aliases
* fix: use explicit string literals in CVPY_TYPE macro
* fix: add handling for class aliases
Use YuNet of fixed input shape to fix not-supported-dynamic-zero-shape for FaceDetectorYN
* use yunet with input of fixed shape
* update yunet used in face recognition regression
Thread Sanitizer identified an incorrect implementation of double checked locking.
Replaced it with a static, which therefore can only be created once.
Default FFMPEG VideoCapture backend to rtsp_flags=prefer_tcp
* Make the VideoCapture ffmpeg backends default rtsp connection type prefer_tcp.
* Ensure that the ffmpeg version of avformat is checked.
there is a recent change, how `std::vector<int>` is wrapped in python,
it used to be a 2d array (requirig that weird `[0]` indexing), now it is only 1d
Per intel docs for libva, when vaDeriveImage fails vaCreateImage +
vaPutImage should be tried. This is important as mesa with AMD HW
will always fail because the image is interlaced so a indirect
method must be used to get the surface to/from and image
Fixes https://github.com/opencv/opencv/issues/21536
* Fix wrong MSAN errors.
Because Fortran is called in Lapack, MSAN does not think the memory
has been written even though it is the case.
MSAN does no support well cross-language memory analysis.
* Make a dedicated check.
- Add special case handling when submodule has the same name as parent
- `PyDict_SetItemString` doesn't steal reference, so reference count
should be explicitly decremented to transfer object life-time
ownership
- Add sanity checks for module registration input
- Add Python 2 and Python 3 reference counting handling
G-API: Wrap GStreamerSource
* Wrap GStreamerSource into python
* Fixed test skipping when can't make Gst-src
* Wrapped GStreamerPipeline class, added dummy test for it
* Fix no_gst testing
* Changed wrap for GStreamerPipeline::getStreamingSource() : now python-specific in-class method GStreamerPipeline::get_streaming_source()
* Added accuracy tests vs OCV:VideoCapture(Gstreamer)
* Add skipping when can't use VideoCapture(GSTREAMER);
Add better handling of GStreamer backend unavailable;
Changed video to avoid terminations
* Applying comments
* back to a separate get_streaming_source function, with comment
Co-authored-by: OrestChura <orest.chura@intel.com>
G-API: oneVPL DX11 inference
* Draft GPU infer
* Fix incorrect subresource_id for array of textures
* Fix for TheOneSurface in different Frames
* Turn on VPP param configuration
* Add cropIn params
* Remove infer sync sample
* Remove comments
* Remove DX11AllocResource extra init
* Add condition for NV12 processing in giebackend
* Add VPP frames pool param configurable
* -M Remove extra WARN & INFOs, Fix custom MAC
* Remove global vars from example, Fix some comments, Disable blobParam due to OV issue
* Conflict resolving
* Revert back pointer cast for cv::any
clang-cl defines both __clang__ and _MSC_VER, yet uses `#pragma GCC` to disable certain diagnostics.
At the time `-Wreturn-type-c-linkage` was reported by clang-cl.
This PR fixes this behavior by reordering defines.
- Add special case handling when submodule has the same name as parent
- `PyDict_SetItemString` doesn't steal reference, so reference count
should be explicitly decremented to transfer object life-time
ownership
- Add sanity checks for module registration input
Comment from Python documentation:
Unlike other functions that steal references, `PyModule_AddObject()` only
decrements the reference count of value on success.
This means that its return value must be checked, and calling code must
`Py_DECREF()` value manually on error.
GAPI: Add OAK backend
* Initial tests and cmake integration
* Add a public header and change tests
* Stub initial empty template for the OAK backend
* WIP
* WIP
* WIP
* WIP
* Runtime dai hang debug
* Refactoring
* Fix hang and debug frame data
* Fix frame size
* Fix data size issue
* Move test code to sample
* tmp refactoring
* WIP: Code refactoring except for the backend
* WIP: Add non-camera sample
* Fix samples
* Backend refactoring wip
* Backend rework wip
* Backend rework wip
* Remove mat encoder
* Fix namespace
* Minor backend fixes
* Fix hetero sample and refactor backend
* Change linking logic in the backend
* Fix oak sample
* Fix working with ins/outs in OAK island
* Trying to fix nv12 problem
* Make both samples work
* Small refactoring
* Remove meta args
* WIP refactoring kernel API
* Change in/out args API for kernels
* Fix build
* Fix cmake warning
* Partially address review comments
* Partially address review comments
* Address remaining comments
* Add memory ownership
* Change pointer-to-pointer to reference-to-pointer
* Remove unnecessary reference wrappers
* Apply review comments
* Check that graph contains only one OAK island
* Minor refactoring
* Address review comments
The Qt backend directly calls some OpenGL functions (glClear, glHint,
glViewport), but since OCV 4.5.5 the GL libraries are no longer part
of the global extra dependencies. When linking with "-Wl,--no-undefined"
this causes linker errors:
`opencv-4.5.5/modules/highgui/src/window_QT.cpp:3307: undefined reference to `glClear'`
Fixes: #21346
Related issues: #21299
Further optimize DNN for RISC-V Vector.
* Optimize DNN on RVV by using vsetvl.
* Rename vl.
* Update fastConv by using setvl instead of mask.
* Fix fastDepthwiseConv
* fix unicode errors for framework headers
This would crash if the header file included non-ASCII characters. This change ensures that headers are read and written as UTF-8 encoded files instead of ascii.
* Adds spaces after commas
- QGLWidget changed to QOpenGLWidget in window_QT.h for Qt6 using
typedef OpenCVQtWidgetBase for handling Qt version
- Implement Qt6/OpenGL functionality in window_QT.cpp
- Swap QGLWidget:: function calls for OpenCVQtWidgetBase:: function calls
- QGLWidget::updateGL deprecated, swap to QOpenGLWidget::update for Qt6
- Add preprocessor definition to detect Qt6 -- HAVE_QT6
- Add OpenGLWidgets to qdeps list in highgui CMakeLists.txt
- find_package CMake command added for locating Qt module OpenGLWidgets
- Added check that Qt6::OpenGLWidgets component is found. Shut off Qt-openGL functionality if not found.
G-API: oneVPL merge DX11 acceleration
* Merge DX11 initial
* Fold conditions row in MACRO in utils
* Inject DeviceSelector
* Turn on DeviceSelector in DX11
* Change sharedLock logic & Move FMT checking in FrameAdapter c-tor
* Move out NumSuggestFrame to configure params
* Drain file source fix
* Fix compilation
* Force zero initializetion of SharedLock
* Fix some compiler warnings
* Fix integer comparison warnings
* Fix integers in sample
* Integrate Demux
* Fix compilation
* Add predefined names for some CfgParam
* Trigger CI
* Fix MultithreadCtx bug, Add Dx11 GetBlobParam(), Get rif of ATL CComPtr
* Fix UT: remove unit test with deprecated video from opencv_extra
* Add creators for most usable CfgParam
* Eliminate some warnings
* Fix warning in GAPI_Assert
* Apply comments
* Add VPL wrapped header with MSVC pragma to get rid of global warning masking
Added CV_PROP_RW macro to keypoints
* Added CV_PROP_RW macro to keypoints
As outlined in the feature request in the issue https://github.com/opencv/opencv/issues/21171 : the keypoints field has been made parsable by the bindings.
* Added test for keypoints
Added test to check if the CV_PROP_RW macro added in the previous commit makes keypoints public and accessible through the python API.
Audio MSMF: added the ability to set sample per second
* Audio MSMF: added the ability to set sample per second
* changed the valid sampling rate check
* fixed docs
* add test
* fixed warning
* fixed error
* fixed error
Update RVV backend for using Clang.
* Update cmake file of clang.
* Modify the RVV optimization on DNN to adapt to clang.
* Modify intrin_rvv: Disable some existing types.
* Modify intrin_rvv: Reinterpret instead of load&cast.
* Modify intrin_rvv: Update load&store without cast.
* Modify intrin_rvv: Rename vfredsum to fredosum.
* Modify intrin_rvv: Rewrite Check all/any by using vpopc.
* Modify intrin_rvv: Use reinterpret instead of c-style casting.
* Remove all macros which is not used in v_reinterpret
* Rename vpopc to vcpop according to spec.
[G-API] Fix issue of getting 1D Mat out of RMat::View
* Fix issue of getting 1D Mat out of RMat::View
- added test
- fixed for standalone too (removed Assert(dims.empty()))
* Fixed asVeiw() function for standalone
* Put more detailed comment
Add capacity to Videocapture to return the extraData from FFmpeg when required
* Update rawMode to append any extra data recieved during the initial negotiation of an RTSP stream or during the parsing of an MPEG4 file header.
For h264[5] RTSP streams this ensures the parameter sets if available are always returned on the first call to grab()/read() and has two purposes:
1) To ensure the parameter sets are available even if they are not transmitted in band. This is common for axis ip camera's.
2) To allow callers of VideoCapture::grab()[read()] to write to split the raw stream over multiple files by appending the parameter sets to the begining of any new files.
For (1) there is no alternative, for (2) if the parameter sets were provided in band it would be possible to parse the raw bit stream and search for the parameter sets however that would be a lot of work when that information is already provided by FFMPEG.
For MPEG4 files this information is only suplied in the header and is required for decoding.
Two properties are also required to enable the raw encoded bitstream to be written to multiple files, these are;
1) an indicator as to whether the last frame was a key frame or not - each new file needs to start at a key frame to avoid storing unusable frame diffs,
2) the length in bytes of the paramater sets contained in the last frame - required to split the paramater sets from the frame without having to parse the stream. Any call to VideoCapture::get(CAP_PROP_LF_PARAM_SET_LEN) returning a number greater than zero indicates the presense of a parameter set at the begining of the raw bitstream.
* Adjust test data to account for extraData
* Address warning.
* Change added property names and remove paramater set start code check.
* Output extra data on calls to retrieve instead of appending to the first packet.
* Reverted old test case and added new one to evaluate new functionality.
* Add missing definition.
* Remove flag from legacy api.
Add property to determine if returning extra data is supported.
Always allow extra data to be returned on calls to cap.retrieve()
Update test case.
* Update condition which indicates CAP_PROP_CODEC_EXTRADATA_INDEX is not supported in test case.
* Include compatibility for windows dll if not updated.
Enforce existing return status convention.
* Fix return error and missing test constraints.
[GSoC] OpenCV.js: Accelerate OpenCV.js DNN via WebNN
* Add WebNN backend for OpenCV DNN Module
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Add WebNN head files into OpenCV 3rd partiy files
Create webnn.hpp
update cmake
Complete README and add OpenCVDetectWebNN.cmake file
add webnn.cpp
Modify webnn.cpp
Can successfully compile the codes for creating a MLContext
Update webnn.cpp
Update README.md
Update README.md
Update README.md
Update README.md
Update cmake files and
update README.md
Update OpenCVDetectWebNN.cmake and README.md
Update OpenCVDetectWebNN.cmake
Fix OpenCVDetectWebNN.cmake and update README.md
Add source webnn_cpp.cpp and libary libwebnn_proc.so
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
update dnn.cpp
update op_webnn
update op_webnn
Update op_webnn.hpp
update op_webnn.cpp & hpp
Update op_webnn.hpp
Update op_webnn
update the skeleton
Update op_webnn.cpp
Update op_webnn
Update op_webnn.cpp
Update op_webnn.cpp
Update op_webnn.hpp
update op_webnn
update op_webnn
Solved the problems of released variables.
Fixed the bugs in op_webnn.cpp
Implement op_webnn
Implement Relu by WebNN API
Update dnn.cpp for better test
Update elementwise_layers.cpp
Implement ReLU6
Update elementwise_layers.cpp
Implement SoftMax using WebNN API
Implement Reshape by WebNN API
Implement PermuteLayer by WebNN API
Implement PoolingLayer using WebNN API
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Implement poolingLayer by WebNN API and add more detailed logs
Update dnn.cpp
Update dnn.cpp
Remove redundant codes and add more logs for poolingLayer
Add more logs in the pooling layer implementation
Fix the indent issue and resolve the compiling issue
Fix the build problems
Fix the build issue
FIx the build issue
Update dnn.cpp
Update dnn.cpp
* Fix the build issue
* Implement BatchNorm Layer by WebNN API
* Update convolution_layer.cpp
This is a temporary file for Conv2d layer implementation
* Integrate some general functions into op_webnn.cpp&hpp
* Update const_layer.cpp
* Update convolution_layer.cpp
Still have some bugs that should be fixed.
* Update conv2d layer and fc layer
still have some problems to be fixed.
* update constLayer, conv layer, fc layer
There are still some bugs to be fixed.
* Fix the build issue
* Update concat_layer.cpp
Still have some bugs to be fixed.
* Update conv2d layer, fully connected layer and const layer
* Update convolution_layer.cpp
* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)
* Delete bib19450.aux
* Add WebNN backend for OpenCV DNN Module
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Add WebNN head files into OpenCV 3rd partiy files
Create webnn.hpp
update cmake
Complete README and add OpenCVDetectWebNN.cmake file
add webnn.cpp
Modify webnn.cpp
Can successfully compile the codes for creating a MLContext
Update webnn.cpp
Update README.md
Update README.md
Update README.md
Update README.md
Update cmake files and
update README.md
Update OpenCVDetectWebNN.cmake and README.md
Update OpenCVDetectWebNN.cmake
Fix OpenCVDetectWebNN.cmake and update README.md
Add source webnn_cpp.cpp and libary libwebnn_proc.so
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
update dnn.cpp
update op_webnn
update op_webnn
Update op_webnn.hpp
update op_webnn.cpp & hpp
Update op_webnn.hpp
Update op_webnn
update the skeleton
Update op_webnn.cpp
Update op_webnn
Update op_webnn.cpp
Update op_webnn.cpp
Update op_webnn.hpp
update op_webnn
update op_webnn
Solved the problems of released variables.
Fixed the bugs in op_webnn.cpp
Implement op_webnn
Implement Relu by WebNN API
Update dnn.cpp for better test
Update elementwise_layers.cpp
Implement ReLU6
Update elementwise_layers.cpp
Implement SoftMax using WebNN API
Implement Reshape by WebNN API
Implement PermuteLayer by WebNN API
Implement PoolingLayer using WebNN API
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Implement poolingLayer by WebNN API and add more detailed logs
Update dnn.cpp
Update dnn.cpp
Remove redundant codes and add more logs for poolingLayer
Add more logs in the pooling layer implementation
Fix the indent issue and resolve the compiling issue
Fix the build problems
Fix the build issue
FIx the build issue
Update dnn.cpp
Update dnn.cpp
* Fix the build issue
* Implement BatchNorm Layer by WebNN API
* Update convolution_layer.cpp
This is a temporary file for Conv2d layer implementation
* Integrate some general functions into op_webnn.cpp&hpp
* Update const_layer.cpp
* Update convolution_layer.cpp
Still have some bugs that should be fixed.
* Update conv2d layer and fc layer
still have some problems to be fixed.
* update constLayer, conv layer, fc layer
There are still some bugs to be fixed.
* Update conv2d layer, fully connected layer and const layer
* Update convolution_layer.cpp
* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)
* Update dnn.cpp
* Fix Error in dnn.cpp
* Resolve duplication in conditions in convolution_layer.cpp
* Fixed the issues in the comments
* Fix building issue
* Update tutorial
* Fixed comments
* Address the comments
* Update CMakeLists.txt
* Offer more accurate perf test on native
* Add better perf tests for both native and web
* Modify per tests for better results
* Use more latest version of Electron
* Support latest WebNN Clamp op
* Add definition of HAVE_WEBNN macro
* Support group convolution
* Implement Scale_layer using WebNN
* Add Softmax option for native classification example
* Fix comments
* Fix comments
* Update how_to_use_OpenCV_parallel_for_new.markdown
Fix an incorrect jump link in the tutorial how_to_use_OpenCV_parallel_for_new.
* Update how_to_use_OpenCV_parallel_for_new.markdown
Update the URL of the tutorial code.
G-API: Removing G-API test code that is a reflection of ts module
* gapi: don't hijack testing infrastructure
* Removed initDataPath functionality (ts module exists)
* Removed false for ocv_extra data from findDataFile
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
[G-API] Fix bugs in GIEBackend
* Remove inputs/outputs map from IEUnit
* Add test
* Add NV12 test
* Reorganize setBlob function
* Check that backend don't overwrite blob precision
* Stop setting config to global IE::Core
* Replace mutable to const_cast
* Update modules/gapi/test/infer/gapi_infer_ie_test.cpp
* Update modules/gapi/test/infer/gapi_infer_ie_test.cpp
* Make blob parameter as const ref
* Cosmetic fixes
* Fix failed test on inferROI
* Removed double ref for ii
* Disable tests
* Skip tests if device not available
* Use Sync prim under shared_ptr to avoid issue on MAC
* Apply WA for IE::Core
* Apply WA for MAC build
* Try to apply another WA
* Not release IE::Core for apple
* Put comment
* Support PreprocInfo for
* InferROI
* InferList
* InferList2
* Remove empty line
* Fix alignment
Co-authored-by: Maxim Pashchenkov <maxim.pashchenkov@intel.com>
Fix the following build failure with gcc 4.8:
In file included from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg_impl.hpp:100:0,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg.cpp:50:
/home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg_hw.hpp: In constructor 'HWAccelIterator::HWAccelIterator(cv::VideoAccelerationType, bool, AVDictionary*)':
/home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg_hw.hpp:939:23: error: use of deleted function 'std::basic_istringstream<char>& std::basic_istringstream<char>::operator=(const std::basic_istringstream<char>&)'
s_stream_ = std::istringstream(accel_list);
^
In file included from /home/buildroot/autobuild/instance-3/output-1/host/opt/ext-toolchain/arm-none-linux-gnueabi/include/c++/4.8.3/complex:45:0,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/core/include/opencv2/core/cvstd.inl.hpp:47,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/core/include/opencv2/core.hpp:3306,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/include/opencv2/videoio.hpp:46,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/precomp.hpp:57,
from /home/buildroot/autobuild/instance-3/output-1/build/opencv4-4.5.4/modules/videoio/src/cap_ffmpeg.cpp:42:
/home/buildroot/autobuild/instance-3/output-1/host/opt/ext-toolchain/arm-none-linux-gnueabi/include/c++/4.8.3/sstream:272:11: note: 'std::basic_istringstream<char>& std::basic_istringstream<char>::operator=(const std::basic_istringstream<char>&)' is implicitly deleted because the default definition would be ill-formed:
class basic_istringstream : public basic_istream<_CharT, _Traits>
^
/home/buildroot/autobuild/instance-3/output-1/host/opt/ext-toolchain/arm-none-linux-gnueabi/include/c++/4.8.3/sstream:272:11: error: use of deleted function 'std::basic_istream<char>& std::basic_istream<char>::operator=(const std::basic_istream<char>&)'
Fixes:
- http://autobuild.buildroot.org/results/60f8846b435dafda0ced412d59ffe15bdff0810d
Signed-off-by: Fabrice Fontaine <fontaine.fabrice@gmail.com>
G-API: oneVPL - Performance: Add async decode pipeline & add cached pool
* Add async decode pipeline & intro cached pool
* Fix performacne test with checking OPENCV_EXTRA
* Add sip perf test with no VPL
* Fix misprint
* Remove empty line..
* Apply some comments
* Apply some comments
* Make perf test fail if no OPENCV_TEST_DATA_PATH declared
Fix: #21021
NDK API AMediaCodec_getOutputBuffer() returns MediaCodecBuffer::data()
which is actually ABuffer::data(). The returned buffer address is already
adjusted by offset.
More info:
ABuffer::base() returns base address without offset
ABuffer::data() returns base + offset
Change-Id: I2936339ce4fa9acf657a5a7d92adc1275d7b28a1
G-API: Disable Windows warnings with 4996 code
* Windows warnings 4503 and 4996 are disabled with dnn style
* Applying comments to review
* Reproducing
* Added check MSVC_VERSION for both warnings
* bmp specified BI_BITFIELDS should take care RGBA bit mask
* change the name
* support xrgb bmp file
* support xrgb bmp file(add test case)
* update testing code
Add DNN-based face detection and face recognition into modules/objdetect
* Add DNN-based face detector impl and interface
* Add a sample for DNN-based face detector
* add recog
* add notes
* move samples from samples/cpp to samples/dnn
* add documentation for dnn_face
* add set/get methods for input size, nms & score threshold and topk
* remove the DNN prefix from the face detector and face recognizer
* remove default values in the constructor of impl
* regenerate priors after setting input size
* two filenames for readnet
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face_recognize.cpp
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update face.hpp
* Update dnn_face.markdown
* add regression test for face detection
* remove underscore prefix; fix warnings
* add reference & acknowledgement for face detection
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update ts.hpp
* Update test_face.cpp
* Update face_match.cpp
* fix a compile error for python interface; add python examples for face detection and recognition
* Major changes for Vadim's comments:
* Replace class name FaceDetector with FaceDetectorYN in related failes
* Declare local mat before loop in modules/objdetect/src/face_detect.cpp
* Make input image and save flag optional in samples/dnn/face_detect(.cpp, .py)
* Add camera support in samples/dnn/face_detect(.cpp, .py)
* correct file paths for regression test
* fix convertion warnings; remove extra spaces
* update face_recog
* Update dnn_face.markdown
* Fix warnings and errors for the default CI reports:
* Remove trailing white spaces and extra new lines.
* Fix convertion warnings for windows and iOS.
* Add braces around initialization of subobjects.
* Fix warnings and errors for the default CI systems:
* Add prefix 'FR_' for each value name in enum DisType to solve the
redefinition error for iOS compilation; Modify other code accordingly
* Add bookmark '#tutorial_dnn_face' to solve warnings from doxygen
* Correct documentations to solve warnings from doxygen
* update FaceRecognizerSF
* Fix the error for CI to find ONNX models correctly
* add suffix f to float assignments
* add backend & target options for initializing face recognizer
* add checkeq for checking input size and preset size
* update test and threshold
* changes in response to alalek's comments:
* fix typos in samples/dnn/face_match.py
* import numpy before importing cv2
* add documentation to .setInputSize()
* remove extra include in face_recognize.cpp
* fix some bugs
* Update dnn_face.markdown
* update thresholds; remove useless code
* add time suffix to YuNet filename in test
* objdetect: update test code
Make the implementation of optimization in DNN adjustable to different vector sizes with RVV intrinsics.
* Update fastGEMM for multi VLEN.
* Update fastGEMM1T for multi VLEN.
* Update fastDepthwiseConv for multi VLEN.
* Update fastConv for multi VLEN.
* Replace malloc with cv::AutoBuffer.
dnn : int8 quantized layers support in onnx importer
* added quantized layers support in onnx importer
* added more cases in eltwise node, some more checks
* added tests for quantized nodes
* relax thresholds for failed tests, address review comments
* refactoring based on review comments
* added support for unsupported cases and pre-quantized resnet50 test
* relax thresholds due to int8 resize layer
Add ExpandDims layer of tf_importer.cpp
* Add ExpandDims to tf_importer.
* add -1 expand test case.
* Support different dimensions of input.
* Compatible with 5-dimensional NDHWC data
* Code align
* support 3-dim input.
* 3-dim bug fixed.
* fixing error of code format.
Recover pose from different cameras (version 2)
* add recoverPose for two different cameras
* Address review comments from original PR
* Address new review comments
* Rename private api
Co-authored-by: tompollok <tom.pollok@gmail.com>
Co-authored-by: Zane <zane.huang@mail.utoronto.ca>
G-API: Handle reshape for generic case in GExecutor
* Handle reshape for generic case for GExecutor
* Add initResources
* Add tests
* Refactor reshape method
* feat: OpenCV extension with pure Python modules
* feat: cv2 is now a Python package instead of extension module
Python package cv2 now can handle both Python and C extension modules
properly without additional "subfolders" like "_extra_py_code".
* feat: can call native function from its reimplementation in Python
Tutorial for parallel_for_ and Universal Intrinsic (GSoC '21)
* New parallel_for tutorial
* Universal Intrinsics Draft Tutorial
* Added draft of universal intrinsic tutorial
* * Added final markdown for parallel_for_new
* Added first half of universal intrinsic tutorial
* Fixed warnings in documentation and sample code for parallel_for_new
tutorial
* Restored original parallel_for_ tutorial and table_of_content_core
* Minor changes
* Added demonstration of 1-D vectorized convolution
* * Added 2-D convolution implementation and tutorial
* Minor changes in vectorized implementation of 1-D and 2-D convolution
* Minor changes to univ_intrin tutorial. Added new tutorials to the table of contents
* Minor changes
* Removed variable sized array initializations
* Fixed conversion warnings
* Added doxygen references, minor fixes
* Added jpg image for parallel_for_ doc
Add CAP_PROP_STREAM_OPEN_TIME
* Added CAP_PROP_STREAM_OPEN_TIME to videoio module - can be used to query the time at which the stream was opened, in seconds since Jan 1 1970 (midnight, UTC). Useful for RTSP and other live video where absolute timestamps are needed. Only applicable to ffmpeg backends
* use nanoseconds instead of seconds to mark the stream open time, and change the cap prop name to CAP_PROP_STREAM_OPEN_TIME_NSEC
* use microseconds for CAP_PROP_STREAM_OPEN_TIME (nanoseconds rolls over too soon, and milliseconds/seconds requires a division)
* fix whitespace issue
[G-API] Extend compileStreaming to support different overloads
* Make different overloads
* Order python compileStreaming overloads
* Fix compileStreaming bug
* Replace
gin -> descr_of
* Set error message
* Fix review comments
* Use macros for pyopencv_to GMetaArgs
* Use GAPI_PROP_RW
* Not split Prims python stuff
* Added exposure and gain props, maximized pixel clk
* removed pixel clock maximization
pixel clock maximization is not suitable for all use cases, so I removed it from PR.
* videoio/gstreamer: Add support for GRAY16_LE.
* videoio/gstreamer: added BGRA/BGRx support
Co-authored-by: Maksim Shabunin <maksim.shabunin@gmail.com>
docs(core/ocl): clarify ownership of arguments passed into OpenCL related functions
* docs(core/ocl): clarify ownership in OpenCLExecutionContext::create
Although it is technically true that OpenCLExecutionContext::create
calls `clRetainContext` on its context argument, it is misleading
because it does not increase the reference count overall. Clarify that
the ownership of one reference of the passed context and device is
taken.
* docs(core/ocl): document ownership transfer in ocl::Device::fromHandle
Optimization of DNN using native RISC-V vector intrinsics.
* Use RVV to optimize fastGEMM (FP32) in DNN.
* Use RVV to optimize fastGEMM1T in DNN.
* Use RVV to optimize fastConv in DNN.
* Use RVV to optimize fastDepthwiseConv in DNN.
* Vectorize tails using vl.
* Use "vl" instead of scalar to handle small block in fastConv.
* Fix memory access out of bound in "fastGEMM1T".
* Remove setvl.
* Remove useless initialization.
* Use loop unrolling to handle tail part instead of switch.
[G-API] Support postprocessing for not argmaxed outputs
* Support postprocessing for not argmaxed outputs
* Fix typo
* Add assert
* Remove static cast
* CamelCast to snake_case
* Fix windows warning
* Add static_cast to uint8_t
* Add const to variables
* Update config_reference.markdown
Added description for `WITH_CLP` build option.
* Added extra description
Can't cross-reference with anchors to other sections of the markdown file due to the presence of markdown link extension in the form of
`## Header {#id-of-header}`
* Fixed trailing space issue
bug fixes for universal intrinsics of RISC-V back-end
* Align universal intrinsic comparator behaviour with other platforms
Set all bits to one for return value of int and fp comparators.
* fix v_pack_triplets, v_pack_store and v_pack_u_store
* Remove redundant CV_DECL_ALIGNED statements
Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>
AArch64 semihosting
* [ts] Disable filesystem support in the TS module.
Because of this change, all the tests loading data will file, but tat
least the core module can be tested with the following line:
opencv_test_core --gtest_filter=-"*Core_InputOutput*:*Core_globbing.accuracy*"
* [aarch64] Build OpenCV for AArch64 semihosting.
This patch provide a toolchain file that allows to build the library
for semihosting applications [1]. Minimal changes have been applied to
the code to be able to compile with a baremetal toolchain.
[1] https://developer.arm.com/documentation/100863/latest
The option `CV_SEMIHOSTING` is used to guard the bits in the code that
are specific to the target.
To build the code:
cmake ../opencv/ \
-DCMAKE_TOOLCHAIN_FILE=../opencv/platforms/semihosting/aarch64-semihosting.toolchain.cmake \
-DSEMIHOSTING_TOOLCHAIN_PATH=/path/to/baremetal-toolchain/bin/ \
-DBUILD_EXAMPLES=ON -GNinja
A barematel toolchain for targeting aarch64 semihosting can be found
at [2], under `aarch64-none-elf`.
[2] https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-a/downloads
The folder `samples/semihosting` provides two example semihosting
applications.
The two binaries can be executed on the host platform with:
qemu-aarch64 ./bin/example_semihosting_histogram
qemu-aarch64 ./bin/example_semihosting_norm
Similarly, the test and perf executables of the modules can be run
with:
qemu-aarch64 ./bin/opecv_[test|perf]_<module>
Notice that filesystem support is disabled by the toolchain file,
hence some of the test that depend on filesystem support will fail.
* [semihosting] Remove blank like at the end of file. [NFC]
The spurious blankline was reported by
https://pullrequest.opencv.org/buildbot/builders/precommit_docs/builds/31158.
* [semihosting] Make the raw pixel file generation OS independent.
Use the facilities provided by Cmake to generate the header file
instead of a shell script, so that the build doesn't fail on systems
that do not have a unix shell.
* [semihosting] Rename variable for semihosting compilation.
* [semihosting] Move the cmake configuration to a variable file.
* [semihosting] Make the guard macro private for the core module.
* [semihosting] Remove space. [NFC]
* [semihosting] Improve comment with information about semihosting. [NFC]
* [semihosting] Update license statement on top of sourvce file. [NFC]
* [semihosting] Replace BM_SUFFIX with SEMIHOSTING_SUFFIX. [NFC]
* [semihosting] Remove double space. [NFC]
* [semihosting] Add some text output to the sample applications.
* [semihosting] Remove duplicate entry in cmake configuration. [NFCI]
* [semihosting] Replace `long` with `int` in sample apps. [NFCI]
* [semihosting] Use `configure_file` to create the random pixels. [NFCI]
* [semihosting][bugfix] Fix name of cmakedefine variable.
* [semihosting][samples] Use CV_8UC1 for grayscale images. [NFCI]
* [semihosting] Add readme file.
* [semihosting] Remove blank like at the end of README. [NFC]
This fixes the failure at
https://pullrequest.opencv.org/buildbot/builders/precommit_docs/builds/31272.
without rounding the composed image sizes (variable "sz") they will be odly fractions of a pixel (e.g. (5300.965, 3772.897)) and therefore cause a "TypeError: integer argument expected, got float" in line
456 roi = warper.warpRoi(sz, K, cameras[i].R)
MTCNN 1st pnet simplification to ensure single graph input
* 1st pnet simplification to ensure single graph input
* address comment from Dmitry M regarding unused variable
* [build][option] Introduce `OPENCV_DISABLE_THREAD_SUPPORT` option.
The option forces the library to build without thread support.
* update handling of OPENCV_DISABLE_THREAD_SUPPORT
- reduce amount of #if conditions
* [to squash] cmake: apply mode vars in toolchains too
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
G-API: Wrap render functionality to python
* Wrap render Rect prim
* Add all primitives and tests
* Cover mosaic and image
* Handle error in pyopencv_to(Prim)
* Move Mosaic and Rect ctors wrappers to shadow file
* Use GAPI_PROP_RW
* Fix indent
* Support cl_image conversion for CL_HALF_FLOAT (float16)
* Support cl_image conversion for additional channel orders:
CL_A, CL_INTENSITY, CL_LUMINANCE, CL_RG, CL_RA
* Comment on why cl_image conversion is unsupported for CL_RGB
* Predict optimal vector width for float16
* ocl::kernelToStr: support float16
* ocl::Device::halfFPConfig: drop artificial requirement for OpenCL
version >= 1.2. Even OpenCL 1.0 supports the underlying config
property, CL_DEVICE_HALF_FP_CONFIG.
* dumpOpenCLInformation: provide info on OpenCL half-float support
and preferred half-float vector width
* randu: support default range [-1.0, 1.0] for float16
* TestBase::warmup: support float16
G-API: Support vaargs for cv.compile_args
* Support cv.compile_args to work with variadic number of inputs
* Disable python2.x G-API
* Move compile_args to gapi pkg
- Reduce branch density by collapsing compares.
- Fix windows build errors
- Use OpenCV universal intrinsics
- Use v_check_any and v_signmask as requested
Function is validated. Included an update to DISABLED_Calib3d_InitInverseRectificationMap.
Includes updates per input from @alalek and unit test regression # to reflect PR #
1) Document GFrame/MediaFrame (and also other G-API types)
- Added doxygen comments for GMat, GScalar, GArray<T>, GOpaque classes;
- Documented GFrame and its host-side counterpart MediaFrame;
- Added some more notes to the data type classes.
2) Give @brief descriptions to most of the cv::gapi::* namespaces
3) Make some symbols private
- These structures are mainly internal and shouldn't be used directly
Update to initInverseRectificationMap()
* update to initInverseRectificationMap() documentation
* Restructured Calib3d_InitInverseRectificationMap unit test per feedback from alalek
* whitespace
G-API: Documentation for Params (IE and ONNX).
* Applying comments
* Removed type of model from PramsDesc
* Added message for onnx ParamDesc
* Whitespaces
* Review
* Fix comments to review
* Fix comments
Co-authored-by: Anatoliy Talamanov <anatoliy.talamanov@intel.com>
G-API: Extend MediaFrame to be able to extract additional info besides access
* Extend MediaFrame to be able to extract additional info besides access
* Add default implementation for blobParams()
* Add comment on the default blobParams()
Fix dynamic loading of clBLAS and clFFT (formerly, clAmdBlas and clAmdFft)
* Fix dynamic loading of clBLAS and clFFT
* Update filenames and function names for clBLAS (formerly, clAmdBlas)
* Update filenames and function names for clFFT (formerly, clAmdFft)
* Uncomment teardown of clFFT; tear down clFFT in same way as clBLAS
* Fix generators for clBLAS and clFFT headers
* Update generators to parse recent clBLAS and clFFT library headers
* Update generators to be compatible with Python 3
* Re-generate OpenCV's clBLAS and clFFT headers
* Update function calls to match names in newly generated headers
* Disable (and comment on) teardown code for clBLAS and clFFT
* Renaming *clamd* files
* Renaming *clamdblas* files to *clblas*
* Renaming *clamdfft* files to *clfft*
* Update generator for CL headers
* Update generator to be compatible with Python 3
Fixed trailing whitespace
Update to initInverseRectificationMap documentation for clarity
Added test case for initInverseRectificationMap()
Updated documentation.
Fixed whitespace error in docs
Small update to test function
Now passes success_error_level
final update to inverseRectification documentation
Fix Robertson Calibration NaN Bug
* add epsilon value for numerical stability in robertson merge
* update test to use range based for loop
* add comment to test
* move the epsilon
* address test comments
fix windows build warnings
fix vector type for tests
update tests
make threshold float
address test comments
fix tests and move epsilon again
* use scalar::all, move epsilon, and remove print
* Add the support for riscv64 vector 0.7.1.
* fixed GCC warnings
* cleaned whitespaces
* Remove the worning by the use of internal API of compiler.
* Update the license header.
* removed trailing whitespaces
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@me.com>
Co-authored-by: yulj <linjie.ylj@alibaba-inc.com>
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
* Adding functions rbegin() and rend() functions to matrix class.
This is important to be more standard compliant with C++ and an ever increasing number of people using standard algorithms for better code readability- and maintainability.
The functions are copy pated from their counterparts (even though they should probably call the counterparts but this gave me some troube).
They return iterators using std::reverse_iterators
Follow up of an open feature request:
https://github.com/opencv/opencv/issues/4641
* Fix rbegin() and rend() and provide tests for them
* Removing unnecessary whitespaces
* Adding rbegin and rend to Mat_ class with the right parameters so we don't need to repeat the template argument.
An instantiating cv::Mat_<int> for example can call it's rbegin() function and doesn't need rbegin<int>() with this convience addition.
Follows what is done for forward iterators
* static cast the vector size (return size_t) to an int (that is required for opencv mat constructor)
Co-authored-by: Stefan <stefan.gerl@tum.de>
G-API: New python operations API
* Reimplement test using decorators
* Custom python operation API
* Remove wip status
* python: support Python code in bindings (through loader only)
* cleanup, skip tests for Python 2.x (not supported)
* python 2.x can't skip unittest modules
* Clean up
* Clean up
* Fix segfault python3.9
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Fixes for Swift troubles
* Remove NS_SWIFT_NAME override for Point, Rect, and Size due to Darwin namespace conflict
* Fix swift_type overrides in objc generator
* Add backwards compatibility Swift typealiases for Point, Rect, Size
* Add disable-swift build option to iOS/macOS builds
* Add import directive to swift source when building with disable-swift
Co-authored-by: Chris Ballinger <cballinger@rightpoint.com>
G-API MTCNN demo hotfix to align overall pipeline accuracy with the reference Python code output.
* MTCNN G-API demo aligned with Python from OMZ
* clean up
* more comments from Maxim are addressed.
* address comment from Dmitry
* Added PaddlePaddle classification model conversion case
* Modify cv2 import as cv
* Modify documents in dnn_conversion/paddlepaddle
* Modify documents in dnn_conversion/paddlepaddle
this corrects bug #16592 where a Stream is created at
each GpuMat::load(arr,stream) call
a correct solution would have been to add a default to GpuMat::load
but due to circular dependence between Stream and GpuMat, this is not possible
add test_cuda_upload_download_stream to test_cuda.py
Support building with OpenEXR 3.x
* Support OpenEXR 3.0
Try to find OpenEXR 3.0 using the upstream cmake config, and fallback to the previous algorithm if not found
* Add explicit ImfFrameBuffer.h include
This was transitively included with OpenEXR 2.x, but that's no longer the case with OpenEXR 3.x
Stitching Detailed Tutorial Improvements
* Add Vertical Wave Correction
The user has the possibility to pass "vert" as wave_correct parameter. However, in the code "cv.detail.WAVE_CORRECT_HORIZ" ist fixed. This change proposes changes so that the wave correction is done vertically if the user passes "vert" as wave_correct parameter. The variable "do_wave_correct" is replaced by None which is passed to the variable "wave_correct" if the user chooses "no" for wave correction.
* Correct fixed conf_thresh
According to the documentation, [cv.detail.leaveBiggestComponent](https://docs.opencv.org/4.5.1/d7/d74/group__stitching__rotation.html#ga855d2fccbcfc3b3477b34d415be5e786) takes features, the pairwise_matches and the conf_threshold as input.
In the tutorial, however, conf_threshold is fixed at 0.3 even though the user can pass conf_thresh as parameter which is 1 by default. Fixing this parameter at 0.3 causes the script to include images into the panorama which are not part of it.
Add reading of specific images from multipage tiff
* Add reading of specific images from multipage tiff
* Fix build issues
* Add missing flag for gdal
* Fix unused param warning
* Remove duplicated code
* change public parameter type to int
* Fix warnings
* Fix parameter check
G-API MTCNN sample
* add face detection demo
* clean up
* enable back accumulate
* additional input
* meta args workaround
* additional arg
* add init
* roll back
* fix shadowing
* roll back
* clean up and PNet copy from debug branch which now works
* try nets operator
* more clean up
* more clean up
* add 6 layers pyramid experimental code
* final clean up and ready for PR
* original image resize
* Remove Pnet declarations. Generic infer is used now.
* scales and sizes calculation added
* fix assert, and add ceil to size calculation
* try doubles for scales
* Address comments from Dmitry.
* use half scale option
* fix half scale
* clean up debug outputs
* try to get input image width and height
* clean up
* trailing spaces and review from Maxim
* more comments from Maxim are addressed
* try to fix warnings
* try to fix warnings and address more comments from Dmitry
* crop fix and clean up
* more warnings fixes
* more warnings fixes
* more comments from Maxim are addressed
* even more consts
* copy_n for regressions
* address more comments from Dmitry
* more comments from Maxim
[G-API] Fix bug of GArray<GArray> passing through a graph
* Add test to check GArray<GArray> passing through a graph (assertion failed)
* G-API: Flatten GArray<T> to std::vector<T> when capturing VCtr
- Also: Fix formatting in garray.hpp
* Refactored test, added valuable check
* Initialize size_t
Co-authored-by: Dmitry Matveev <dmitry.matveev@intel.com>
* fix the perf tests of OpenCV.js so that it can run on Node.js successfully
* do not modify the CMakeLists.txt
Co-authored-by: lionkun <871518554@qq.com>
G-API: ONNX. Adding INT64-32 conversion for output.
* Added int64 to 32 conversion
* Added warning
* Added type checks for all toCV
* Added type checks for tests
* Small fixes
* Const for fixture in test
* std::tuple if retutn value for toCV
* Mistake
* Changed toCV for tests
* Added Assert
* Fix for comments
* One conversion for ONNX and IE
* Clean up
* One more fix
* Added copyFromONNX
* Removed warning
* Apply review comments
G-API: IE. Adding support for INT32 type.
* Added support for int32
* Added sample for semantic-segmentation-adas-0001
* Alignment
* Alignment 2
* Rstrt build
* Removed test for sem seg
ONNX diagnostic tool
* Final
* Add forgotten Normalize layer to the set of supported types
* ONNX diagnostic tool corrections
* Fixed CI test warnings
* Added code minor corrections
Co-authored-by: Sergey Slashchinin <sergei.slashchinin@xperience.ai>
[G-API]: Performance tests for KalmanFilter
* Kalman perf.tests and some tests refactoring
* Input generation moved to a separate function; Slowest case sneario testing added
* Generating refactored
* Generating refactoring
* Addressing comments
* Error Message for SURF if not implemented
In OpenCV 4.5.1
import cv2 as cv
cv.xfeatures2d_SURF.create
will not create an AttributeError, even if the function is excluded (no nonfree option)
In Line 305 (now 306) however ´finder = FEATURES_FIND_CHOICES[args.features]()´ will raise an
error: OpenCV(4.5.1) ..\opencv_contrib\modules\xfeatures2d\src\surf.cpp:1029: error: (-213:The function/feature is not implemented) This algorithm is patented and is excluded in this configuration; Set OPENCV_ENABLE_NONFREE CMake option and rebuild the library in function 'cv::xfeatures2d::SURF::create'
So we should check with cv.xfeatures2d_SURF.create() correctly if SURF is available
G-API: Implement async version for InferList & Infer2
* Implement async version for InferList & Infer2
* Fix warning
* Fix bug with roi ordering
* Post input meta instead of empty
* Fix comments to review
* Add Python Bindings for getCacheDirectory function
* Added getCacheDirectory interop test with image codecs.
Co-authored-by: Sergey Slashchinin <sergei.slashchinin@xperience.ai>
* Added CALIB_FIX_FOCAL_LENGTH to fisheye calibration #13450
Sometimes you want to calibrate just the principal point of a camera, or just the distortion coefficients. In this case, you can pass the CALIB_FIX_FOCAL_LENGTH flag to keep Fx and Fy
* Added test for CALIB_FIX_FOCAL_LENGTH option in fisheye callinration.
- to reduce binaries size of FFmpeg Windows wrapper
- MinGW linker doesn't support -ffunction-sections (used for FFmpeg Windows wrapper)
- move code to improve locality with its used dependencies
- move UMat::dot() to matmul.dispatch.cpp (Mat::dot() is already there)
- move UMat::inv() to lapack.cpp
- move UMat::mul() to arithm.cpp
- move UMat:eye() to matrix_operations.cpp (near setIdentity() implementation)
- move normalize(): convert_scale.cpp => norm.cpp
- move convertAndUnrollScalar(): arithm.cpp => copy.cpp
- move scalarToRawData(): array.cpp => copy.cpp
- move transpose(): matrix_operations.cpp => matrix_transform.cpp
- move flip(), rotate(): copy.cpp => matrix_transform.cpp (rotate90 uses flip and transpose)
- add 'OPENCV_CORE_EXCLUDE_C_API' CMake variable to exclude compilation of C-API functions from the core module
- matrix_wrap.cpp: add compile-time checks for CUDA/OpenGL calls
- the steps above allow to reduce FFmpeg wrapper size for ~1.5Mb (initial size of OpenCV part is about 3Mb)
[G-API] Introduce cv.gin/cv.descr_of for python
* Implement cv.gin/cv.descr_of
* Fix macos build
* Fix gcomputation tests
* Add test
* Add using to a void exceeded length for windows build
* Add using to a void exceeded length for windows build
* Fix comments to review
* Fix comments to review
* Update from latest master
* Avoid graph compilation to obtain in/out info
* Fix indentation
* Fix comments to review
* Avoid using default in switches
* Post output meta for giebackend
videoio: HW decode/encode in FFMPEG backend; new properties with support in FFMPEG/GST/MSMF
* HW acceleration in FFMPEG backend
* fixes on Windows, remove D3D9
* HW acceleration in FFMPEG backend
* fixes on Windows, remove D3D9
* improve va test
* Copyright
* check LIBAVUTIL_BUILD >= AV_VERSION_INT(55, 78, 100) // FFMPEG 3.4+
* CAP_MSMF test on .mp4
* .mp4 in test
* improve va test
* Copyright
* check LIBAVUTIL_BUILD >= AV_VERSION_INT(55, 78, 100) // FFMPEG 3.4+
* CAP_MSMF test on .mp4
* .mp4 in test
* .avi for GStreamer test
* revert changes around seek()
* cv_writer_open_with_params
* params.warnUnusedParameters
* VideoCaptureParameters in GStreamer
* open_with_params
* params->getUnused
* Reduce PSNR threshold 33->32 (other tests use 30)
* require FFMPEG 4.0+; PSNR 30 as in other tests
* GStreamer AVI-demux plugin not installed in Ubuntu test environment?
* fix build on very old ffmpeg
* fix build on very old ffmpeg
* fix build issues
* fix build issues (static_cast)
* FFMPEG built on Windows without H264 encoder?
* fix for write_nothing test on VAAPI
* fix warnings
* fix cv_writer_get_prop in plugins
* use avcodec_get_hw_frames_parameters; more robust fallback to SW codecs
* internal function hw_check_device() for device check/logging
* two separate tests for HW read and write
* image size 640x480 in encode test
* WITH_VA=ON (only .h headers used in OpenCV, no linkage dependency)
* exception on VP9 SW encoder?
* rebase master; refine info message
* videoio: fix FFmpeg standalone plugin build
* videoio(ffmpeg): eliminate MSVC build warnings
* address review comments
* videoio(hw): update videocapture_acceleration.read test
- remove parallel decoding by SW code path
- check PSNR against the original generated image
* videoio: minor fixes
* videoio(test): disable unsupported MSMF cases (SW and HW)
* videoio(test): update PSNR thresholds for HW acceleration read
* videoio(test): update debug messages
* "hw_acceleration" whitelisting parameter
* little optimization in test
* D3D11VA supports decoders, doesn't support encoders
* videoio(test): adjust PSNR threshold in write_read_position tests
* videoio(ffmpeg): fix rejecting on acceleration device name mismatch
* videoio(ffmpeg): fix compilation USE_AV_HW_CODECS=0, add more debug logging
* videoio: rework VideoAccelerationType behavior
- enum is not a bitset
- default value is backend specific
- only '_NONE' and '_ANY' may fallback on software processing
- specific H/W acceleration doesn't fallback on software processing. It fails if there is no support for specified H/W acceleration.
* videoio(test): fix for current FFmpeg wrapper
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
calib3d(usac): do not crash on empty models
* calib3d(test): regression test for issue 19639
* calib3d(usac): do not crash in setModelParameters()
* calib3d(usac): handle empty models in isModelGood()
[G-API] Support multiple asynchronous requests
* Support nireq option
* Disable tests to check CI
* Fix bug with hanging
* WA to green CI
* Snapshot
* Simplify RequestPool
* Add default values to id
* Fix win warning
[G-API]: Performance tests for kmeans
* - Perf.Tests for kmeans(2D, 3D (Point2f/3f), ND (Mat))
- New file for common parts of acc. and perf. tests for core kernels added
- Some typos corrections
* Applying comments
Android NDK camera support
* Add native camera video backend for Android
* In the event of a "No buffer available error" wait for the appropriate callback and retry
* Fix stale context when creating a new AndroidCameraCapture
* Add property handling
OpenEXR compression options
* Adding possibility to select the compression type for the OpenEXR format.
There are compression modes other than the default that are more suited for certain data. Mainly grainy/noisy data.
* Code review fixes.
Co-authored-by: Daniel Rydstrom <daniel.rydstrom@sick.se>
Render Frame NV12 on CPU
* render frame on CPU
* doxygen fix
* address review from Alexey
* comment fixes
* Address comments from Ruslan
* remove NV12 specific
* mat clone and more renaming
* misprint fix
* goodFeaturesToTrack returns also corner value
(cherry picked from commit 4a8f06755c)
* Added response to GFTT Detector keypoints
(cherry picked from commit b88fb40c6e)
* Moved corner values to another optional variable to preserve backward compatibility
(cherry picked from commit 6137383d32)
* Removed corners valus from perf tests and better unit tests for corners values
(cherry picked from commit f3d0ef21a7)
* Fixed detector gftt call
(cherry picked from commit be2975553b)
* Restored test_cornerEigenValsVecs
(cherry picked from commit ea3e11811f)
* scaling fixed;
mineigen calculation rolled back;
gftt function overload added (with quality parameter);
perf tests were added for the new api function;
external bindings were added for the function (with different alias);
fixed issues with composition of the output array of the new function (e.g. as requested in comments) ;
added sanity checks in the perf tests;
removed C API changes.
* minor change to GFTTDetector::detect
* substitute ts->printf with EXPECT_LE
* avoid re-allocations
Co-authored-by: Anas <anas.el.amraoui@live.com>
Co-authored-by: amir.tulegenov <amir.tulegenov@xperience.ai>
[G-API] Introduce GOpaque and GArray for python
* Introduce GOpaque and GArray for python
* Fix ctor
* Avoid code duplication by using macros
* gapi: move Python-specific files to misc/python
* Fix windows build
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Return accumulator value in HoughLines algorithm
* try to solve #17050
use cv_wrap_as
add python test
parameters
* review
* move wrapper to imgproc/bindings.hpp
G-API: ONNX. Support for networks with three dimensional input.
* Padding without tests
* Removed padding
* Some small fixes
* Added wstring_convert
* Alignment fix, m b
* Small fixes
* Moved include from onnx.hpp
VideoCapture/DSHOW : Allow to set CAP_PROP_CONVERT_RGB before FOURCC/FPS/CHANNEL/WIDTH/HEIGHT.
* 🐛 cap_dshow : Allow to set CAP_PROP_CONVERT_RGB before FOURCC/FPS/CHANNEL
* 🐛 cap_dshow : fix g_VI.setConvertRGB not being called with correct boolean value on first property set.
* ✅ cap_dshow : Test CAP_PROP_CONVERT_RGB persistence
* 🚨 Fix cast from bool to double
* 🚨 Fix trailing whitespace
add video capture parameters
* add parameters
* videoio: revert unnecessary massive changes
* videoio: support capture parameters in backends API
- add tests
- FFmpeg backend sample code
- StaticBackend API is done
- support through PluginBackend API will be added later
Co-authored-by: Milashchenko <maksim.milashchenko@intel.com>
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Add DaSiamRPN tracker sample of c++ version
* add sample dasiamrpn_tracker of c++ version.
* samples(dasiamrpn_tracker.cpp): apply clang-format
- exclude "keys" variable
* samples(dasiamrpn_tracker.cpp): coding style and UX fixes
[G-API]: Performance tests for fitLine and findContours
* Perf.Test for findContours(H)
* Perf.Test for fitLine(2D.3D;Mat,vector<Point2i/2f/2d/3i/3f/3d>)
* Reducing the template specializations number
* Applying comments
Conv1D and Pool1D for CUDA backend
* CUDA-independent changes
* Add Conv1D and Pool1D for CUDA backend
* CUDA-independent changes
* Fix typo
* fix comment
* Update fix
* make changes more correct for pooling layer
* Minor fixes for review
* Split skip blocks
- migrate GStreamer backed
- migrate FFmpeg backend (with switch on legacy API)
- cv_videoio_capture_retrieve_cb_t uses Mat type instead of number of channels
[G-API]: Performance tests for boundingRect
* Update boundingRect() tests with the changes from fitLine() PR
* Add performance tests for boundingRect
* Applying comment about g_type_of_t
* Addressing comments
* Addressing comment: replace cmp_f by CompareF in perf.tests + add the default constructor for CompareF
* Fix typo
G-API: Support GFrame for ONNX infer
* Added GFrame for ONNX
* Cut test
* Removed IE from assert
* Review comments
* Added const/bbot rstrt
* View instead unique_ptr in func. sig.
* Added extractMat function, ONNXCompiled contains exMat - cv::Mat with non processed input data
* Added meta check for inferList2
* implements https://github.com/opencv/opencv/issues/19147
* CAUTION: this PR will only functions safely in the
4+ branches that already include PR 19029
* CAUTION: this PR requires thread-safe startup of the alloc.cpp
translation unit as implemented in PR 19029
Make xcframework output path argument explicit and required
* Make output path argument explicit and required
* Improve xcframework documentation
* Add TODOs for future breaking changes on build_framework.py scripts
[G-API] Support GFrame for infer
* GInfer(GFrame), currently broken
* Fixed (API only)
* Support GFrame in GIEBackend
* Fix comments to review
* Fix comments to review
* Fix doxygen
* Fix building with different IE versions
* Fix warning on MacOS
Co-authored-by: Dmitry Matveev <dmitry.matveev@intel.com>
Co-authored-by: Smirnov Alexey <alexey.smirnov@intel.com>
add thread-safe startup of fastMalloc and fastFree
* add perf test core memory allocation
* fix threading in isAlignedAllocationEnabled()
* tweaks requested by maintainer
Add CV_16UC1/GRAY16_LE support to GStreamer backend for VideoWriter
* videoio(backend): add Writer_open_with_params to plugin API
This will allow arbitrary parameters to be passed to plugin backends
* videoio(gstreamer): add GRAY16_LE/CV_16UC1 writing support to GStreamer
This introduces a new property VIDEOWRITER_PROP_DEPTH, which defaults to
CV_8U, but for GStreamer can be set to CV_16U.
Also, fix another test to not fail if plugin isn't found, copying logic
from the read_write test.
* videoio(plugin): fix handling plugins with previous API level
* videoio: coding style
* fix warning
[GSoC] High Level API and Samples for Scene Text Detection and Recognition
* APIs and samples for scene text detection and recognition
* update APIs and tutorial for Text Detection and Recognition
* API updates:
(1) put decodeType into struct Voc
(2) optimize the post-processing of DB
* sample update:
(1) add transformation into scene_text_spotting.cpp
(2) modify text_detection.cpp with API update
* update tutorial
* simplify text recognition API
update tutorial
* update impl usage in recognize() and detect()
* dnn: refactoring public API of TextRecognitionModel/TextDetectionModel
* update provided models
update opencv.bib
* dnn: adjust text rectangle angle
* remove points ordering operation in model.cpp
* update gts of DB test in test_model.cpp
* dnn: ensure to keep text rectangle angle
- avoid 90/180 degree turns
* dnn(text): use quadrangle result in TextDetectionModel API
* dnn: update Text Detection API
(1) keep points' order consistent with (bl, tl, tr, br) in unclip
(2) update contourScore with boundingRect
Add option for NMS for boxes with different labels
* DetectionModel impl
* Add option for NMS for boxes with different labels
In the detect function in modules/dnn/include/opencv2/dnn/dnn.hpp, whose implementation can be found at modules/dnn/src/model.cpp, the Non Max Suppression (NMS) is applied only for objects of the same label. Thus, a flag
was added with the purpose to allow developers to choose if they want to keep the default implementation or wether they would like NMS to be applied to all the boxes, regardless of label.
The flag is called nmsDifferentLabels, and is given a default value of false, which applies the current default implementation, thus allowing existing projects to update opencv without disruption
Solves issue opencv#18832
* Change return type of set & Add default constr
* Add assertions due to default constructor
The test has race condition, which is addressed by the patch.
The race is next:
Master thread is calling execute (effectively blocked, waiting for
callback to be called)
"Async" thread picks up the callback
Call the callback
Then sets the variables in test
After call back is called, master thread is unblocked and may check
the variables (set in point 4 by the "async" thread) earlier then they
actually changed
Changes:
callback should be called as the last step (after flag variables are
set), as it effectively unblock the master thread
fixes#18974
- explicitly declared default constructor
- made initilizer_list constructor to accept the list by copy
-- as it is more canonical (and as copying the initializer_list does
not force copy of the list items)
-- current version anyway does not do what it is intended to
[G-API]: kmeans() Standard Kernel Implementation
* cv::gapi::kmeans kernel implementation
- 4 overloads:
- standard GMat - for any dimensionality
- GMat without bestLabels initialization
- GArray<Point2f> - for 2D
- GArray<Point3f> - for 3D
- Accuracy tests:
- for every input - 2 tests
1) without initializing. In this case, no comparison with cv::kmeans is done as kmeans uses random auto-initialization
2) with initialization
- in both cases, only 1 attempt is done as after first attempt kmeans initializes bestLabels randomly
* Addressing comments
- bestLabels is returned to its original place among parameters
- checkVector and isPointsVector functions are merged into one, shared between core.hpp & imgproc.hpp by placing it into gmat.hpp (and implementation - to gmat.cpp)
- typos corrected
* addressing comments
- unified names in tests
- const added
- typos
* Addressing comments
- fixed the doc note
- ddepth -> expectedDepth, `< 0 ` -> `== -1`
* Fix unsupported cases of input Mat
- supported: multiple channels, reversed width
- added test cases for those
- added notes in docs
- refactored checkVector to return dimentionality along with quantity
* Addressing comments
- makes chackVector smaller and (maybe) clearer
* Addressing comments
* Addressing comments
- cv::checkVector -> cv::gapi::detail
* Addressing comments
- Changed checkVector: returns bool, quantity & dimensionality as references
* Addressing comments
- Polishing checkVector
- FIXME added
* Addressing discussion
- checkVector: added overload, separate two different functionalities
- depth assert - out of the function
* Addressing comments
- quantity -> amount, dimensionality -> dim
- Fix typos
* Addressing comments
- fix docs
- use 2 variable's definitions instead of one (for all non-trivial variables)
* TBB executor for GAPI
- the sole executor
- unit tests for it
- no usage in the GAPI at the momnet
* TBB executor for GAPI
- introduced new overload of execute to explicitly accept tbb::arena
argument
- added more basic tests
- moved arena creation code into tests
-
* TBB executor for GAPI
- fixed compie errors & warnings
* TBB executor for GAPI
- split all-in-one execute() function into logicaly independant parts
* TBB executor for GAPI
- used util::variant in in the tile_node
* TBB executor for GAPI
- moved copy_through_move to separate header
- rearranged details staff in proper namespaces
- moved all implementation into detail namespace
* TBB executor for GAPI
- fixed build error with TBB 4.4.
- fixed build warnings
* TBB executor for GAPI
- aligned strings width
- fixed spaces in expressions
- fixed english grammar
- minor improvements
* TBB executor for GAPI
- added more comments
- minor improvements
* TBB executor for GAPI
- changed ITT_ prefix for macroses to GAPI_ITT
* TBB executor for GAPI
- no more "unused" warning for GAPI_DbgAssert
- changed local assert macro to man onto GAPI_DbgAssert
* TBB executor for GAPI
- file renamings
- changed local assert macro to man onto GAPI_DbgAsse
* TBB executor for GAPI
- test file renamed
- add more comments
* TBB executor for GAPI
- minor clenups and cosmetic changes
* TBB executor for GAPI
- minor clenups and cosmetic changes
* TBB executor for GAPI
- changed spaces and curly braces alignment
* TBB executor for GAPI
- minor cleanups
* TBB executor for GAPI
- minor cleanups
Support XCFramework builds, Catalyst
* Early work on xcframework support
* Improve legibility
* Somehow this works
* Specify ABIs in a place where they won't get erased
If you pass in the C/CXX flags from the Python script, they won't be respected. By doing it in the actual toolchain, the options are respected and Catalyst successfully links.
* Clean up and push updates
* Actually use Catalyst ABI
Needed to specify EXE linker flags to get compiler tests to link to the Catalyst ABIs.
* Clean up
* Revert changes to common toolchain that don't matter
* Try some things
* Support Catalyst build in OSX scripts
* Remove unnecessary iOS reference to AssetsLibrary framework
* Getting closer
* Try some things, port to Python 3
* Some additional fixes
* Point Cmake Plist gen to osx directory for Catalyst targets
* Remove dynamic lib references for Catalyst, copy iOS instead of macos
* Add flag for building only specified archs, remove iOS catalyst refs
* Add build-xcframework.sh
* Update build-xcframework.sh
* Add presumptive Apple Silicon support
* Add arm64 iphonesimulator target
* Fix xcframework build
* Working on arm64 iOS simulator
* Support 2.7 (replace run with check_output)
* Correctly check output of uname_m against arch
* Clean up
* Use lipo for intermediate frameworks, add python script
Remove unneeded __init__.py
* Simplify python xcframework build script
* Add --only-64-bit flag
* Add --framework-name flag
* Document
* Commit to f-strings, improve console output
* Add i386 to iphonesimulator platform in xcframework generator
* Enable objc for non-Catalyst frameworks
* Fix xcframework builder for paths with spaces
* Use arch when specifying Catalyst build platform in build command
* Fix incorrect settings for framework_name argparse configuration
* Prefer underscores instead of hyphens in new flags
* Move Catalyst flags to where they'll actually get used
* Use --without=objc on Catalyst target for now
* Remove get_or_create_folder and simplify logic
* Remove unused import
* Tighten up help text
* Document
* Move common functions into cv_build_utils
* Improve documentation
* Remove old build script
* Add readme
* Check for required CMake and Xcode versions
* Clean up TODOs and re-enable `copy_samples()`
Remove TODO
Fixup
* Add missing print_function import
* Clarify CMake dependency documentation
* Revert python2 change in gen_objc
* Remove unnecessary builtins imports
* Remove trailing whitespace
* Avoid building Catalyst unless specified
This makes Catalyst support a non-breaking change, though defaults should be specified when a breaking change is possible.
* Prevent lipoing for the same archs on different platforms before build
* Rename build-xcframework.py to build_xcframework.py
* Check for duplicate archs more carefully
* Prevent sample copying error when directory already exists
This can happen when building multiple architectures for the same platform.
* Simplify code for checking for default archs
* Improve build_xcframework.py header text
* Correctly resolve Python script paths
* Parse only known args in ios/osx build_framework.py
* Pass through uncaptured args in build_xcframework to osx/ios build
* Fix typo
* Fix typo
* Fix unparameterized build path for intermediate frameworks
* Fix dyanmic info.plist path for catalyst
* Fix utf-8 Python 3 issue
* Add dynamic flag to osx script
* Rename platform to platforms, remove armv7s and i386
* Fix creation of dynamic framework on maccatalyst and macos
* Update platforms/apple/readme.md
* Add `macos_archs` flag and deprecate `archs` flag
* Allow specification of archs when generating xcframework from terminal
* Change xcframework platform argument names to match archs flag names
* Remove platforms as a concept and shadow archs flags from ios/osx .py
* Improve documentation
* Fix building of objc module on Catalyst, excluding Swift
* Clean up build folder logic a bit
* Fix framework_name flag
* Drop passthrough_args, use unknown_args instead
* minor: coding style changes
Co-authored-by: Chris Ballinger <cballinger@rightpoint.com>
Expose CGImage <-> Mat conversion for iOS platforms
* Add apple_conversions to framework builds
This exposes CGImage <-> Mat conversion.
* Export Mat <-> CGImage methods on iOS targets
* Add CGImage converters to iOS objc helper class
* Add CF_RETURNS_RETAINED annotations to methods returning CGImageRef
Ordinary quaternion
* version 1.0
* add assumeUnit;
add UnitTest;
check boundary value;
fix the func using method: func(obj);
fix 4x4;
add rodrigues vector transformation;
fix mat to quat;
* fix blank and tab
* fix blank and tab
modify test;cpp to hpp
* mainly improve comment;
add rvec2Quat;fix toRodrigues;
fix throw to CV_Error
* fix bug of quatd * int;
combine hpp and cpp;
fix << overload error in win system;
modify include in test file;
* move implementation to quaternion.ini.hpp;
change some constructor to createFrom* function;
change Rodrigues vector to rotation vector;
change the matexpr to mat of 3x3 return type;
improve comments;
* try fix log function error in win
* add enums for assumeUnit;
improve docs;
add using std::cos funcs
* remove using std::* from header;
add std::* in affine.hpp,warpers_inl.hpp;
* quat: coding style
* quat: AssumeType => QuatAssumeType
G-API: ONNX. Support tensor input for CNN with dynamic input
* Added support for dynamic input tensor, refactored one input/output tests
* Added multiple input/output fixture, test for mobilenet
* Removed whitespace
* Removed mistake in inferROI
* Small fixes
* One more fix
* Code cleanup
* Code cleanup X2
* bb rstrt
* Fix review comments
* One more fix review comments
* Mistake
uEye are cameras from IDS, c.f. https://en.ids-imaging.com/
Supports driver version 4.94 and up currently, since the event system was overhauled there.
Supports setting/getting the properties: fps,width,height
[G-API]: findContours() and boundingRect() Standard Kernels Implementation
* Add findContours() standard kernel
- API and documentation provided:
- as OpenCV provides two overloads whether to calculate hierarchy or not, but they differ by only the output in sight of G-API, two different G-API functions and kernels implemented
- G-API Imgproc documentation divided into more parts according to imgproc module parts
- some typos connected with division into parts corrected
- `GArray<GArray<U>>` overload for `get_out` function provided to coonvert correctly into `vector<vector<U>>`
- OCV backend supported
- accuracy tests provided
* Add boundingRect() standard kernel
- API and documentation provided:
- GOpaque<Rect> used as an output
- as OpenCV provides two possibilities whether to take a gray-scale image or a set of 2D points (`Point2i` or `Point2f` supported), three different overloads of a single G-API function and three kernels implemented
- for a gray-scale image the overload via `GMat`
- for a set of `Point2i` - the one via GArray<`Point2i`>
- set of `Point2f` -> GArray<`Point2f`>
- OCV backend supported
- accuracy tests provided
- comparison function for Rects provided
- some typos in `gapi_tests_common` corrected
* Fix precommit windows warnings
* - Addressing comments:
- split tests
- Fix Windows warnings
* Static_cast for warnings
* - Remove randomness
- Fix unnecessary precision losses
* - Forgot reference for RNG
* addressing comments
* equalizeHist -> no group
* `const` addedin new functions
* Address suggestions:
- Hierarchical -> H
- added cv::GMatDesc::isVectorPoins()
- added support of giving a set of points to boundingRect()
* Addressing comments
- IoU comparison function added for Rects
- isPointsVector moved from a GMatDesc method to a separate function in imgproc.hpp
- enums instead of int
- typos corrected
* Addressing comments
- findContours: Point offset -> GOpaque<Point>
- removed "straight" comparison for Rects, IoU available only
- changed vectors initialization -> fix Debug test run
- Some typos
* added comment for later upgrades
* Fix not to corrupt docs by FIXME
* Addressing commens
- overload without offset added (as a temporary workaround)
- checkMetaForFindingContours -> validateFindingContoursMeta
- added ostream overload for enums used in tests
[G-API]: morphologyEx() Standard Kernel Implementation
* cv::gapi::morphologyEx() kernel
- implemented (without separate 3x3 version)
- tests added: check only different operations, not kernels/borders
* Address comments: add `const` where needed
* Replaced fundamental tyeps -> enums where needed
- added operator<< overload for cv::MorphTypes for tests output
* G-API: Introduce ONNX backend for Inference
- Basic operations are implemented (Infer, -ROI, -List, -List2);
- Implemented automatic preprocessing for ONNX models;
- Test suite is extended with `OPENCV_GAPI_ONNX_MODEL_PATH` env for test data
(test data is an ONNX Model Zoo repo snapshot);
- Fixed kernel lookup logic in core G-API:
- Lookup NN kernels not in the default package, but in the associated
backend's aux package. Now two NN backends can work in the same graph.
- Added Infer SSD demo and a combined ONNX/IE demo;
* G-API/ONNX: Fix some of CMake issues
Co-authored-by: Pashchenkov, Maxim <maxim.pashchenkov@intel.com>
Expand ie::Params to support config
* Add config to IE params
* Add test
* Remove comments from tests
* Rename to pluginConfig
* Add one more overloads for pluginConfig
* Add more tests
Set queue size = 1 to Copy island right after the desync.
In this case, Copy won't read more data from a "last_written"
container than required, while feeding the desynchronized path.
Sometimes Copy don't get fused into an island and behaves
on its own -- in this case, it reads more data in advance
so the slow (desync) part actually processes some data in-sync
(more than actually required)
- cv::gapi::serialize bypasses compile arguments which have no S11N specialization with serialize/deserialize callbacks for underlying types
- cv::gapi::deserialize can accept arbitraty number of serialized compile args in a stream but will return only those which are requested by user via template parameter pack if they are presented in the stream. If some or all of them are not presented cv::gapi::deserialize will ignore and return only those which are presented
- cv::gapi::deserialize can accept only types which can be deserialized (have S11N<T> specialization with the user callbacks)
- Added cv::gapi::s11n::detail::has_S11N_spec<T> trait to separate compile arguments which have S11N<T> specialization with the user callbacks
- desync() is a new (and for now, the only one) intrinsic
which splits the graph execution into asynchronous parts
when running in Streaming mode;
- desync() makes no effect when compiling in Traditional mode;
- Added tests on desync() working in various scenarios;
- Extended GStreamingExecutor to support desync(); also extended
GStreamingCompiled() with a new version of pull() returning a
vector of optional values;
- Fixed various issues with storing the type information & proper
construction callbacks for GArray<> and GOpaque;
- Introduced a new infer(Roi,GMat) overload with a sample;
- Introduced an internal API for Islands to control fusion
procedure (to fuse or not to fuse);
- Introduced handleStopStream() callback for island executables;
- Added GCompileArgs to metadata of the graph (required for other
features).
- Changed descr_of(RMat) to use canDescribeHelper to correctly handle planar case
- Added export of createMat
- Added setting of Storage::INPUT and Storage::OUTPUT in deserialization routine of GComputation
Add support for Swift version independence
* Build for distribution (Swift version independence) when new Xcode build system is available
* Add module map and set "Defines Modules" flag
* support similarity masks
* add test for similarity threshold
* short license in test
* use UMat in buildSimilarityMask
* fix win32 warnings
* fix test indentation
* fix umat/mat sync
* no in-place argument for erode/dilate
* add HEVC(H.265) codec to iOS,Mac VideoWriter
* Update cap_avfoundation_mac.mm
add CV_FOURCC('h','v','c','1') for HEVC codec
* Update cap_avfoundation.mm
add CV_FOURCC('h','v','c','1') for HEVC codec
* feat: add availability check for HEVC codec on iOS and OS X
Co-authored-by: Vadim Levin <vadim.levin@xperience.ai>
GAPI: Addition new Color conversion kernels to CPU backend.
* Add BGR2RGB kernel to CPU backend
* Add BGR2I420 and RGB2I420 kernels to CPU backend
* Add I4202BGR and I4202RGB kernels to CPU backend
[GAPI] RMat integration into the framework
* RMat integration
* Added initialization of input mat in GArray initialization tests
* Fixed klocwork warnings in RMat tests, changed argument order in EXPECT_EQ
A running GMainLoop processes many events on the GLib/GStreamer
world. While some things may work without it, many others wont.
Examples of these are signals, timers and many other source
events. The problem becomes more concerning by the fact that
some GStreamer elements rely on signals to work.
This commit allows the user to specify an OpenCV option to
start a main loop, if needed. Since the loop blocks, this is
done in a separate thread.
[G-API] Export a part of serialization interface
* Initial stub
* Add test on serialization of a custom type
* Namespaces rework
* Fix isSupported in test struct
* Fix clang build and rework namespaces
* Remove redundant header
[G-API]: countNonZero() Standard Kernel Implementation
* Add countNonZero() standard kernel
- API and documentation provided
- OCV backend supported
- accuracy and performance tests provided
- some refactoring of related documentation done
* Fix GOpaque functionality for OCL Backend
- test for OCL Opaque usage providied
* countNonZero for GPU
- OCL Backend implementation for countNonZero() added
- tests provided
* Addressing comments
[G-API] Add support for more types serialization
* Support more types
* Add std::string support
* Fix GOpaque and gin interaction
* Fix tests on kind
* Make map serialization support templates and add tests on kind
Update G-API slides to OpenCV 4.4
* G-API: Updated slides to v4.4 (+ sample)
* Slight formatting changes + Python API page
* Some more updates to slides:
- Added more info on 4.2 and 4.4 versions
- Added explanation on Operations and their functional wrappers
* G-API: Make GFrame a new (distinct) G-type, not an alias to GMat
- The underlying host type is still cv::Mat, a new cv::MediaFrame
type is to be added as a separate PR
* Fix warnings and review comments
- Somewhow there was a switch() without a default: clause in Fluid
[G-API]: Add Fluid bitwise operations implementation for (GMat, GScalar)
* Added Fluid `bitwise` with `Scalar` + acc.tests
- simple loop implementation for Fluid used (no `hal`);
- `Scalar` is casted to `int` in the beginning
- tests just modified to work with `Scalar`
- expected output in operators' tests fixed (operators can't change Mat's depth)
- `float` `Scalar` `RNG` added, `RNG` reworked (`time` is used now), initialization of test fixtures reworked
- if input or output is `float` Scalar is initialized by `float`
- some problems with Fluid/OCV floating-point comparison difference stashed by `AbsSimilarPoints()` usage, FIXME added
- divide-by-zero is now fixed differently and everywhere
* - Added perf_tests for bitwise_Scalar operations
- due to errors of Fluid floating-point comparison operations, added support of different validation in Cmp perf_tests; added FIXME
- reworked integral initialization of Scalar
* Addressing comments
- NULL -> nullptr
- Scalar convertion moved to the function
- avoid -> avoiding
* Addressing comments
* CV_assert -> GAPI_assert
* Addressed DM comments
- refactored convertScalarForBitwise()
- removed unnecessary braces for switch
* Changed the operators tests
- switch via `enum` implemented
- infrastructure for that refactored
[G-API]: Add four kernels to parse NN outputs & provide information in Streaming scenarios
* Kernels from GL "blue" branch, acc and perf tests
* Code cleanup
* Output fix
* Comment fix
* Added new file for parsers, stylistic corrections
* Added end line
* Namespace fix
* Code cleanup
* nnparsers.hpp moved to gapi/infer/, nnparsers -> parsers
* Removed cv:: from parsers.hpp
[G-API]: Add GArray initialization support
* Added GArray initialization (CONST_VALUE, GScalar analog) and test for this
* Whitespaces
* And one more space
* Trailing whitespace
* Test name changed. Build with magic commands.
* GArray works with rvalue initialization
* Code cleanup
* Ternary operator in the initialization list.
[G-API]: Relocation of operators' overloads
* Relocates overloaded operators for `cv::GMat` and `cv::GScalar` to `cv::` namespace
- adds test to check usage of operators compilation
* Add tests for all the operators
* Address comments
* Universal Build for Big Sur
* Refactor MacOS/iOS build to only ever build one architecture at a time + improve code readability
* Workaround for CMake issue 20989
Remove obsolete FFMPEG versions support
* refactor: removed obsolete FFMPEG version support
- Oldest available version via official FFMPEG repository mirror has tag v.0.5
LIBAVFORMAT version for this tag is 52.31.0
* refactor: prefer std::min function to MIN macro
* refactor: use appropriate macro instead of manual version calculation
* refactor: remove macros for versions prior 0.5.15 release
* refactor: remove libavcodec macros for versions < 54.35.1 (default to Ubuntu 14.04)
* refactor: remove libavformat macro for versions < 54.20.4 (default ubuntu 14.04)
* refactor: remove libavutil macro for versions < 52.3.0 (default ubuntu 14.04)
* refactor: remove missed macros for libavcodec and libavformat
* refactor: remove unused _opencv_ffmpeg_free function
* build: add FFMPEG libraries versions checks
- Add verbose message about what FFMPEG libraries are missing.
- Add minimal versions check set to libav 9.20 release (default ubuntu 14.04) and FFMPEG 1.1.16 release.
If the check is failed CMake produces user-friendly message instead of build error.
* fix: libavcodec version guard for AVDISCARD_NONINTRA
* fix: libav check of libavcodec version guard for AVDISCARD_NONINTRA
* fix: version check for AV_CODEC_FLAG_GLOBAL_HEADER
* fix: missing FFMPEG libraries output
[G-API]: Fluid Core kernels performance tests
* Add performance tests for a list of Fluid Core kernels
* Update gapi_core_perf_tests_fluid.cpp
Addressing a comment
changed OpenCV license from BSD to Apache 2 license
* as discussed and announced earlier, changed OpenCV license from BSD to Apache 2. Many files still contain old-style copyrights though
* changed wording a bit; preserve the original OpenCV BSD license
* Fix trees parsing behavior in hierarchical_clustering_index:
Before, when maxCheck was reached in the first descent of a tree, time was still wasted parsing
the next trees till their best leaf, just to skip the points stored there.
Now we can choose either to keep this behavior, and so we skip parsing other trees after reaching
maxCheck, or we choose to do one descent in each tree, even if in one tree we reach maxCheck.
* Apply the same change to kdtree.
As each leaf contains only 1 point (unlike hierarchical_clustering), difference is visible if trees > maxCheck
* Add the new explore_all_trees parameters to miniflann
* Adapt the FlannBasedMatcher read_write test to the additional search parameter
* Adapt java tests to the additional parameter in SearchParams
* Fix the ABI dumps failure on SearchParams interface change
* Support of ctor calling another ctor of the class is only fully supported from C+11
- Added cross compile cmake file for target riscv64-clang
- Extended cmake for RISC-V and added instruction checks
- Created intrin_rvv.hpp with C++ version universal intrinsics
* added depth-wise convolution; gives ~20-30% performance improvement in MobileSSD networks
* hopefully, eliminated compile warnings, errors, as well as failure in one test
* * fixed a few typos
* decreased buffer size in some cases
* added more optimal im2row branch in the case of 1x1 convolutions
* tuned fastConv to reduce the number of passes over arrays
* add findEssentialMat for two different cameras
* added smoke test for the newly added variant of findEssentialMatrix
Co-authored-by: tompollok <tom.pollok@gmail.com>
* Implement G-API python bindings
* Fix hdr_parser
* Drop initlization with brackets using regexp
* Handle bracket initilization another way
* Add test for core operations
* Declaration and definition of View constructor now in different files
* Refactor tests
* Remove combine decorator from tests
* Fix comment to review
* Fix test
* Fix comments to review
* Remove GCompilerArgs implementation from python
Co-authored-by: Pinaev <danil.pinaev@intel.com>
* Added overload for `GArray<GMat>` ProtoParam in `gtyped.hpp`
* Tests+compile_args
- added tests for GArray<GMat> as an input and an output of GComputationT
- added possibility to give the compile_args to GComputationT.apply()
* Fix win errors
GAPI: Migration to IE Core API
* Migration to IE Core API
- both versions are maintained
- checked building with all the OpenVINO versions (2019.R1, R2, R3, 2020.4 (newest))
* commit to awake builders
* Addressing comments
- migrated to Core API in 'gapi_ie_infer_test.cpp'
- made Core a singleton object
- dropped redundant steps
* Addressing comments
- modified Mutex locking
* Update
* Addressing comments
- remove getInitMutex()
- reduce amount of #ifdef by abstracting into functions
* return to single IE::Core
* Divide functions readNet and loadNet to avoid warnings on GCC
* Fix deprecated code warnings
* Fix deprecated code warnings on CMake level
* Functions wrapped
- All the functions depended on IE version wrapped into a cv::gapi::ie::wrap namesapace
- All this contained to a new "giebackend/gieapi.hpp" header
- The header shared with G-API infer tests to avoid code duplications
* Addressing comments
- Renamed `gieapi.hpp` -> `giewrapper.hpp`, `cv::gapi::ie::wrap` -> `cv::gimpl::ie::wrap`
- Created new `giewrapper.cpp` source file to avoid potential "multiple definition" problems
- removed unnecessary step SetLayout() in tests
* Enabling two NN infer teest
* Two-NN infer test change for CI
- deleted additional network
- inference of two identical NN used instead
* Fix CI fileNotFound
* Disable MYRIAD test not to fail Custom CI runs
[G-API] Allow building graphs with a dynamic number of inputs and outputs
* Add dinamic graph feature and tests
* Remove unnecessary file
* Review response
* Add implementation of operator += for GRunArgs
And test for that case
* Tests refactoring
* Add doxygen
Review response
* Fix docs
* A small documentation fix
* Review response
* Add tests for more entities
* Add typed tests
* Another typed tests
* Doc fix
* Documentation fix
* Build fix
* Commit for rebuild
* The last one
* G-API: Introduce a new gapi::infer2 overload + gaze estimation sample
* G-API/infer2: Introduced static type checking for infer2
- Also added extra tests on the type check routine
* G-API/infer2: Addressed self-review comments in the sample app
- Also fix build on Linux;
* G-API/infer2: Remove incorrect SetLayout(HWC) + dead code
- Also fixed comments in the backend
* G-API/infer2: Continue with self-review
- Fix warnings/compile errors in gaze estimation
- Dropped the use of RTTI (VectorRef::holds()) from the giebackend
- Replaced it with a trait-based enums for GArray<T> and std::vector<T>
- The enums and traits are temporary and need to be unified with
the S11N when it comes
* G-API/infer2: Final self-review items
- Refactored ROIList test to cover 70% for infer<> and infer2<>;
- Fixed the model data discovery routine to be compatible with new
OpenVINO;
- Hopefully fixed the final issues (warnings) with the sample.
* G-API/infer2: address review problems
- Fixed typo in comments;
- Fixed public (Doxygen) comment on GArray<GMat> input case for infer2;
- Made model lookup more flexible to allow new & old OMZ dir layouts.
* G-API/infer2: Change the model paths again
* G-API/infer2: Change the lookup path for test data
* G-API/infer2: use randu instead of imread. CI war is over
G-API args serialization
* args serialization
* GRunArgP draft
* UMat added
* bind added
* DmitryM's review addressed. Code clean up required.
* fix android build
* bind test added
* more comments addressed
* try to fix Mac build
* clean up
* header-based generic implementation (GRunArg)
* clang again
* one more attempt for clang
* more clean up
* More Dmitry's comments addressed.
* monostate removed
* Top level functions and some other comments addressed.
* fix warnings
* disable warning
fix instable fisheye undistortPoints
* remove artefacts when (un)distorting fisheye images with large distortion coefficient values
* fix fisheye undistortion when theta is close to zero
* add fisheye image undistort and distort test
* Fixed type conversion warnings
* fixed trailing whitespace
Fix cuda11
* use cudnn_version.h to detect version when it is available
* remove nppi from CUDA11
* use ocv_list_filterout
* dnn(cuda): temporary disable CUDNN 8.0
G-API Serialization routines
* Serialization backend in tests, initial version
* S11N/00: A Great Rename
- "Serialization" is too long and too error-prone to type,
so now it is renamed to "s11n" everywhere;
- Same applies to "SRLZ";
- Tests also renamed to start with 'S11N.*' (easier to run);
- Also updated copyright years in new files to 2020.
* S11N/01: Some basic interface segregation
- Moved some details (low-level functions) out of serialization.hpp;
- Introduced I::IStream and I::OStream interfaces;
- Implemented those via the existing [De]SerializationStream classes;
- Moved all operators to use interfaces instead of classes;
- Moved the htonl/ntohl handling out of operators (to the classes).
The implementation didn't change much, it is a subject to the further
refactoring
* S11N/02: Basic operator reorg, basic tests, vector support
- Reorganized operators on atomic types to follow >>/<< model
(put them closer in the code for the respective types);
- Introduce more operators for basic (scalar) types;
- Drop all vector s11n overloads -- replace with a generic
(template-based) one;
- Introduced a new test suite where low-level s11n functionality
is tested (for the basic types).
* S11N/03: Operators reorganization
- Sorted the Opaque types enum by complexity;
- Reorganized the existing operators for basic types, also ordered by
complexity;
- Organized operators in three groups (Basics, OpenCV, G-API);
- Added a generic serialization for variant<>;
- Reimplemented some of the existing operators (for OpenCV and G-API
data structures);
- Introduced new operators for cv::gimpl data types. These operators
(and so, the data structures) are not yet used in the graph
dump/reconstruction routine, it will be done as a next step.
* S11N/04: The Great Clean-up
- Drop the duplicates of GModel data structures from the
serialization, serialize the GModel data structures themselve
instead (hand-written code replaced with operators).
- Also removed usuned code for printing, etc.
* S11N/05: Internal API Clean-up
- Minimize the serialization API to just Streams and Operators;
- Refactor and fix the graph serialization (deconstruction and
reconstruction) routines, fix data addressing problems there;
- Move the serialization.[ch]pp files to the core G-API library
* S11N/06: Top-level API introduction
- !!!This is likely the most invasive commit in the series!!!
- Introduced a top-level API to serialize and deserialize a GComputation
- Extended the compiler to support both forms of a GComputation:
an expession based and a deserialized one. This has led to changes in
the cv::GComputation::Priv and in its dependent components (even the
transformation tests);
- Had to extend the kernel API (GKernel) with extra information on
operations (mainly `outMeta`) which was only available for expression
based graphs. Now the `outMeta` can be taken from kernels too (and for
the deserialized graphs it is the only way);
- Revisited the internal serialization API, had to expose previously
hidden entities (like `GSerialized`);
- Extended the serialized graph info with new details (object counter,
protocol). Added unordered_map generic serialization for that;
- Reworked the very first pipeline test to be "proper"; GREEN now, the rest
is to be reworked in the next iteration.
* S11N/07: Tests reworked
- Moved the sample pipeline tests w/serialization to
test the public API (`cv::gapi::serialize`, then
followed by `cv::gapi::deserialize<>`). All GREEN.
- As a consequence, dropped the "Serialization" test
backend as no longer necessary.
* S11N/08: Final touches
- Exposed the C++ native data types at Streams level;
- Switched the ByteMemoryIn/OutStreams to store data in `char`
internally (2x less memory for sample pipelines);
- Fixed and refactored Mat dumping to the stream;
- Renamed S11N pipeline tests to their new meaning.
* linux build fix
* fix RcDesc and int uint warnings
* more Linux build fix
* white space and virtual android error fix (attempt)
* more warnings to be fixed
* android warnings fix attempt
* one more attempt for android build fix
* android warnings one more fix
* return back override
* avoid size_t
* static deserialize
* and how do you like this, elon? anonymous namespace to fix android warning.
* static inline
* trying to fix standalone build
* mat dims fix
* fix mat r/w for standalone
Co-authored-by: Dmitry Matveev <dmitry.matveev@intel.com>
cuda4dnn: reduce CUDA version requirements to at least CUDA 9.2
* remove half2 specializations
* do not remove atomicAdd for half in CUDA 10 and below
* remove fp16.hpp
Objc binding
* Initial work on Objective-C wrapper
* Objective-C generator script; update manually generated wrappers
* Add Mat tests
* Core Tests
* Imgproc wrapper generation and tests
* Fixes for Imgcodecs wrapper
* Miscellaneous fixes. Swift build support
* Objective-C wrapper build/install
* Add Swift wrappers for videoio/objdetect/feature2d
* Framework build;iOS support
* Fix toArray functions;Use enum types whenever possible
* Use enum types where possible;prepare test build
* Update test
* Add test runner scripts for iOS and macOS
* Add test scripts and samples
* Build fixes
* Fix build (cmake 3.17.x compatibility)
* Fix warnings
* Fix enum name conflicting handling
* Add support for document generation with Jazzy
* Swift/Native fast accessor functions
* Add Objective-C wrapper for calib3d, dnn, ml, photo and video modules
* Remove IntOut/FloatOut/DoubleOut classes
* Fix iOS default test platform value
* Fix samples
* Revert default framework name to opencv2
* Add converter util functions
* Fix failing test
* Fix whitespace
* Add handling for deprecated methods;fix warnings;define __OPENCV_BUILD
* Suppress cmake warnings
* Reduce severity of "jazzy not found" log message
* Fix incorrect #include of compatibility header in ios.h
* Use explicit returns in subscript/get implementation
* Reduce minimum required cmake version to 3.15 for Objective-C/Swift binding
Fixes the help for `--features`, previously listed all possible values as default value.
Also adds the default value to the help for two other arguments
The legacy `includedir` was removed in 4.0 (https://github.com/opencv/opencv/pull/12477) but it was not removed from the `.pc` file.
This causes issues when trying to link against OpenCV using pkg-config in CMake.
* fix bug for CHECK issue
* remove chack for bpp
* add test for tif file
* add test for tiff file
* change the test name
* use proper bpp value, use clear test names
- reworked variant::operator(T&&) and varaint::variant(T&&) to be more
concise and signature accurate with C++17 specification
- restricted cv::detail::OpaqueRef::OpaqueRef(T&&) to not substitute
copy/move ctors
- moved common additions to C++11 version of std <type_traits> to
separte header
* imgproc: templmatch: Add support for mask for all methods
Add support for masked template matching. Fix/scrub old implementation
for masked matching, as it did partly not even really do a meaningful
masking, and only supported limited template matching methods.
Add documentation including formulas for masked matching.
* imgproc: test: Add tests for masked template matching
Test accuracy by comparing to naive implementation for one point.
Test compatibility/correctness by comparing results without mask and
with all ones mask.
All tests are done for all methods, all supported depths, and for 1 and
3 channels.
* imgproc: test: templmatch: Add test for crossCorr
Add a test for the crossCorr function in templmatch.cpp. crossCorr() had
to be added to exported functions to be testable.
This test can maybe help to identify the problem with template matching
on MacOSX.
* fix: Fixed wrong evaluations of the MatExpr on Clang
* fix: removed crossCorr from public interface.
If it should be exported, it should be done as separate PR.
Co-authored-by: Vadim Levin <vadim.levin@xperience.ai>
- moved "standalone" aliases of cv types to "opencv_includes.hpp" to
keep responsibility principle aplied
- introduced correct aliasing for "descr_of(Mat)" function for
standalone case
- added missing include in `gapi/own/mat.hpp`
cuda4dnn: optimizations for swish, mish, sigmoid, region, resize based ops, transpose, identity-conv fusion
* bunch of optimizations
* more accurate implementation for mish
* feature: Extend VideoWriter to accept vector of parameters
- Add additional constructor and `open` method for `VideoWriter`
those accept a vector of parameters
- Move actual implementation of the `VideoWriter::open` to general method
which accepts vector of parameters
- Propagate parsed parameters map up to actual video backend construction
* fix: Change VideoWriter constructor description to suppress doc warning
* refactor: Rollback newlines changes
* feature: Changed VideoWriter parameters workflow
* feature: Log unused parameters in VideoWriter open
* doc: Fix VideoWriter `isColor` parameter description
* fix: int to bool VC++ conversion warning
* doc: Remove information about `isColor` flag usage.
G-API: Laplacian and bilateralFilter standard kernels
* Added Laplacian kernel and tests
* Added: Laplacian kernel, Bilateral kernel (CPU, GPU); Performance and accuracy tests for this kernels
* Changed tolerance for GPU test
* boner
* Some changes with alignment; Tests's parameters are the same as for OCV
* Cut tests
* Compressed tests
* Minor changes (rsrt bb)
* Returned types
- kernel added to a cv::gapi::video namespace
- tests to check a kernels (based on cv::video tests for cv::buildOpticalFlowPyramid())
- tests for a combined G-API-pipeline (buildOpticalFlowPyramid() -> calcOpticalFlowPyrLK())
- tests for internal purposes added
- custom function for comparison in tests implemented
* LineVirtualIterator
Proposal of LineVirtualIterator, an alternative to "LineIterator not attached to any mat".
This is basically the same implementation, replacing the address difference by a single "offset" variable. elemsize becomes irrelevant and considered to be 1. "step" is thus equal to size.width since no stride is expected.
* Update drawing.cpp
fixed warning
* improvement of LineVirtualIterator
instead of being too conservative, the new implementation gets rid of "offset/step" and only keeps a "Point currentPos" up to date.
left_to_right is renamed to forceLeftToRight as suggested (even for the old LineIterator)
assert() replaced by CV_Assert() (even for the old LineIterator)
* fixed implementation
+fixed last commit so that LineVirtualIterator gives at least the same results as LineIterator
+added a new constructor that does not require any Size, so that no clipping is done and iteration occurs from pt1 to pt2. This is done by adding a spatial offset to pt1 and pt2 so that the same implementation is used, the size being in that case the spatial size between pt1 and pt2
* Update imgproc.hpp
fixed warnings
* Update drawing.cpp
fixed whitespace
* Update drawing.cpp
trailing whitespace
* Update imgproc.hpp
+added a new constructor that takes a Rect rather than a Size. It computes the line pt1->pt2 that clips that rect.
Yet again, this is still based on the same implementation, thanks to the Size and the currentPosOffset that can artifically consider the origin of the rect at (0,0)
* revert changes
revert changes on original LineIterator implementation, that will be superseded by the new LineVirtualIterator anyway
* added test of LineVirtualIterator
* More tests
* refactoring
Use C++11 chained constructors
Improved code style
* improve test
Added offset as random test data.
* fixed order of initialization
* merged LineIterator and VirtualLineIterator
* merged LineIterator & VirtualLineIterator
* merged LineIterator & VirtualLineIterator
* merged LineIterator & VirtualLineIterator
* made LineIterator::operator ++() more efficient
added one perfectly predictable check; in theory, since ptmode is set in the end of the constructor in the header file, the compiler can figure out that it's always true/false and eliminate the check from the inline `LineIterator::operator++()` completely
* optimized Line() function
in the most common case (CV_8UC3) eliminated the check from the loop
Co-authored-by: Vadim Pisarevsky <vadim.pisarevsky@gmail.com>
- opencv_gapi module is linked with opencv_video module (optional dependency)
- kernels added to a new cv::gapi::video namespace and a brand new files created to provide gapi_video environment
- there are 2 different kernels as G-API should provide GMat AND GArray<GMat> implementation: cv::calcOptFlowPyrLK doesn't calculate pyramids if vector<Mat> is given so just the cast GMat -> GArray<GMat> wouldn't represent all the cv:: functionality
- tests to check both kernels (based on cv::video tests for cv::calcOpticalFlowPyrLK())
- tests for internal purposes added
- vectors<T> comparison in tests implemented
- new (and old too) common test structures refactored to avoid code copypasting
- "modules/gapi/test/common/gapi_video_tests_common.hpp" created to share some code snippets between perf and acc tests and avoid code copypasting
added estimateTranslation3D to calib3d/ptsetreg
* added estimateTranslation3D; follows API and implementation structure for estimateAffine3D, but only allows for translation
* void variables in null function to suppress compiler warnings
* added test for estimateTranslation3D
* changed to Matx13d datatype for translation vector in ptsetreg and test; used short license in test
* removed iostream include
* calib3d: code cleanup
- cv::gapi::goodFeaturesToTrack() kernel is implemented
- tests (for exact check with cv::goodFeaturesToTrack() and for internal cases) are implemented
- a custom comparison function for vectors and a custom test fixture implemented
- some posiible issues as wrong/inexact sorting of two compared vectors are
not taken into account
- initializations of an input Mat using a picture from opencv_extra implemented (function from gapi_streaming_test used)
G-API: Unification of own:: Scalar with cv:: Scalar
* cvdefs.hpp
* Small changes
* Deowned Scalar. Does't work
* Something
* Removed to_ocv for Scalar
* Clear code
* Deleted whitespaces
* Added include<..own/scalar.hpp in cvdefs.hpp.
* Long string split on two now
* Comment about scalar
* Comment about crutch
* Removed second varible in scalar_wrapper
* Changed wrapper for scalar, alignment
* Alignment
* Whitespaces
* Removed scalar_wrapper
Jpeg2000 OpenJPEG port
* OpenJPEG based JPEG2000 decoder implementation
Currently, the following input color spaces and depth conversions are
supported:
- 8 bit -> 8 bit
- 16 bit -> 16 bit (IMREAD_UNCHANGED, IMREAD_ANYDEPTH)
- RGB(a) -> BGR
- RGBA -> BGRA (IMREAD_UNCHANGED)
- Y(a) -> Y(a) (IMREAD_ANYCOLOR, IMREAD_GRAY, IMREAD_UNCHANGED))
- YCC -> Y (IMREAD_GRAY)
* Check for OpenJPEG availability
This enables OpenJPEG based JPEG2000 imread support by default, which
can be disabled by -DWITH_OPENJPEG=OFF. In case OpenJPEG is enabled
and found, any checks for Jasper are skipped.
* Implement precision downscaling for precision > 8 without IMREAD_UNCHANGED
With IMREAD_UNCHANGED, values are kept from the input image, without it
components are downscaled to CV_8U range.
* Enable Jpeg2K tests when OpenJPEG is available
* Add support for some more color conversions
Support IMREAD_GRAY when input color space is RGB or unspecified.
Support YUV input color space for BGR output.
* fix: problems with unmanaged memory
* fix: CMake warning - HAVE_OPENJPEG is undefined
Removed trailing whitespaces
* fix: CMake find_package OpenJPEG add minimal version
* Basic JPEG2K encoder
Images with depth CV_8U and CV_16U are supported, with 1 to 4 channels.
* feature: Improved code for OpenJPEG2000 encoder/decoder
- Removed code duplication
- Added error handlers
- Extracted functions
* feature: Update conversion openjpeg array from/to Mat
* feature: Extend ChannelsIterator to fulfill RandomAccessIterator named requirements
- Removed channels split in copyFromMatImpl. With ChannelsIterator no allocations are performed.
- Split whole loop into 2 parts in copyToMat -> where std::copy and std::transforms are called.
* fix: Applied review comments.
- Changed `nullptr` in CV_LOG* functions to `NULL`
- Added `falls through` comment in decoder color space `switch`
- Added warning about unsupported parameters for the encoder
* feature: Added decode from in-memory buffers.
Co-authored-by: Vadim Levin <vadim.levin@xperience.ai>
Image sharpness, as well as brightness, are a critical parameter for
accuracte camera calibration. For accessing these parameters for
filtering out problematic calibraiton images, this method calculates
edge profiles by traveling from black to white chessboard cell centers.
Based on this, the number of pixels is calculated required to transit
from black to white. This width of the transition area is a good
indication of how sharp the chessboard is imaged and should be below
~3.0 pixels.
Based on this also motion blur can be detectd by comparing sharpness in
vertical and horizontal direction. All unsharp images should be excluded
from calibration as they will corrupt the calibration result. The same
is true for overexposued images due to a none-linear sensor response.
This can be detected by looking at the average cell brightness of the
detected chessboard.
Changes:
* UMat for blur + rotate resulting in a speedup of around 2X on an i7
* support for boards larger than specified allowing to cover full FOV
* support for markers moving the origin into the center of the board
* increase detection accuracy
The main change is for supporting boards that are larger than the FOV of
the camera and have their origin in the board center. This allows
building OEM calibration targets similar to the one from intel real
sense utilizing corner points as close as possible to the image border.
cuda4dnn(concat): write outputs from previous layers directly into concat's output
* eliminate concat by directly writing to its output buffer
* fix concat fusion not happening sometimes
* use a whitelist instead of a blacklist
* cmake: allow customization of CMAKE_CXX_STANDARD value
* cmake: extra skip flag OPENCV_SKIP_CMAKE_CXX_STANDARD
* cmake: dump CMAKE_CXX_STANDARD value
- compiler option is missing in dumped flags
* G-API/Samples: Added a simple "privacy masking camera" sample
The main idea is to host this code for an opencv.org blog post only
* G-API/Samples: Modified privacy masking camera code to look better for the post
* G-API/Samples: fix Windows (MSVC) support in Privacy Masking Camera
* G-API/Samples: Addressed the majority of review comments in PMC
* G-API/Samples: Use TickMeter to measure time + more info in cmd options
* G-API/Samples: fix yet another Windows warning in PMC
* G-API/Samples: Fix wording in PMC cmd arg parameters
* Fix wording, again
* G-API/Samples: Fix PMC cmd-line arguments, again
G-API: Using functors as kernel implementation
* Implement ability to create kernel impls from functors
* Clean up
* Replace make_ocv_functor to ocv_kernel
* Clean up
* Replace GCPUFunctor -> GOCVFunctor
* Move GOCVFunctor to cv::gapi::cpu namespace
* Implement override for rvalue and lvalue cases
* Fix comments to review
* Remove GAPI_EXPORT for template functions
* Fix indentation
* improved version of HoughCircles (HOUGH_GRADIENT_ALT method)
* trying to fix build problems on Windows
* fixed typo
* * fixed warnings on Windows
* make use of param2. make it minCos2 (minimal value of squared cosine between the gradient at the pixel edge and the vector connecting it with circle center). with minCos2=0.85 we can detect some more eyes :)
* * added description of HOUGH_GRADIENT_ALT
* cleaned up the implementation; added comments, replaced built-in numeic constants with symbolic constants
* rewrote circle_popcount() to use built-in popcount() if possible
* modified some of HoughCircles tests to use method parameter instead of the built-in loop
* fixed warnings on Windows
trying to fix handling file storages with extremely long lines
* trying to fix handling of file storages with extremely long lines: https://github.com/opencv/opencv/issues/11061
* * fixed errorneous pointer access in JSON parser.
* it's now crash-test time! temporarily set the initial parser buffer size to just 40 bytes. let's run all the test and check if the buffer is always correctly resized and handled
* fixed pointer use in JSON parser; added the proper test to catch this case
* fixed the test to make it more challenging. generate test json with
*
**
***
etc. shape
- Added `explicit` to `VideoCapture` constructors with 2
arguments, 1 of them has default value
- Applied library code style
- Introduced 2 debug macros to improve readability of the code
support eltwise sum with different number of input channels in CUDA backend
* add shortcut primitive
* add offsets in shortcut kernel
* skip tests involving more than two inputs
* remove redundant modulus operation
* support multiple inputs
* remove whole file indentation
* skip acc in0 trunc test if weighted
* use shortcut iff channels are unequal
Enable cuda4dnn on hardware without support for __half
* Enable cuda4dnn on hardware without support for half (ie. compute capability < 5.3)
Update CMakeLists.txt
Lowered minimum CC to 3.0
* UPD: added ifdef on new copy kernel
* added fp16 support detection at runtime
* Clarified #if condition on atomicAdd definition
* More explicit CMake error message
* add cv::compare test when Mat type == CV_16F
* add assertion in cv::compare when src.depth() == CV_16F
* cv::compare assertion minor fix
* core: add more checks
* enable tests for DNN_TARGET_CUDA_FP16
* disable deconvolution tests
* disable shortcut tests
* fix typos and some minor changes
* dnn(test): skip CUDA FP16 test too (run_pool_max)
G-API: Tutorial: Face beautification algorithm implementation
* Introduce a tutorial on face beautification algorithm
- small typo issue in render_ocv.cpp
* Addressing comments rgarnov smirnov-alexey
* G-API: Added G-API Overview slides & its source code
- Sample code snippets are moved to separate files;
- Introduced a separate benchmark to measure Fluid/OpenCV
performance;
- Added notes on API changes (it is still a 4.0, not a 4.2 talk!)
- Added a "Metropolis" beamer download-n-build script.
* G-API: Addressed review issues on G-API overview slides
G-API: Fix various issues for 4.2 release
* G-API: Fix issues reported by Coverity
- Fixed: passing values by value instead of passing by reference
* G-API: Fix redundant std::move()'s in return statements
Fixes#15903
* G-API: Added a smarter handling of Stop messages in the pipeline
- This should fix the "expected 100, got 99 frames" problem
- Fixes#15882
* G-API: Pass enum instead of GKernelPackage in Streaming test parameters
- Likely fixes#15836
* G-API: Address review issues in new bugfix comments
* G-API-NG/Docs: Added a tutorial page on interactive face detection sample
- Introduced a "--ser" option to run the pipeline serially for
benchmarking purposes
- Reorganized sample code to better fit the documentation;
- Fixed a couple of issues (mainly typos) in the public headers
* G-API-NG/Docs: Reflected meta-less compilation in new G-API tutorial
* G-API-NG/Docs: Addressed review comments on Face Analytics Pipeline example
cuda4dnn(resize): process multiple channels each iteration
* resize bilinear: process multiple chans. per iter.
* remove unused headers
* correct dispatch logic
* resize_nn: process multiple chans. per iter.
* G-API: Addressed various documentation issues
- Fixed various typos and missing references;
- Added brief documentaion on G_TYPED_KERNEL and G_COMPOUND_KERNEL macros;
- Briefly described GComputationT<>;
- Briefly described G-API data objects (in a group section).
* G-API: Some clean-ups in doxygen, also a chapter on Render API
* G-API: Expose more graph compilation arguments in the documentation
* G-API: Address documentation review comments
Fix cudacodec python
* Add python bindings to cudacodec.
* Allow args with CV_OUT GpuMat& or CV_OUT cuda::GpuMat& to generate python bindings that allow the argument to be an optional output in the same way as OutputArray.
* Add wrapper flag to indicate that an OutputArray is a GpuMat.
* python: drop CV_GPU, extra checks in test
* Remove "cuda::GpuMat" check rom python parser
G-API-NG/Streaming: don't require explicit metadata in compileStreaming()
* First probably working version
Hardcode gose to setSource() :)
* Pre final version of move metadata declaration from compileStreaming() to setSource().
* G-API-NG/Streaming: recovered the existing Streaming functionality
- The auto-meta test is disabling since it crashes.
- Restored .gitignore
* G-API-NG/Streaming: Made the meta-less compileStreaming() work
- Works fine even with OpenCV backend;
- Fluid doesn't support such kind of compilation so far - to be fixed
* G-API-NG/Streaming: Fix Fluid to support meta-less compilation
- Introduced a notion of metadata-sensitive passes and slightly
refactored GCompiler and GFluidBackend to support that
- Fixed a TwoVideoSourcesFail test on streaming
* Add three smoke streaming tests to gapi_streaming_tests.
All three teste run pipeline with two different input sets
1) SmokeTest_Two_Const_Mats test run pipeline with two const Mats
2) SmokeTest_One_Video_One_Const_Scalar test run pipleline with Mat(video source) and const Scalar
3) SmokeTest_One_Video_One_Const_Vector test run pipeline with Mat(video source) and const Vector
# Please enter the commit message for your changes. Lines starting
* style fix
* Some review stuff
* Some review stuff
* Added Swish and Mish activations
* Fixed whitespace errors
* Kernel implementation done
* Added function for launching kernel
* Changed type of 1.0
* Attempt to add test for Swish and Mish
* Resolving type mismatch for log
* exp from device
* Use log1pexp instead of adding 1
* Added openCL kernels
Fix incorrect use of std::move() in g-api perf tests
* First version
* Fix perfomace tests
Replace
c.apply(...);
with
cc = c.compile(...);
cc(...);
* Remove output meta arguments from .compile()
* Style fix
* Remove useless commented string
* Stick to common pattern : i.e. use gin() and gout() explicitly.
* Use cc(gin(...), gout(...)) in all cases.
Add retrieve encoded frame to VideoCapture
* Add capacity to retrieve the encoded frame from a VideoCapture object.
* Correct raw codec and pixle format output from ffmpeg capture.
* Remove warnings from build.
* Added VideoCaptureRaw subclass.
* Include abstract base class VideoCaptureBase and rename new subclass VideoContainer as suggested by mshabunin.
* Remove using.
* Change base class name for compatibility with jave bindings generator.
* Move grab and retrieve and add override specifier
* Add setRaw and readRaw to IVideoCapture interface
-setRaw to disable video decoding and enable bitstream filters from mp4 to h254 and h265.
-readRaw to return the raw undecoded/filtered bitstream.
Add createRawCapture to initiate a backend with setRaw enabled.
Remove inheritance and use an independant VideoContainer subclass with IVideoCapture member.
* Address unused parameter warings.
Remove VideoContainer from python bindings as it no longer returns a Mat.
Use opencv type uchar instead of unsigned char.
Add missing destructor to VideoContainer class.
* Address build warnings and include all params in documentation.
* Include deprecated bitstream filtering API.
* Update codec_id query to work with older ffmpeg api's.
Change api version defines to be consistent - most recent api version first.
* Fix typo.
* Update test to work with naming of new files in the extra repo
* Investigate test failure
* Check bytes read by ffmpeg
* Removed mp4 video container test
* Applied suggested changes.
* videoio: rework API for extraction of RAW video streams
- FFmpeg only
* address review comments
Introducing the sample of Face Beautification algorithm implemented via Graph-API
* Introducing the sample of Face Beautification algorithm implemented via Graph-API
- 'gapi/samples/face_beautification.cpp' added
- FIXME added in 'gcpukernel.hpp'
* INF_ENGINE fix
- preprocessing clauses added not to run the sample without Inference Engine
* INF_ENGINE fix 2
- warnings removed
* Fixes
- checking IE version cut as there is no dependency
- some alignments fixed
- the comment about preprocessing commands fixed
* ie::backend() issue fix (according to dmatveev)
- as the sample needs the cv::gapi::ie::backend() to be defined regardless of having IE or not, there is its throw-error definition in `giebackend.cpp` now (by dmatveev)
- for the same reason, #includes in `giebackend.hpp` are fixed
- HAVE_INF_ENGINE check is removed from the sample
Implement Camera Multiplexing API
* IdideoCapture + two wrong function
function waitAny
Add errors catcher
Stub for Python added.
Sifting warnings
One test added
Two tests for camera and Perf tests added
* Perf sync and async tests for waitAny() added, waitAnyInterior() deleted, getDeviceHandle() deleted
* Variable OPENCV_TEST_CAMERA_LIST added
* Without fps set
* ASSERT_FAILED for environment variable
* Perf tests is DISABLED_
* --Trailing whitespace
* Return false from cap.cpp deleted
* Two functions deleted from interface, +range for, +environment variable in test_camera
* Space deleted
* printf deleted, perror added
* CV_WRAP deleted, cv2 cleared from stubs
* -- space
* default timeout added
* @param changed
* place of waitAny changed
* --whitespace
* ++function description
* function description changed
* revert unused changes
* videoio: rework API for VideoCapture::waitAny()
The hard-coded string value "Mat" was used in the two format strings for vector_mat and vector_mat_template, preventing UMat arguments to functions that have these types from working correctly. Notably, #12231 references this issue.
* G-API: Doxygen documentatation for Async API
* G-API: Doxygen documentatation for Async API
- renamed local variable (reading parameter async) async ->
asyncNumReq in object_detection DNN sample
to avoid Doxygen erroneous linking the sample to cv::gapi::wip::async
documentation
* G-API-NG/Streaming: Introduced a Streaming API
Now a GComputation can be compiled in a special "streaming" way
and then "played" on a video stream.
Currently only VideoCapture is supported as an input source.
* G-API-NG/Streaming: added threading & real streaming
* G-API-NG/Streaming: Added tests & docs on Copy kernel
- Added very simple pipeline tests, not all data types are covered yet
(in fact, only GMat is tested now);
- Started testing non-OCV backends in the streaming mode;
- Added required fixes to Fluid backend, likely it works OK now;
- Added required fixes to OCL backend, and now it is likely broken
- Also added a UMat-based (OCL) version of Copy kernel
* G-API-NG/Streaming: Added own concurrent queue class
- Used only if TBB is not available
* G-API-NG/Streaming: Fixing various issues
- Added missing header to CMakeLists.txt
- Fixed various CI issues and warnings
* G-API-NG/Streaming: Fixed a compile-time GScalar queue deadlock
- GStreamingExecutor blindly created island's input queues for
compile-time (value-initialized) GScalars which didn't have any
producers, making island actor threads wait there forever
* G-API-NG/Streaming: Dropped own version of Copy kernel
One was added into master already
* G-API-NG/Streaming: Addressed GArray<T> review comments
- Added tests on mov()
- Removed unnecessary changes in garray.hpp
* G-API-NG/Streaming: Added Doxygen comments to new public APIs
Also fixed some other comments in the code
* G-API-NG/Streaming: Removed debug info, added some comments & renamed vars
* G-API-NG/Streaming: Fixed own-vs-cv abstraction leak
- Now every island is triggered with own:: (instead of cv::)
data objects as inputs;
- Changes in Fluid backend required to support cv::Mat/Scalar were
reverted;
* G-API-NG/Streaming: use holds_alternative<> instead of index/index_of test
- Also fixed regression test comments
- Also added metadata check comments for GStreamingCompiled
* G-API-NG/Streaming: Made start()/stop() more robust
- Fixed various possible deadlocks
- Unified the shutdown code
- Added more tests covering different corner cases on start/stop
* G-API-NG/Streaming: Finally fixed Windows crashes
In fact the problem hasn't been Windows-only.
Island thread popped data from queues without preserving the Cmd
objects and without taking the ownership over data acquired so when
islands started to process the data, this data may be already freed.
Linux version worked only by occasion.
* G-API-NG/Streaming: Fixed (I hope so) Windows warnings
* G-API-NG/Streaming: fixed typos in internal comments
- Also added some more explanation on Streaming/OpenCL status
* G-API-NG/Streaming: Added more unit tests on streaming
- Various start()/stop()/setSource() call flow combinations
* G-API-NG/Streaming: Added tests on own concurrent bounded queue
* G-API-NG/Streaming: Added more tests on various data types, + more
- Vector/Scalar passed as input;
- Vector/Scalar passed in-between islands;
- Some more assertions;
- Also fixed a deadlock problem when inputs are mixed (1 constant, 1 stream)
* G-API-NG/Streaming: Added tests on output data types handling
- Vector
- Scalar
* G-API-NG/Streaming: Fixed test issues with IE + Windows warnings
* G-API-NG/Streaming: Decoupled G-API from videoio
- Now the core G-API doesn't use a cv::VideoCapture directly,
it comes in via an abstract interface;
- Polished a little bit the setSource()/start()/stop() semantics,
now setSource() is mandatory before ANY call to start().
* G-API-NG/Streaming: Fix STANDALONE build (errors brought by render)
If an aravis camera is software triggered, a trigger needs to be explicitly sent using `arv_camera_software_trigger`, otherwise the camera will not grab any frames.
> Size parameter is changed from int to cv::Size type to allow rectangle kernels
> Kernel creation code is adopted for different kernel sizes to not create only white images on the output
G-API: add transformation logic to GCompiler
* Introduce transformation logic to GCOmpiler
* Remove partialOk() method
* Fix minor issues
* Refactor code according to code review
1. Re-design matchPatternToSubstitute logic
2. Update transformations order
3. Replace check_transformations pass with a
one time check in GCompiler ctor
* Revert unused nodes handling in pattern matching
* Address minor code review issues
* Address code review comments:
1) Fix some mistakes
2) Add new tests for endless loops
3) Update GCompiler's transformations logic
* Simplify GCompiler check for endless loops
1. Simplify transformations endless loops check:
- Original idea wasn't a full solution
- Need to develop a good method (heuristic?) to find loops
in general case (TODO)
2. Remove irrelevant Endless Loops tests
3. Add new "bad arg" tests and unit tests
* Update comments
* - headers in "infer/" and "infer/ie/" folders are included into gapi_ext_hdrs;
+ because of that a few #includes are required in the headers
- HAVE_INF_ENGINE flag check in headers "infer/ie.hpp" and "infer/ie/util.hpp" is deleted
* - the "ie/util.hpp" header is a private header now as it's used for tests; it's been moved to the scr directory to the place next to the implementation file "ie/giebackend.cpp"
- the path to this header in files "ie/giebackend.cpp" and "test/infer/gapi_infer_ie_test.cpp" is updated
- As it's private header now and explicitly depends on IE, the "HAVE_INF_ENGINE" flag check is returned
* Support GArray as input in fluid kernels
* Create tests on GArray input in fluid
* Some fixes to fully support GArray
* Refactor code and change the kernel according to review
* Add histogram calculation as a G-API kernel
Add assert that input GArgs in fluid contain at least one GMat
Detected by clang trunk:
```
opencv/modules/core/src/ocl.cpp:4337:37: warning: object backing the pointer will be destroyed at the end of the full-expression [-Wdangling]
CV_OCL_CHECK_RESULT(retval, cv::format("clCreateBuffer(capacity=%lld) => %p", (long long int)entry.capacity_, (void*)entry.clBuffer_).c_str());
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
opencv/modules/core/src/ocl.cpp:193:42: note: expanded from macro 'CV_OCL_CHECK_RESULT'
if (0) { const char* msg_ = (msg); CV_UNUSED(msg_); /* ensure const char* type (cv::String without c_str()) */ } \
```
because `cv::format` yields a temporary std::string, and thus `msg_` points to a destroyed buffer.
* Fix the detection of XIMEA on Windows (when it has been installed by another user with administrative privileges, for example).
* Change the flow: we first try HKEY_CURRENT_USER key and, if empty, then try HKEY_LOCAL_MACHINE
* in embindgen.py added inpaint function
* added test for inpaint function and fixed function in build_js
* fixed test for inpaint function
* rotate deleted, build_js.py fixed
G-API: Fix Journal usage in Fluid backend (#15238)
* Fix Journal usage in Fluid backend
* Delete dumpDotRequired(): invalid check
* Update mem consumption test
* Test that new test works
* Debug memory consumption function
* Increase iterations in test
* Re-write memory consumption measurement part
* Restore correct fix for Fluid journals
* G-API: rename ArgKind OPAQUE to GOPAQUE
Rename ArgKind value to GOPAQUE to fix conflict in the
user code when wingdi.h is included: it defines OPAQUE
macro that (for some reason) is chosen instead of ArgKind
value
* Add compatibility with existing API
* Renamed GOPAQUE to OPAQUE_VAL
* G-API-NG/API: Introduced inference API and IE-based backend
- Very quick-n-dirty implementation
- OpenCV's own DNN module is not used
- No tests so far
* G-API-NG/IE: Refined IE backend, added more tests
* G-API-NG/IE: Fixed various CI warnings & build issues + tests
- Added tests on multi-dimensional own::Mat
- Added tests on GMatDesc with dimensions
- Documentation on infer.hpp
- Fixed more warnings + added a ROI list test
- Fix descr_of clash for vector<Mat> & standalone mode
- Fix build issue with gcc-4.8x
- Addressed review comments
* G-API-NG/IE: Addressed review comments
- Pass `false` to findDataFile()
- Add deprecation warning suppression macros for IE
* G-API: fix GOCLExecutable issue with UMat lifetime
Add tests on initialized/uninitialized outputs for all
backends
* Use proper clean-up procedure for magazine
* Rename InitOut test and reduce tested sizes
* Enable output allocation test
G-API: GAPI_TRANSFORM internal functionality rework (#14952)
* Change internal pattern and substitute signatures and refactor tests
* Enhance GArrayU with type-checker function
Add a couple of new tests on GAPI_TRANSFORM
G-API: clean up accuracy tests (#14945)
* Delete createOutputMatrices flag
Update the way compile args function is created
Fix instantiation suffix print function
* Update comment (NB)
* Make printable comparison functions
* Use defines instead of objects for compile args
* Remove custom printers, use operator<< overload
* Remove SAME_TYPE and use -1 instead
* Delete createOutputMatrices flag in new tests
* Fix GetParam() printed values
* Update Resize tests: use CompareF object
* Address code review feedback
* Add default cases for operator<< overloads
* change throw to GAPI_Assert
G-API: Add output allocation tests for backends (#15012)
* Add output tests for backends
* Fix large size test: output is in fact reallocated
* Use cv::Mat copies for reallocation tracking
* Separate LargeSizeWithCorrectSubmatrix test
* Rename backed output allocation tests
* Address code review feedback
Update test names
Add illustrative "expect (non-)empty" checks
Rename mat "copy" to mat reference
Add more pointer checks
* Add illustrative checks
- Added new graph compile time argument to specify multiple independent
ROIs (Tiles)
- Added new "executable" with serial loop other user specified
ROIs(Tiles)
- refactored graph traversal code into separate function to be called
once
- added saturate cast to Fluid AddCsimple test kernel
G-API planar kernels (#14917)
* Added resizeP with tests
* NV12 planar filters
* fix warnings in ResizeP test
* fix out mat ocv warning
* sz_on - > sz rename
* cpu tests new signature
* try to fix resizeP test
* trailing spaces remove
* doxygen doc fixed
* doxygen minor fix
* more doxygen fixes
* Doxygen corrected and extended after review.
G-API: Parameterized render tests (#14892)
* Init commit
* Add mat size as test parameter
* Add test for text render
* Add test for rect render
* Add tests for line and circle
* Remove old render tests
* Init output mats
* Remove methods input arguments
* Add comment about data loss in BGR2NV12 conversion
* Add edge test cases
* Replace default color for out mats black -> white
G-API: Introduce new approach to write accuracy tests (#14757)
* G-API: Introduce new common accuracy test fixture
* Enable Range<> to Seq<> implicit conversion
* Fix shadowing parameters
* Update license headers
* Rename ALIGNED_TYPE to SAME_TYPE
* Move MkRange to tests
* Fix TODO(agolubev) in test instantiations
* Squash simple fixture declarations in one line
* Remove unused line
* Fix Windows issues with macro expansion
* Choose between 1 or 2 matrix initialization
* Redesign common class behavior
Use "views" for GetParam() provided by GTest
base class instead of doing segregation
(with copy!) of common and specific parameters:
request common or specific parameter directly
by index from GetParam()-returned parameters
* Refine user-level API and usage of new test model
* Fix -fpermissive errors
* Remove unnecessary init calls
* Replace GCompileArgs member variable with func ptr
* Rename initMatsRandN to make its behavior explicit
Rename initMatsRandN to initMatrixRandN to eliminate confusion:
initMatsRandN only initialized first matrix (similarly to
initMatrixRandU)
* Fix common of initNothing
* Update copyright dates in missed files
* Add check for specific parameters
* Fix coment stlye
Description:
Moved NVIDIA_Optical_flow sample app and comparison app to
opencv_contrib branch. Added CUDA_CUDA_LIBRARY in CMakeLists.txt for
resolving linker errors.
* Introduce GAPI_TRANSFORM initial interface
Comes along with simple tests and kernel package changes
* Fix documentation and adjust combine() function
* Fix stuff after rebasing on master
* Remove redundant functionality
* Refactoring according to review feedback provided
* Fixes according to review feedback
* Reconsider transformations return and fix a warning
* Fixes from code review
* Add a new simple test
* Cleanup, added tests on GScalar, GMatP, GArray
G-API: Add parameters alpha and beta in tests on ConvertTo kernel (#14684)
* Add parameters alpha and beta in tests on ConvertTo kernel
* Change tolerance function
* Reduce number of test cases
G-API aux kernels (#14599)
* Removed gcpuimgproc.hpp and gcpucore.hpp
* Changed GModel::orderedInputs and orderedOutputs to get ConstGraph&
* Added auxiliaryKernels() method of GBackend::Priv
G-API: Kernel package design (#13851)
* Remove cv::unite_policy from API
* Add check that all id in kernel package are unique
* Refactor checker id procedure
* Remove cv::gapi::GLookupOrder from API
* Implement cv::gapi::use_only
* Fix samples
* Fix docs
* Fix comments to review
* Remove unite_policy
* Fix GKernelPackage::backends()
* Fix comments to review
* Fix all_unique
* Fix comments to review
* Fix comments to review
* Remove out of date tests
OE-11 Logging revamp (#13909)
* Initial commit for log tag support.
Part of #11003, incomplete. Should pass build.
Moved LogLevel enum to logger.defines.hpp
LogTag struct used to convey both name and log level threshold as
one argument to the new logging macro. See logtag.hpp file, and
CV_LOG_WITH_TAG macro.
Global log level is now associated with a global log tag, when a
logging statement doesn't specify any log tag. See getLogLevel and
getGlobalLogTag functions.
A macro CV_LOGTAG_FALLBACK is allowed to be re-defined by other modules
or compilation units, internally, so that logging statements inside
that unit that specify NULL as tag will fall back to the re-defined tag.
Line-of-code information (file name, line number, function name),
together with tag name, are passed into the new log message sink.
See writeLogMessageEx function.
Fixed old incorrect CV_LOG_VERBOSE usage in ocl4dnn_conv_spatial.cpp.
* Implemented tag-based log filtering
Added LogTagManager. This is an initial version, using standard C++
approach as much as possible, to allow easier code review. Will
optimize later.
A workaround for all static dynamic initialization issues is
implemented. Refer to code comments.
* Added LogTagConfigParser.
Note: new code does not fully handle old log config parsing behavior.
* Fix log tag config vs registering ordering issue.
* Started testing LogTagConfigParser, incomplete.
The intention of this commit is to illustrate the capabilities of
the current design of LogTagConfigParser.
The test contained in this commit is not complete. Also, design changes
may require throwing away this commit and rewriting test code from
scratch.
Does not test whitespace segmentation (multiple tags on the config);
will do in next commit.
* Added CV_LOGTAG_EXPAND_NAME macro
This macro allows to be re-defined locally in other compilation units
to apply a prefix to whatever argument is passed as the "tag" argument
into CV_LOG_WITH_TAG. The default definition in logger.hpp does not
modify the argument. It is recommended to include the address-of
operator (ampersand) when re-defined locally.
* Added a few tests for LogTagManager, some fail.
See test_logtagmanager.cpp
Failed tests are: non-global ("something"), setting level by name-part
(first part or any part) has no effect at all.
* LogTagManagerTests substring non-confusion tests
* Fix major bugs in LogTagManager
The code change is intended to approximate the spec documented in
https://gist.github.com/kinchungwong/ec25bc1eba99142e0be4509b0f67d0c6
Refer to test suite in test_logtagmanager.cpp
Filter test result in "opencv_test_core" ...
with gtest_filter "LogTagManager*"
To see the test code that finds the bugs, refer to original commits
(before rebase; might be gone)
.. f3451208 (2019-03-03T19:45:17Z)
.... LogTagManagerTests substring non-confusion tests
.. 1b848f5f (2019-03-03T01:55:18Z)
.... Added a few tests for LogTagManager, some fail.
* Added LogTagManagerNamePartNonConfusionTest.
See test_logtagmanager.cpp in modules/core/test.
* Added LogTagAuto for auto registration in ctor
* Rewritten LogTagManager to resolve issues.
* Resolves code review issues around 2019-04-10
LogTagConfigParser::parseLogLevel - as part of resolving code review
issues, this function is rewritten to simplify control flow and to
improve conformance with legacy usage (for string values "OFF",
"DISABLED", and "WARNINGS").
G-API external backend development (#13943)
* Moved HostCtor and ConstVal from gapi_priv.hpp to objref.hpp
* Added gmodel_priv.hpp, added export of symbols from gmodel.hpp
* Added export of binInArg and bindOutArg
* Renamed gapi_priv.*pp -> gorigin.*pp
* Added a fixme on collecting exports inside one class
Many of the Android samples rely on an options menu to work properly
but, at least on newer devices, the menu is permanently hidden by the
Android theme "Theme.NoTitleBar.Fullscreen", which means that most
of the examples were dysfunctional.
Allow nodes produced after some operation to be
"unused": not being an output and not being used
as inputs to other operations
Add fluid test to cover this case
* Fix Issue 13908
Allocate the matrix _Jo only when the solver needs it (ie when solver.state == CvLevMarq::CALC_J)
* Fix calib3D unit test
Fix _Jo allocation when stddev is not empty
* Removing trailing whitespaces
* scope _dp* variables
* fix whitespaces
* Android build improvements
* look for NDK in "ndk-bundle" directory under the SDK directory if location not specified
* look for cmake and ninja in "cmake" directory under the SDK directory if not found in the path
* disable use of ccache if not found in the path
* Redo build tool existence checks
* core, stitching: revise syntax to support Visual C++ 2013
* stitching: revise syntax again to support Visual C++ 2013 and other compilers
* stitching: minor update to clarify changes
* LineIterator witout a Mat
cv::LineIterator can be used without being attached to any cv::Mat, it only needs the size and type of data. An alternative constructor has been defined for that.
In that case, a LineIterator can no more be dereferenced with the * operator, but pos() still returns valid pixel positions.
It can be useful when LineIterator is just used to compute positions of pixels on a line, without requiring to build a Mat just for that.
Use case : with a dataset that would represent a huge image, pixel positions can be pre-computed before querying the dataset API.
* Update imgproc.hpp
removed trailing spaces
* Update drawing.cpp
fixed warning
* Add Sobel kernel which returns both dx and dy
* Splice dx and dy and extend add_border function
Also change some tests parameters
* Add borderValue parameter in test
* Introduces fluid kernel for sobelxy
Adds tests (basic and performance) on new backend
* Introduces BufHelper struct for some arithmetic
GAPI: Add normalize kernel in G-API (#13721)
* Add normalize kernel in G-API
In addition add several tests on new kernel
* Fix indentations and normalize test structure
* Move normalize kernel from imgproc to core
Set default parameter ddepth to -1
* Fix alignment
* Return vector of MetaArg instead of MatDesc and fix test with ADL check
* Fix construction of vector
* Change names and tests according to review
Also add GAPI_EXPORTS prefix for two ostream operators
* Add version of descr_of function taking vector of Mat
* Overload descr_of function for cv::Mat
* Add template function instead of copypasting and change tests a little
Improve stitching detailed (#13584)
* Added block size getter/setters
* Added a bunch of new features to the stitching_detailed sample
* Do not required XFEATURES2D for default use
* Add support for akaze features in stitching_detailed
* Improved sample logs
* dnn/Vulkan: fix GPU hang for heavy convolution tasks
Intel i915 driver will declare GPU hang if the compute shader
takes too long to complete. See
https://bugs.freedesktop.org/show_bug.cgi?id=108947 for details.
The idea in this commit is to divide heavy task into several light
ones and run compute shader multiple times to make each run take
short time enough.
TODO: Add more efficient compute shader
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
* dnn/Vulkan: add a more efficient conv shader
* Python wrapper for detail
* hide pyrotationwrapper
* copy code in pyopencv_rotationwarper.hpp
* move ImageFeatures MatchInfo and CameraParams in core/misc/
* add python test for detail
* move test_detail in test_stitching
* rename
Stitching: added functions to set warp interpolation mode (#13449)
* Added functions to set warp interpolation mode
* Use InterpolationFlags enum
* Improved getter/setter naming
* Enable Javascript bindings for photo module.
1. Enable the build flag in build_js.py.
2. Append js into WRAP list of photo’s CMakefiles.txt
3. Add photo module's API into JS API whitelist (embindgen.py)
Exposing the HDR imaging part of photo module.
[TODO]
Add tests
Fix opencv/doc/js_tutorials/
* [WIP] TODO: Add tests
* Remove TonemapDurand: algorithm patented in US, so moved to opencv_contrib
* Fix ningxin's comment: expose the base class.
* Add some more simple binding tests.
Also expose process function
* videoio(librealsense): fix pipeline start with config
fix to apply pipeline settings by passing config to start.
* videoio(librealsense): add support get props
add support get some props.
* Get/Set functions for BRISK parameters, issue #11527.
Allows setting threshold and octaves parameters after creating a brisk object. These parameters do not affect the initial pattern initialization and can be changed later without re-initialization.
* Fix doc parameter name.
* Brisk get/set functions tests. Check for correct value and make tests independent of default parameter values.
* Add dummy implementations for BRISK get/set functions not to break API in case someone has overloaded the Feature2d::BRISK interface. This makes BRISK different from the other detectors/descriptors on the other hand, where get/set functions are pure virtual in the interface.
More fixes for G-API tests (#13251)
* scalar comparator and more fixes for tests
* add weighted aligned
* white space
* more white space
* Add weighted test accuracy check enabled
GAPI (fluid): optimization of Separable filter (#13221)
* GAPI (fluid): Separable filter: performance test
* GAPI (fluid): enable all performance tests
* GAPI: separable filters: alternative code for Sobel
* GAPI (fluid): hide unused old code for Sobel filter
* GAPI (fluid): especial code for Sobel if U8 into S16
* GAPI (fluid): back to old code for Sobel
* GAPI (fluid): run_sepfilter3x3_impl() with CPU dispatcher
* GAPI (fluid): run_sepfilter3x3_impl(): fix compiler warnings
* GAPI (fluid): new engine for separable filters (but Sobel)
* GAPI (fluid): new performance engine for Sobel
* GAPI (fluid): Sepfilters performance: fixed compilation error
* custom OpenCL G-API kernel draft
* clean up and warnings fix
* more warnings
* white space
* new blank line at the EOF removed
* HAVE_OPENCL guard
* remove unnecessary ocl API call
* remove sum test workaround
* check if opencl activated
* fix std::str warning
* CPU fall back for symm7x7
* gpu test kernel draft
* adjust have opencl guard
* more guards
* one more attempt to adjust guards
* empty stub files and kernel source files creation in the test directory
* try to force auto generation
* one more attempt to force build
* remove symm7x7 custom from gapi module
* looks like that this version works properly on Win desktop
* clean up
* more clean up
* address some suggestions from Dmitry's review
* const kernel coefficients
* CV_Error in kernel + try to fix cpu fallback
* CV_Error_ instead CV_Error
* everything in one gapi_gpu_test.cpp
* fix warning
* remove kernel generation, add kernel string
* avoid generated code and ocl internal namespace
* fix misprint
* c_str
* dnn/Vulkan: don't init Vulkan runtime if using other backend/target
Don't need to explictly call a init API but will automatically
init Vulkan environment the first time to use an VkCom object.
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
* dnn/Vulkan: depress compilier warning for "-Wsign-promo"
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
* Added caching of agents execution sequence
* Merged linesRead() and nextWindow() methods on FluidAgent in one method
* Added caching of input lines for fluid::View
* Added caching of output lines for fluid::Buffer
* Fixed GAPI_Assert to work in standalone mode
G-API: Doxygen class reference
* G-API Doxygen documentation: covered cv::GComputation
* G-API Doxygen documentation: added sections on compile arguments
* G-API Doxygen documentation: restructuring & more text
* Added new sections (organized API reference into it);
* Documented GCompiled, compile args, backends, etc.
* G-API Doxygen documentation: documented GKernelPackage and added group for meta
* G-API: First steps with tutorial
* G-API Tutorial: First iteration
* G-API port of anisotropic image segmentation tutorial;
* Currently works via OpenCV only;
* Some new kernels have been required.
* G-API Tutorial: added chapters on execution code, inspection, and profiling
* G-API Tutorial: make Fluid kernel headers public
For some reason, these headers were not moved to the public
headers subtree during the initial development. Somehow it even
worked for the existing workloads.
* G-API Tutorial: Fix a couple of issues found during the work
* Introduced Phase & Sqrt kernels, OCV & Fluid versions
* Extended GKernelPackage to allow kernel removal & policies on include()
All the above stuff needs to be tested, tests will be added later
* G-API Tutorial: added chapter on running Fluid backend
* G-API Tutorial: fix a number of issues in the text
* G-API Tutorial - some final updates
- Fixed post-merge issues after Sobel kernel renaming;
- Simplified G-API code a little bit;
- Put a conclusion note in text.
* G-API Tutorial - fix build issues in test/perf targets
Public headers were refactored but tests suites were not updated in time
* G-API Tutorial: Added tests & reference docs on new kernels
* Phase
* Sqrt
* G-API Tutorial: added link to the tutorial from the main module doc
* G-API Tutorial: Added tests on new GKernelPackage functionality
* G-API Tutorial: Extended InRange tests to cover 32F
* G-API Tutorial: Misc fixes
* Avoid building examples when gapi module is not there
* Added a volatile API disclaimer to G-API root documentation page
* G-API Tutorial: Fix perf tests build issue
This change came from master where Fluid kernels are still used
incorrectly.
* G-API Tutorial: Fixed channels support in Sqrt/Phase fluid kernels
Extended tests to cover this case
* G-API Tutorial: Fix text problems found on team review
cap_libv4l depends on an external library (libv4l) yet is still larger
(1966 loc vs 1822 loc).
It was initially introduced copy pasting cap_v4l in order to offload
various color conversions to libv4l.
However nowadays we handle most of the needed color conversions inside
OpenCV. Our own implementation is better tested and (probably) also
better performing. (as it can optionally leverage IPP/ OpenCL)
Currently cap_v4l is better maintained and generally the code is in
better shape. There is however an API
difference in getting unconverted frames:
* on cap_libv4l one need to set `CV_CAP_MODE_GRAY=1` or
`CV_CAP_MODE_YUYV=1`
* on cap_v4l one needs to set `CV_CAP_PROP_CONVERT_RGB=0`
the latter is more flexible though as it also allows accessing undecoded
JPEG images.
fixes#4563
[evolution] Stitching for OpenCV 4.0
* stitching: wrap Stitcher::create for bindings
* provide method for consistent stitcher usage across languages
* samples: add python stitching sample
* port cpp stitching sample to python
* stitching: consolidate Stitcher create methods
* remove Stitcher::createDefault, it returns Stitcher, not Ptr<Stitcher> -> inconsistent API
* deprecate cv::createStitcher and cv::createStitcherScans in favor of Stitcher::create
* stitching: avoid anonymous enum in Stitcher
* ORIG_RESOL should be double
* add documentatiton
* stitching: improve documentation in Stitcher
* stitching: expose estimator in Stitcher
* remove ABI hack
* stitching: drop try_use_gpu flag
* OCL will be used automatically through T-API in OCL-enable paths
* CUDA won't be used unless user sets CUDA-enabled classes manually
* stitching: drop FeaturesFinder
* use Feature2D instead of FeaturesFinder
* interoperability with features2d module
* detach from dependency on xfeatures2d
* features2d: fix compute and detect to work with UMat vectors
* correctly pass UMats as UMats to allow OCL paths
* support vector of UMats as output arg
* stitching: use nearest interpolation for resizing masks
* fix warnings
* Support for Matx read/write by FileStorage
* Only empty filestorage read now produces default Matx. Split Matx IO test into smaller units. Test checks for exception thrown if reading a Mat into a Matx of different size.
* moved DIS optical flow from opencv_contrib to opencv, moved TVL1 from opencv to opencv_contrib
* fixed compile warning
* TVL1 optical flow example moved to opencv_contrib
* significantly reduced OpenCV binary size by disabling IPP calls in some OpenCV functions: Sobel, Scharr, medianBlur, GaussianBlur, filter2D, mean, meanStdDev, norm, sum, minMaxIdx, sort.
* re-enable IPP in norm, since it's much faster (without adding too much space overhead)
* removed C API in the following modules: photo, video, imgcodecs, videoio
* trying to fix various compile errors and warnings on Windows and Linux
* continue to fix compile errors and warnings
* continue to fix compile errors, warnings, as well as the test failures
* trying to resolve compile warnings on Android
* Update cap_dc1394_v2.cpp
fix warning from the new GCC
G-API GPU-OpenCL backend (#13008)
* gpu/ocl backend core
* accuracy tests added and adjusted + license headers
* GPU perf. tests added; almost all adjusted to pass
* all tests adjusted and passed - ready for pull request
* missing license headers
* fix warning (workaround RGB2Gray)
* fix c++ magic
* precompiled header
* white spaces
* try to fix warning and blur test
* try to fix Blur perf tests
* more alignments with the latest cpu backend
* more gapi tests refactoring + 1 more UB issue fix + more informative tolerance exceed reports
* white space fix
* try workaround for SumTest
* GAPI_EXPORTS instead CV_EXPORTS
This is a workaround for GPU hang on heavy convolution workload (> 10 GFLOPS).
e.g. ResNet101_DUC_HDC
For the long time task, vkWaitForFences() return without error but next call on
vkQueueSubmit() return -4, i.e. "VK_ERROR_DEVICE_LOST" and driver reports GPU hang.
Need more investigation on root cause of GPU hang and need to optimize convolution shader
to reduce process time.
* integrated the new C++ persistence; removed old persistence; most of OpenCV compiles fine! the tests have not been run yet
* fixed multiple bugs in the new C++ persistence
* fixed raw size of the parsed empty sequences
* [temporarily] excluded obsolete applications traincascade and createsamples from build
* fixed several compiler warnings and multiple test failures
* undo changes in cocoa window rendering (that was fixed in another PR)
* fixed more compile warnings and the remaining test failures (hopefully)
* trying to fix the last little warning
G-API: Introduce new `reshape()` API (#12990)
* Moved initFluidUnits, initLineConsumption, calcLatency, calcSkew to separate functions
* Added Fluid::View::allocate method (moved allocation logic from constructor)
* Changed util::zip to util::indexed, utilized collectInputMeta in GFluidExecutable constructor
* Added makeReshape method to FluidExecutable
* Removed m_outputRoi from GFluidExecutable
* Added reshape feature
* Added switch of resize mapper if agent ratio was changed
* Added more TODOs and renamed a function
* G-API reshape(): add missing `override` specifiers
Fix warnings on all platforms
Made scale parameter optional for mul kernel wrapper (#12949)
* Added missed operator*(GMat, GMat). Made scale parameter optional for mul kernel.
* Fixed perf test for mul(GMat, GMat) kernel
* Removed operator*(GMat, GMat) as not needed
* dnn: Add a Vulkan based backend
This commit adds a new backend "DNN_BACKEND_VKCOM" and a
new target "DNN_TARGET_VULKAN". VKCOM means vulkan based
computation library.
This backend uses Vulkan API and SPIR-V shaders to do
the inference computation for layers. The layer types
that implemented in DNN_BACKEND_VKCOM include:
Conv, Concat, ReLU, LRN, PriorBox, Softmax, MaxPooling,
AvePooling, Permute
This is just a beginning work for Vulkan in OpenCV DNN,
more layer types will be supported and performance
tuning is on the way.
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
* dnn/vulkan: Add FindVulkan.cmake to detect Vulkan SDK
In order to build dnn with Vulkan support, need installing
Vulkan SDK and setting environment variable "VULKAN_SDK" and
add "-DWITH_VULKAN=ON" to cmake command.
You can download Vulkan SDK from:
https://vulkan.lunarg.com/sdk/home#linux
For how to install, see
https://vulkan.lunarg.com/doc/sdk/latest/linux/getting_started.htmlhttps://vulkan.lunarg.com/doc/sdk/latest/windows/getting_started.htmlhttps://vulkan.lunarg.com/doc/sdk/latest/mac/getting_started.html
respectively for linux, windows and mac.
To run the vulkan backend, also need installing mesa driver.
On Ubuntu, use this command 'sudo apt-get install mesa-vulkan-drivers'
To test, use command '$BUILD_DIR/bin/opencv_test_dnn --gtest_filter=*VkCom*'
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
* dnn/Vulkan: dynamically load Vulkan runtime
No compile-time dependency on Vulkan library.
If Vulkan runtime is unavailable, fallback to CPU path.
Use environment "OPENCL_VULKAN_RUNTIME" to specify path to your
own vulkan runtime library.
Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
* dnn/Vulkan: Add a python script to compile GLSL shaders to SPIR-V shaders
The SPIR-V shaders are in format of text-based 32-bit hexadecimal
numbers, and inserted into .cpp files as unsigned int32 array.
* dnn/Vulkan: Put Vulkan headers into 3rdparty directory and some other fixes
Vulkan header files are copied from
https://github.com/KhronosGroup/Vulkan-Docs/tree/master/include/vulkan
to 3rdparty/include
Fix the Copyright declaration issue.
Refine OpenCVDetectVulkan.cmake
* dnn/Vulkan: Add vulkan backend tests into existing ones.
Also fixed some test failures.
- Don't use bool variable as uniform for shader
- Fix dispathed group number beyond max issue
- Bypass "group > 1" convolution. This should be support in future.
* dnn/Vulkan: Fix multiple initialization in one thread.
This is a fix to the signature of static function
collectCalibrationData() and clean-up for #12772. Since fallback scheme
in calibration method selection is not used anymore. As an input
parameter, iFixedPoint should be passed by value according to the OpenCV
coding style guide.
* Renamed Sobel operator GAPI kernel to match with OpenCV naming rules
* Fixed perf tests
* Small refactoring to check CI issue
* Refactored alignment for kernel wrappers in imgproc.hpp
* Update videoio.hpp
add VideoCapturePropertie for clossbar input pin setting
* Update cap_dshow.cpp
For some kind of capture card, such as "avermedia cv710 " , it use SerialDigital as input pin and so it can not work.
Here added new PhysicalConnectorType enumeration: PhysConn_Video_YRYBY and PhysConn_Video_SerialDigital to support it.
And also provide new property parameter CAP_CROSSBAR_INPIN_TYPE to set the crossbar input pin type which will be used in videoInput::start(int deviceID, videoDevice *VD):
" if(VD->useCrossbar)
{
DebugPrintOut("SETUP: Checking crossbar\n");
routeCrossbar(&VD->pCaptureGraph, &VD->pVideoInputFilter, VD->connection, CAPTURE_MODE);
}
"
And at last ,fixed one issue for function setSizeAndSubtype, added code
pVih->rcSource.top = pVih->rcSource.left = pVih->rcTarget.top =pVih->rcTarget.left=0;
pVih->rcSource.right = pVih->rcTarget.right= attemptWidth;
pVih->rcSource.bottom = pVih->rcTarget.bottom = attemptHeight;
without these code , rcSource and rcTarget will keeping use default resolution and cause fail in hr = VD->streamConf->SetFormat(VD->pAmMediaType) and cannot find suitable MediaType.
Tested with python3 and mfc (Avermedia cv710)
Python3 code:
import cv2
print("test cv")
cap=cv2.VideoCapture(0)
cap.set(5,60)
cap.set(3,1920)
cap.set(4,1080)
cap.set(31,6)
ret,img=cap.read()
cv2.namedWindow("cap",cv2.WINDOW_NORMAL)
cv2.resizeWindow("cap",960,640);
while True:
ret,img=cap.read()
if ret==False:
continue
cv2.imshow("cap",img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
MFC code:
void CcvtestDlg::OnBnClickedButton1()
{
VideoCapture cap(0);
cap.set(CAP_PROP_FRAME_WIDTH, 1920);
cap.set(CAP_PROP_FRAME_HEIGHT, 1080);
cap.set(CAP_CROSSBAR_INPIN_TYPE , 6);
Mat img;
namedWindow("test", WINDOW_NORMAL);
resizeWindow("test", 960, 640);
while (1)
{
if (cap.read(img))
{
imshow("test", img);
if ('q' ==waitKey(1))
break;
}
}
destroyAllWindows();
cap.release();
}
* Update cap_dshow.cpp
* Update videoio.hpp
move enum value of CAP_CROSSBAR_INPIN_TYPE to the end of list
* Update videoio.hpp
* Update cap_dshow.cpp
removed trailing whitespace
* Update test_camera.cpp
Add test for capture device using PhysConn_Video_SerialDigital as crossbar input pin
* Update test_camera.cpp
Correction of misunderstanding about how to add test case.
More accurate pinhole camera calibration with imperfect planar target (#12772)
43 commits:
* Add derivatives with respect to object points
Add an output parameter to calculate derivatives of image points with
respect to 3D coordinates of object points. The output jacobian matrix
is a 2Nx3N matrix where N is the number of points.
This commit introduces incompatibility to old function signature.
* Set zero for dpdo matrix before using
dpdo is a sparse matrix with only non-zero value close to major
diagonal. Set it to zero because only elements near major diagonal are
computed.
* Add jacobian columns to projectPoints()
The output jacobian matrix of derivatives with respect to coordinates of
3D object points are added. This might break callers who assume the
columns of jacobian matrix.
* Adapt test code to updated project functions
The test cases for projectPoints() and cvProjectPoints2() are updated to
fit new function signatures.
* Add accuracy test code for dpdo
* Add badarg test for dpdo
* Add new enum item for new calibration method
CALIB_RELEASE_OBJECT is used to whether to release 3D coordinates of
object points. The method was proposed in: K. H. Strobl and G. Hirzinger.
"More Accurate Pinhole Camera Calibration with Imperfect Planar Target".
In Proceedings of the IEEE International Conference on Computer Vision
(ICCV 2011), 1st IEEE Workshop on Challenges and Opportunities in Robot
Perception, Barcelona, Spain, pp. 1068-1075, November 2011.
* Add releasing object method into internal function
It's a simple extension of the standard calibration scheme. We choose to
fix the first and last object point and a user-selected fixed point.
* Add interfaces for extended calibration method
* Refine document for calibrateCamera()
When releasing object points, only the z coordinates of the
objectPoints[0].back is fixed.
* Add link to strobl2011iccv paper
* Improve documentation for calibrateCamera()
* Add implementations of wrapping calibrateCamera()
* Add checking for params of new calibration method
If input parameters are not qualified, then fall back to standard
calibration method.
* Add camera calibration method of releasing object
The current implementation is equal to or better than
https://github.com/xoox/calibrel
* Update doc for CALIB_RELEASE_OBJECT
CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with
potentially less precise and less stable in some rare cases.
* Add RELEASE_OBJECT calibration to tutorial code
To select the calibration method of releasing object points, a command
line parameter `-d=<number>` should be provided.
* Update tutorial doc for camera_calibration
If the method of releasing object points is merged into OpenCV. It will
be expected to be firstly released in 4.1, I think.
* Reduce epsilon for cornerSubPix()
Epsilon of 0.1 is a bigger one. Preciser corner positions are required
with calibration method of releasing object.
* Refine camera calibration tutorial
The hypothesis coordinates are used to indicate which distance must be
measured between two specified object points.
* Update sample calibration code method selection
Similar to camera_calibration tutorial application, a command line
argument `-dt=<number>` is used to select the calibration method.
* Add guard to flags of cvCalibrateCamera2()
cvCalibrateCamera2() doesn't accept CALIB_RELEASE_OBJECT unless overload
interface is added in the future.
* Simplify fallback when iFixedPoint is out of range
* Refactor projectPoints() to keep compatibilities
* Fix arg string "Bad rvecs header"
* Read calibration flags from test data files
Instead of being hard coded into source file, the calibration flags will
be read from test data files.
opencv_extra/testdata/cv/cameracalibration/calib?.dat must be sync with
the test code.
* Add new C interface of cvCalibrateCamera4()
With this new added C interface, the extended calibration method with
CALIB_RELEASE_OBJECT can be called by C API.
* Add regression test of extended calibration method
It has been tested with new added test data in xoox:calib-release-object
branch of opencv_extra.
* Fix assertion in test_cameracalibration.cpp
The total number of refined 3D object coordinates is checked.
* Add checker for iFixedPoint in cvCalibrateCamera4
If iFixedPoint is out of rational range, fall back to standard method.
* Fix documentation for overloaded calibrateCamera()
* Remove calibration flag of CALIB_RELEASE_OBJECT
The method selection is based on the range of the index of fixed point.
For minus values, standard calibration method will be chosen. Values in
a rational range will make the object-releasing calibration method
selected.
* Use new interfaces instead of function overload
Existing interfaces are preserved and new interfaces are added. Since
most part of the code base are shared, calibrateCamera() is now a
wrapper function of calibrateCameraRO().
* Fix exported name of calibrateCameraRO()
* Update documentation for calibrateCameraRO()
The circumstances where this method is mostly helpful are described.
* Add note on the rigidity of the calibration target
* Update documentation for calibrateCameraRO()
It is clarified that iFixedPoint is used as a switch to select
calibration method. If input data are not qualified, exceptions will be
thrown instead of fallback scheme.
* Clarify iFixedPoint as switch and remove fallback
iFixedPoint is now used as a switch for calibration method selection. No
fallback scheme is utilized anymore. If the input data are not
qualified, exceptions will be thrown.
* Add badarg test for object-releasing method
* Fix document format of sample list
List items of same level should be indented the same way. Otherwise they
will be formatted as nested lists by Doxygen.
* Add brief intro for objectPoints and imagePoints
* Sync tutorial to sample calibration code
* Update tutorial compatibility version to 4.0
* G-API Documentation: first submission
This PR introduces a number of new OpenCV documentation chapters for
Graph API module.
In particular, the following topics are covered:
- Introduction & background information;
- High-level design overview;
- Kernel API;
- Pipeline example.
All changes are done in Markdown files, no headers, etc modified.
Doxygen references for main API classes will be added later.
Also, a tutorial will be introduced soon (in the common Tutorials place)
* G-API Documentation - fix warnings & trailing whitespaces
* G-API Documentation: address review issues
* G-API Documentation: export code snippets to compileable files
* gapi: move documentation samples
* rewrote the line segment intersection function to make the static analyzer happy
* fixed bug with improper "no intersection" detection in some of corner cases
* fixed bug with improper "no intersection" detection in some of corner cases
Several Resize optimizations count on fetching multiple input lines at
once to do interpolation more efficiently.
At the moment, Fluid backend supports only LPI=1 for Resize kernels.
This patch introduces scheduling support for Resizes with LPI>1 and
covers these cases with new tests.
The support is initially written by Ruslan Garnov.
* hide use of std::mutex from /clr compilation under Visual Studio
C++11 <mutex> is not available when compiling with /clr under Visual Studio, thus opencv cannot be easily included.
It is fixed by making a CEEMutex wrapper class, around an opaque implementation using std::mutex internally
* fixed compilation outside of Visual Studio
fixed compilation outside of Visual Studio by avoiding some macros
* fixed indentation, prepare getting rid of CEEMutex/CEELockGuard
fixed indentation
After discussion, CEEMutex and CEELockGuard can be totally removed, letting the developer in a /clr context to provide his own implementation
* remove CEEMutex/CEELockGuard
* Update G-API code base to 27-Sep-18
Changes mostly improve standalone build support
* G-API code base update 28-09-2018
* Windows/Documentation warnings should be fixed
* Fixed stability issues in Fluid backend
* Fixed precompiled headers issues in G-API source files
* G-API code base update 28-09-18 EOD
* Fixed several static analysis issues
* Fixed issues found when G-API is built in a standalone mode
- avoid updating of input image during equalizeHist() call
- avoid for() with double variable (use 'int' instead)
- more CV_Check*() macros
- use Mat_<T>, Matx
- static for local variables
* G-API Initial code upload
* Update G-API code base to Sep-24-2018
* The majority of OpenCV buildbot problems was addressed
* Update G-API code base to 24-Sep-18 EOD
* G-API code base update 25-Sep-2018
* Linux warnings should be resolved
* Documentation build should become green
* Number of Windows warnings should be reduced
* Update G-API code base to 25-Sep-18 EOD
* ARMv7 build issue should be resolved
* ADE is bumped to latest version and should fix Clang builds for macOS/iOS
* Remaining Windows warnings should be resolved
* New Linux32 / ARMv7 warnings should be resolved
* G-API code base update 25-Sep-2018-EOD2
* Final Windows warnings should be resolved now
* G-API code base update 26-Sep-2018
* Fixed issues with precompiled headers in module and its tests
findChessboardCornersSB: speed improvements (#12615)
* chessboard: fix do not modify const image
* chessboard: speed up scale space using parallel_for
* chessboard: small improvements
* chessboard: speed up board growing using parallel_for
* chessboard: add flags for tuning detection
* chessboard: fix compiler warnings
* chessborad: change flag name to CALIB_CB_EXHAUSTIVE
This also fixes a typo
* chessboard: fix const ref + remove to_string
Before this fix, the code would fail if only standard deviations of
extrinsic parameters are requested. While standard deviations matrix
should be computed if any set of standard deviations is requested. A
variable is added to represent this case.
* add new chessboard detector
The chessboar detector is based on the paper.
Accurate Detection and Localization of Checkerboard Corners for
Calibration Alexander Duda, Udo Frese
British Machine Vision Conference, o.A., 2018.
It utilizes point symmetry of checkerboard corners in combination with a
localized Radon transform approximated by box filters to achieve high
performance even on large images. Here, tests have shown that the
ability to localize checkerboard corners is close to the theoretical
limit of 1/100 of a pixel while being considerably less sensitive
to image noise than standard methods.
* chessboard: add reference to bibtex file
* chessboard: add dependency to opencv_flann
* fix: test chesscorners. It is valid to return an empty list
In case no chessboard was detected it should be valid for the detector
to return an empty list.
For simplifcation, it should be allowed to return any number of corners
if they are flagged as not found.
* fix: opencv.bib remove empty lines
* fix: doc findChessboardCorners replace cvSize with cv::Size
* chessboard tests: factor out logic selecting detector
* chessboard: add unit test for findChessboardCorners2
This is includes a new chessboard generator which supports subpix
corners with high accuracy by wrapping an optimal chessboard using
wrapPerspective.
* fix: chessboard unit test - overwrite of default parameter flag of findCirclesGrid
* chessboard: remove trailing whitespace
* chessboard: fix debug drawing
* chessboard: fix some issues during code review
* chessboard: normalize asymmetric chessboard
* chessboard: fix float double warning
* remove trailing whitespace
* chessboards: fix compiler warnings
* chessboards: fix compiler warnings
* checkerboard: some performance improvements
* chessboard: remove NULL macros for language bindinges from internal headers
* chessboard: shorten license terms
* chessboard: remove unused internal method
* chessboard: set helper functions to static
* chessboard: fix normalizePoints1D using unshifted points
* chessboard: remove wrongly copied text
* chessboard: use CV_CheckTypeEQ macro
* chessboard: comment all NaN checks
* chessboard: use consistent color conversion
* chessboard: use CheckChannelEQ macro
* chessboard: assume gray color image for internal methods
* chessboard: use std::swap
* chessboard: use Mat.dataend
* chessboard: fix compiler warnings
* chessboard: replace some checks witch CV_CHECK macro
* chessboard: fix comparison function for partial sort
* chessboard: small cleanup
* chessboard: use short license header
* chessboard: rename findChessboard2 to findChessboardSB
* chessboard: fix type in unit test
* added basic support for CV_16F (the new datatype etc.). CV_USRTYPE1 is now equal to CV_16F, which may break some [rarely used] functionality. We'll see
* fixed just introduced bug in norm; reverted errorneous changes in Torch importer (need to find a better solution)
* addressed some issues found during the PR review
* restored the patch to fix some perf test failures
* bgr2gray 8u fixed to be in conformance with IPP code
* coefficients fixed so their sum is 32768
* java test for CascadeDetect fixed: equalizeHist added
fix some errors found by static analyzer. (#12391)
* fix possible divided by zero and by negative values
* only 4 elements are used in these arrays
* fix uninitialized member
* use boolean type for semantic boolean variables
* avoid invalid array index
* to avoid exception and because base64_beg is only used in this block
* use std::atomic<bool> to avoid thread control race condition
* Add HPX backend for OpenCV implementation
Adds hpx backend for cv::parallel_for_() calls respecting the nstripes chunking parameter. C++ code for the backend is added to modules/core/parallel.cpp. Also, the necessary changes to cmake files are introduced.
Backend can operate in 2 versions (selectable by cmake build option WITH_HPX_STARTSTOP): hpx (runtime always on) and hpx_startstop (start and stop the backend for each cv::parallel_for_() call)
* WIP: Conditionally include hpx_main.hpp to tests in core module
Header hpx_main.hpp is included to both core/perf/perf_main.cpp and core/test/test_main.cpp.
The changes to cmake files for linking hpx library to above mentioned test executalbles are proposed but have issues.
* Add coditional iclusion of hpx_main.hpp to cpp cpu modules
* Remove start/stop version of hpx backend
* video: remove duplicate RANSAC code
* remove RANSAC code video module. The module now uses RANSAC estimators from calib3d.
* deprecate estimateRigidTransform
* replace internal usage of deprecated estimateRigidTransform
* remove from wrappers
* replace usage in shape module. shape module now links to calib3d instead of video module.
* reprecate also C API version
* remove cvEstimateRigidTransform
* supress deprecated warnings in estimateRigidTransform test
* the function is now deprecated
* created new decoder and encoder for PFM
pfm file format stores binary RGB or grayscale float images.
* added test for pfm codec
* replaced large with short licence header
* little/big-endian-check is now compile time
* fixed width/height confusion, improved big/little endian recognition, fixed scaling issue and Improved signature check
* adapted tests to handle float images well
* removed data-dependency: lena.pfm
the lena image is now loaded is pam and converted to pfm.
* fixed bug in endianess detection macro
* Added endianess detection for android and win
* removed fancy endianess detection
endianess detection will be implemented in cmake scripts soonish.
* fixed minor warnings
* fixed stupid elif defined bug
* silenced some implicit cast warnings
* replaced std::to_string with std::stringstream solution
std::to_string variant did not build on android.
* replaced new endianess macros with existing ones
* improved readability
* a part of https://github.com/opencv/opencv/pull/11364 by Tetragramm. Rewritten and extended findNonZero & PSNR to support more types, not just 8u.
* fixed compile & doxygen warnings
* fixed small bug in findNonZero test
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* Include ELA example
* did some code cleanup
* fixed compile error
this enables the usage of current sensors, while dropping support for
legacy devices, see:
https://github.com/IntelRealSense/librealsense#overview
Given limited resources, and that the legacy sensors where not that
great, I think we should focus on v2.
description:Create a report to help us reproduce and fix the bug
labels:["bug"]
body:
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value:>
#### Thank you for contributing! Before reporting a bug, please have a look at the [FAQ](https://github.com/opencv/opencv/wiki/FAQ), make sure the issue has no duplicate and hasn't been already addressed by searching through [the existing and past issues](https://github.com/opencv/opencv/issues?page=1&q=is%3Aissue+sort%3Acreated-desc).
- type:textarea
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Please provide the following system information to help us diagnose the bug. For example:
// example for c++ user
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Operating System / Platform: Ubuntu 20.04
Compiler & compiler version: GCC 9.3.0
// example for python user
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Test data: [image](https://link/to/the/image), [model.onnx](htts://link/to/the/onnx/model)
validations:
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