Documentation fixes, Added How to use pre-built opencv doc #29288
closes: https://github.com/opencv/opencv/issues/29263
co-authored by: @kirtijindal14 @Akansha-977
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[FOLLOW UP] : Documentation optimizations for the new Sphinx structure #29220
### Pull Request Readiness Checklist
This PR serves as a follow-up to the new documentation system introduced in [#29206](https://github.com/opencv/opencv/pull/29206)
Co-authored by: @abhishek-gola @kirtijindal14 @Akansha-977 @Prasadayus @varun-jaiswal17
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OpenCV New Documentation #29206
This PR introduces end to end working new Documentation in OpenCV.
Co-authored by: @abhishek-gola @omrope79 @Akansha-977 @Prasadayus @varun-jaiswal17
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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>
Introduce option to generate Java code with finalize() or Cleaners interface #28159
Closes https://github.com/opencv/opencv/issues/22260
Replaces https://github.com/opencv/opencv/pull/23467
The PR introduce configuration option to generate Java code with Cleaner interface for Java 9+ and old-fashion finalize() method for old Java and Android. Mat class and derivatives are manually written. The PR introduce 2 base classes for it depending on the generator configuration.
Pros:
1. No need to implement complex and error prone cleaner on library side.
2. No new CMake templates, easier to modify code in IDE.
Cons:
1. More generator branches and different code for modern desktop and Android.
TODO:
- [x] Add Java version check to cmake
- [x] Use Cleaners for ANDROID API 33+
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- Added vector_MatShape and vector_vector_MatShape to gen_dict.json
- Implemented MatShape_to_vector_MatShape, vector_MatShape_to_MatShape, MatShape_to_vector_vector_MatShape, and vector_vector_MatShape_to_MatShape conversion functions in dnn_converters.h/cpp and Converters.java
- Added testGetLayersShapes test to verify List<List<MatShape>> conversion
- Added vector_vector_Mat to gen_dict.json
- Implemented Mat_to_vector_vector_Mat and vector_vector_Mat_to_Mat conversion functions in converters.h/cpp and Converters.java
- Added DnnForwardAndRetrieve.java test to verify List<List<Mat>> conversion : Reference: C++ test in modules/dnn/test/test_misc.cpp - TEST(Net, forwardAndRetrieve)
Enable Java wrapper generation for Vec4i #27567
Fixes an issue where Java wrapper generation skips methods using Vec4i.
Related PR in opencv_contrib: https://github.com/opencv/opencv_contrib/pull/3988
The root cause was the absence of Vec4i in gen_java.json, which led to important methods such as aruco.drawCharucoDiamond() and ximgproc.HoughPoint2Line() being omitted from the Java bindings.
This PR includes the following changes:
- Added Vec4i definition to gen_java.json
- Updated gen_java.py to handle jintArray-based types properly
- ~~Also adjusted jn_args and jni_var for Vec2d and Vec3d to ensure correct JNI behavior~~
The modified Java wrapper generator successfully builds and includes the expected methods using Vec4i.
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This is a useful property for modularized libraries and applications to be able to use OpenCV
A full module-info.java file for true compatibility with the Java module system would require compiling with Java 9+ and either use a multi-release JAR (which can be tricky to maintain) or compile the entire library with Java 9+ (which would break Android consumers on older SDK versions). In the interest of causing the least disruption, only an automatic module name is set so that modular Java 9+ consumers can use OpenCV but not break anybody else.
Consider QRCode ECI encoding #24426
### Pull Request Readiness Checklist
related: https://github.com/opencv/opencv/pull/24350#pullrequestreview-1661658421
1. Add `getEncoding` method to obtain ECI number
2. Add `detectAndDecodeBytes`, `decodeBytes`, `decodeBytesMulti`, `detectAndDecodeBytesMulti` methods in Python (return `bytes`) and Java (return `byte[]`)
3. Allow Python bytes to std::string conversion in general and add `encode(byte[] encoded_info, Mat qrcode)` in Java
Python example with Kanji encoding:
```python
img = cv.imread("test.png")
detect = cv.QRCodeDetector()
data, points, straight_qrcode = detect.detectAndDecodeBytes(img)
print(data)
print(detect.getEncoding(), cv.QRCodeEncoder_ECI_SHIFT_JIS)
print(data.decode("shift-jis"))
```
```
b'\x82\xb1\x82\xf1\x82\xc9\x82\xbf\x82\xcd\x90\xa2\x8aE'
20 20
こんにちは世界
```
source: https://github.com/opencv/opencv/blob/ba4d6c859d21536f84e0328c16f4cc3e96bf3065/modules/objdetect/test/test_qrcode_encode.cpp#L332
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Fixed Android setCameraIndex issue. #27419
Fixed camera switching issue on Android devices: When a device has more than two cameras, the setCameraIndex method failed to switch to non-default cameras.
Root cause: The original code only considered two default camera IDs when updating camera IDs, ignoring all others. This fix ensures all camera IDs are properly handled.
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Java VideoCapture buffered stream constructor #27284
### Pull Request Readiness Checklist
resolves#26809
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Added trackers factory with pre-loaded dnn models #26875
Replaces https://github.com/opencv/opencv/pull/26295
Allows to substitute custom models or initialize tracker from in-memory model.
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AndroidMediaNdkCapture pixel format enhancement #26656
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New dnn engine #26056
This is the 1st PR with the new engine; CI is green and PR is ready to be merged, I think.
Merge together with https://github.com/opencv/opencv_contrib/pull/3794
---
**Known limitations:**
* [solved] OpenVINO is temporarily disabled, but is probably easy to restore (it's not a deal breaker to merge this PR, I guess)
* The new engine does not support any backends nor any targets except for the default CPU implementation. But it's possible to choose the old engine when loading a model, then all the functionality is available.
* [Caffe patch is here: #26208] The new engine only supports ONNX. When a model is constructed manually or is loaded from a file of different format (.tf, .tflite, .caffe, .darknet), the old engine is used.
* Even in the case of ONNX some layers are not supported by the new engine, such as all quantized layers (including DequantizeLinear, QuantizeLinear, QLinearConv etc.), LSTM, GRU, .... It's planned, of course, to have full support for ONNX by OpenCV 5.0 gold release. When a loaded model contains unsupported layers, we switch to the old engine automatically (at ONNX parsing time, not at `forward()` time).
* Some layers , e.g. Expat, are only partially supported by the new engine. In the case of unsupported flavours it switches to the old engine automatically (at ONNX parsing time, not at `forward()` time).
* 'Concat' graph optimization is disabled. The optimization eliminates Concat layer and instead makes the layers that generate tensors to be concatenated to write the outputs to the final destination. Of course, it's only possible when `axis=0` or `axis=N=1`. The optimization is not compatible with dynamic shapes since we need to know in advance where to store the tensors. Because some of the layer implementations have been modified to become more compatible with the new engine, the feature appears to be broken even when the old engine is used.
* Some `dnn::Net` API is not available with the new engine. Also, shape inference may return false if some of the output or intermediate tensors' shapes cannot be inferred without running the model. Probably this can be fixed by a dummy run of the model with zero inputs.
* Some overloads of `dnn::Net::getFLOPs()` and `dnn::Net::getMemoryConsumption()` are not exposed any longer in wrapper generators; but the most useful overloads are exposed (and checked by Java tests).
* [in progress] A few Einsum tests related to empty shapes have been disabled due to crashes in the tests and in Einsum implementations. The code and the tests need to be repaired.
* OpenCL implementation of Deconvolution is disabled. It's very bad and very slow anyway; need to be completely revised.
* Deconvolution3D test is now skipped, because it was only supported by CUDA and OpenVINO backends, both of which are not supported by the new engine.
* Some tests, such as FastNeuralStyle, checked that the in the case of CUDA backend there is no fallback to CPU. Currently all layers in the new engine are processed on CPU, so there are many fallbacks. The checks, therefore, have been temporarily disabled.
---
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Unified build.gradle files into one template #26009
Issue #24686
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Add sample for GPT2 inference #25868
### Pull Request Readiness Checklist
This PR adds sample for inferencing GPT-2 model. More specificly implementation of GPT-2 from [this repository](https://github.com/karpathy/build-nanogpt). Currently inference in OpenCV is only possible to do with fixed window size due to not supported dynamic shapes.
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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Fixed kotlin requirement in Android build.gradle #25856
Now OpenCV Android SDK doesn't always require kotlin plugin. Kotlin code is compiled only if the application uses kotlin plugin.
Fixes#24663
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Documentation transition to fresh Doxygen #25042
* current Doxygen version is 1.10, but we will use 1.9.8 for now due to issue with snippets (https://github.com/doxygen/doxygen/pull/10584)
* Doxyfile adapted to new version
* MathJax updated to 3.x
* `@relates` instructions removed temporarily due to issue in Doxygen (to avoid warnings)
* refactored matx.hpp - extracted matx.inl.hpp
* opencv_contrib - https://github.com/opencv/opencv_contrib/pull/3638
Allow multiple flags with OPENCV_GRADLE_VERBOSE_OPTIONS #24969
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Merge with https://github.com/opencv/ci-gha-workflow/pull/144
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Modified Java tests to run on Android #24910
To run the tests you need to:
1. Build OpenCV using Android pipeline. For example:
`cmake -DBUILD_TEST=ON -DANDROID=ON -DANDROID_ABI=arm64-v8a -DCMAKE_TOOLCHAIN_FILE=/usr/lib/android-sdk/ndk/25.1.8937393/build/cmake/android.toolchain.cmake -DANDROID_NDK=/usr/lib/android-sdk/ndk/25.1.8937393 -DANDROID_SDK=/usr/lib/android-sdk ../opencv`
`make`
2. Connect Android Phone
3. Run tests:
`cd android_tests`
`./gradlew tests_module:connectedAndroidTest`
Related CI pipeline: https://github.com/opencv/ci-gha-workflow/pull/138
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Added screen rotation support to JavaCamera2View amd NativeCameraView. Fixed JavaCamera2View initialization. #24869
Added automatic image rotation to JavaCamera2View and NativeCameraView so the video preview was matched with screen orientation.
Fixed double preview initialization bug in JavaCamera2View.
Added proper cameraID parsing to NativeCameraView similar to JavaCameraView
### Pull Request Readiness Checklist
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Abhishek Gola
Gold856
omrope79
kirtijindal14
Alexander Smorkalov
Alexander Smorkalov
ffccites
utibenkei
utibenkei
Sam Carlberg
Dmitry Kurtaev
FleeOvernight
Vadim Levin
Rüdiger Ihle
WU Jia
Maksim Shabunin
Vadim Pisarevsky
Alexander Smorkalov
alexlyulkov
Abduragim Shtanchaev
Alexander Lyulkov