Add CAP_PROP_IMAGE_SEQ_START #28844
Resolves https://github.com/opencv/opencv/issues/28843
New CAP_PROP_IMAGE_SEQ_START as an open only property for setting the first frame index when a VideoCap is opening with pattern, squashes test_images TODO.
`CAP_FFMPEG`: forwarded to the image2 demuxers "start_number" option.
`CAP_IMAGES`: Now a WithParams variant so the value reaches open() before probe runs, replaces 0 or 1 auto probe for sequence start.
Property is opt in so default behavior is not affected.
Please note that G_STREAMER is not considered here as I think its out of scope, it already has a "start-index" property and its backend is driven by the pipeline strings rather then these printf patterns.
If an alternative solution is preferred that will not involve a new property or promoting CAP_IMAGES to a "WithParams" variant I don't mind implementing.
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Bump some calib3d files to C++ #28825
This is just copy/pasting files from 5.x (first commit) and applying some light patch for compilation (second commit).
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Avoid lossy Latin-1 conversions when creating/looking up Qt HighGUI windows and convert C-string entry points to UTF-8 explicitly. This fixes non-ASCII title handling paths that could lead to mismatched window lookup and silent display failures.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
objdetect: clear stale outputs in CharucoDetector::detectDiamonds #28818
## Summary
- clear `diamondCorners`/`diamondIds` outputs at the beginning of `CharucoDetector::detectDiamonds`
- prevent stale detections from previous calls when the current call has fewer than 4 markers or finds no diamonds
- add a regression test that pre-fills outputs, calls `detectDiamonds` with 3 markers, and verifies outputs are empty
Fixes#28783.
## Testing
- built `opencv_test_objdetect` locally
- ran `opencv_test_objdetect --gtest_filter=Charuco.detectDiamondsClearsOutputsWithLessThanFourMarkers`
- result: PASS
Multiscale ECC #28802
OpenCV Extra: https://github.com/opencv/opencv_extra/pull/1338
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Previously, OpenCL in-place flip kernels (rows/cols/both) could produce
incorrect results compared to the CPU implementation on strict OpenCL
drivers such as Mesa. The kernels relied on implicit load–load–store–store
(LLSS) ordering when src and dst alias, which is not guaranteed by the
OpenCL memory model and may be reordered.
Some vendor drivers happened to preserve the expected ordering, masking
the issue, but Mesa correctly exposes the undefined behavior.
This change introduces dedicated in-place flip kernels that:
- Explicitly detect in-place execution (src == dst)
- Stage data through local memory tiles
- Enforce correct ordering with work-group barriers
- Avoid global memory read/write aliasing hazards
The non in-place path is unchanged.
With this fix, OpenCL in-place flip produces correct and consistent results
across drivers, matches CPU behavior, and complies with the OpenCL memory
model.
Signed-off-by: jiajia Qian <jiajia.qian@nxp.com>
Avfoundation fractional fps seek fix#28833
Accompanied by PR on [opencv_extra](https://github.com/opencv/opencv_extra/pull/1345)
Fixes https://github.com/opencv/opencv/issues/28831
AVFoundation backend seeking slowly drifts for any video which has a non-integer frame rate.
Narrowing of a float `mAssetTrack.nominalFrameRate` to int32_t means fractional rates are treated as integer when seeking by frame number.
Solution implemented in this branch is to use the tracks native rational frame duration when seeking (and available).
I've also included an AVF only test case which uses a new test file in opencv_extra. This test just compares the video caps expected ms vs actual for a known rate file (23.976).
Could consider extending this test to more then just AVF, as from what I can see there are no fractional rate tests / files.
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imgcodecs(png): support cICP metadata for imreadWithMetadata() #28615
Close https://github.com/opencv/opencv/issues/28606
Related https://github.com/opencv/opencv/pull/27741 (support for imwriteWithMetadata)
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The existing 2-pass cross-check implementation requires both forward and
reverse distance computations on GPU, followed by CPU-side filtering.
This adds a single-pass kernel using int64 atomics to eliminate the
reverse pass. The BruteForceMatch_CrossCheckMatch kernel performs forward
matching and tracks best train->query mappings in one GPU pass, reducing
memory transfers. Falls back to 2-pass approach on devices without
cl_khr_int64_base_atomics extension.
Tested on NVIDIA RTX 5060 Ti: 1.65x-1.97x faster than 2-pass GPU,
3.49x-7.33x faster than CPU at 640x480 to 1920x1080 resolutions.
Allow TIFF compression schemes for 32F#28785
Related to [https://github.com/opencv/opencv/issues/28775](https://github.com/opencv/opencv/issues/28775)
Previously, only 32FC3+SGILOG could be specified for TIFF encoding. But when floats use quantization, compression schemes can be efficient even on 32F data. This PR will allow them.
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I just don't know what kind of accuracy/performance tests should be added.
Fixes redundant code in Cloning::illuminationChange() which performed
unnecessary copyTo operations. This satisfies Issue #22056.
Testing: No functional changes made; logic identical to before.
Resolves#22056
core(opencl): fix inplace transpose race by enforcing LLSS ordering via local barrier #28686
The former inplace transpose implementation allowed a reordering of global-memory operations across work-items. Specifically, the intended LLSS (Load–Load–Store–Store) access pattern could be reordered by the GPU into LSLS (Load–Store–Load–Store), causing partially written tiles to be observed by other work-items and producing incorrect output.
This patch introduces a tiled LDS-based algorithm and adds an explicit:
barrier(CLK_LOCAL_MEM_FENCE);
between the load and store phases.
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python: fix segfault on 0-channel numpy array input #28747
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N/A: a Python unit test is added in `modules/python/test/test_mat.py`. No external test data required.
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N/A: this is a bug fix, not a new feature. No documentation update needed.
### Problem
Passing a numpy array with shape `(H, W, 0)` (0 channels) to any OpenCV function that accepts a `Mat` argument (e.g. `cv2.resize`, `cv2.warpAffine`, `cv2.blur`) causes a **segfault**.
**Reproducer:**
```python
import cv2
import numpy as np
arr = np.zeros((100, 100, 0), np.uint8)
cv2.resize(arr, (200, 200)) # segfault
```
### Root Cause
In `modules/python/src2/cv2_convert.cpp`, the numpy→Mat conversion checks channel validity only against `CV_CN_MAX` (upper bound):
```cpp
if (channels > CV_CN_MAX) // channels=0 passes this check
```
With `channels=0`, `CV_MAKETYPE(0, 0)` produces `type=-8`, which corrupts the Mat's internal type field and causes undefined behavior downstream.
### Fix
Extend the check to also reject `channels < 1`:
```cpp
if (channels < 1 || channels > CV_CN_MAX)
```
**After fix:**
```
cv2.error: src unable to wrap channels, invalid count (0, must be in [1, 512])
```
### Notes
- This affects all functions that accept a `Mat` input, not just `cv2.resize`
- The same bug exists in the `5.x` branch
- A 0-channel array has no valid OpenCV Mat representation; rejecting it with a clear error is the correct behavior and poses no backward-compatibility risk (the previous behavior was a crash)
videoio(gstreamer): fix timestamp drift and color negotiation on Apple #28535
This commit addresses two issues on macOS with Apple M3 hardware:
1. Replaces floating-point timestamp math with gst_util_uint64_scale_int to ensure nanosecond precision.
2. Explicitly forces I420 format in the encoding profile to prevent hardware encoder negotiation failure.
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core: add NEON implementation for rotate function #28609
- This PR adds a NEON intrinsics-based implementation for the rotate function in matrix_transform.cpp for Windows-ARM64.
- The optimized implementation uses ARM NEON intrinsics to accelerate the internal transpose step used by the rotate function.
- In the x64 architecture, the rotate operation benefits from IPP-based optimized implementations. However, on ARM64, the execution falls back to the scalar implementation, which results in lower performance.
- To achieve performance parity with x64, a NEON-based SIMD implementation has been added for ARM64.
- After introducing these changes, the rotate function showed noticeable performance improvements on ARM64 platforms.
<img width="1009" height="817" alt="image" src="https://github.com/user-attachments/assets/8bec0041-b19c-4fc8-9103-532746224515" />
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dnn: fix Resize initNgraph for two-input case #28724
## Summary
Fixes the issue #28707
When a Resize/Upsample layer has two inputs, the data tensor and a reference tensor whose **shape** defines the output spatial size, the OpenVINO/NGRAPH backend's `initNgraph()` was ignoring `nodes[1]` entirely and relying solely on the `outHeight`/`outWidth` member variables.
These variables are set by `finalize()` from the pre-computed output blob dimensions. However, when the output shape is determined dynamically at runtime from the second input, `finalize()` sets them from the live tensor, but the OpenVINO backend calls `initNgraph()` to build a static compiled graph. If the member variables are 0 at that point, the compiled `Interpolate` node gets hardcoded with `{0, 0}` output dimensions, causing CV_Assert failure: {N,C,0,0} vs {N,C,H2,W2}
BFMatcher::match() with crossCheck=true previously skipped the OCL
dispatch in knnMatchImpl entirely, falling back to CPU even when UMat
inputs and an OpenCL device were available. This adds
ocl_matchWithCrossCheck() for CV_32FC1 descriptors (e.g. SIFT, SURF):
both the forward and reverse nearest-neighbour passes run on the GPU
via the existing ocl_matchSingle() kernel, then the cross-check filter
runs on the CPU. Only two small index arrays (1×N ints) are downloaded
— the O(N²×D) distance work stays on the device.
The OCL dispatch in knnMatchImpl is also refactored to unify the
Mat/UMat train collection selection before branching on crossCheck.
On a NVIDIA RTX 3060 with SIFT descriptors the OCL path is 6–9×
faster than CPU at 2k–10k features per image. Binary descriptors
(ORB, BRIEF — CV_8U) are unaffected; the existing type guard in
ocl_matchSingle keeps them on the CPU path as before.
Also adds a correctness test (Features2d_BFMatcher_CrossCheck) and an
OCL perf test (BruteForceMatcherFixture/MatchCrossCheck).
Fixes#28396 : out-of-bounds read in SIMD type conversion #28397Fixes#28396Fixes#27080
The vx_load_expand function in WASM intrinsics was using
wasm_v128_load which always loads a full 128-bit register
(16 bytes), even when the function only needed 8 elements.
For example, when converting uint8 to float32:
- vx_load_expand needs 8 uint8 elements
- But wasm_v128_load reads 16 bytes from memory
- This causes an 8-byte out-of-bounds read
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Optimize calibrateCamera with Schur‑complement LM and parallel Jacobian accumulation #28461
## Summary
- Optimized `calibrateCamera` for faster runtime without changing outputs using Schur‑complement LM, Parallel Jacobian accumulation, alongside other optimizations.
- Reduced time complexity from O(n^3) to O(n)
- Add a perf test that uses a 500-image chessboard dataset for performance testing.
## Performance
<img width="1200" height="800" alt="base_vs_fast_results" src="https://github.com/user-attachments/assets/6dafa19f-f9cb-4f7f-ba40-0940373712e8" />
<img width="1200" height="800" alt="fast_vs_ceres_results" src="https://github.com/user-attachments/assets/7157af27-8a2b-4810-8b53-3cc9972a8493" />
<img width="1200" height="800" alt="base_vs_fast_param_deviation" src="https://github.com/user-attachments/assets/fe4f954c-34f9-4b9a-b1b2-46e4c76ce08c" />
[Testing repo
](https://github.com/Ron12777/OpenCV-benchmarking)
## Testing
- All local tests pass
## Related
- [opencv_extra PR with test images](https://github.com/opencv/opencv_extra/pull/1312)
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Convert exportResource() and loadResource() to use try-with-resources
to ensure InputStream, FileOutputStream, and ByteArrayOutputStream are
properly closed even when exceptions occur.
Also remove printStackTrace() in exportResource(), as the exception is
already rethrown as CvException with the original exception details.
Signed-off-by: ffccites <99155080+PDGGK@users.noreply.github.com>
Replace System.exit(-1) with exceptions in HighGui.java (#28696) #28699
## Summary
Library code should never call System.exit() as it kills the entire JVM. Replaced all 3 instances with appropriate exceptions.
Closes#28696
## Changes
- `imshow()` with empty image: `System.exit(-1)` -> `throw new IllegalArgumentException("Image is empty")`
- `waitKey()` with no windows: `System.exit(-1)` -> `throw new IllegalStateException("No windows created. Call imshow() first")`
- `waitKey()` with null window image: `System.exit(-1)` -> `throw new IllegalStateException("No image set for window: ... Call imshow() first")`
- `InterruptedException` catch: `printStackTrace()` -> `Thread.currentThread().interrupt()`