Commit Graph

33685 Commits

Author SHA1 Message Date
Alexander Smorkalov
ce2b9f83f7
Merge pull request #24401 from mshabunin:enable-riscv-ci
CI: enable RISC-V for 4.x branch
2023-10-16 10:16:11 +03:00
Maksim Shabunin
331763a48b CI: enable RISC-V for 4.x branch 2023-10-16 09:28:37 +03:00
Yuantao Feng
d789cb459c
Merge pull request #24231 from fengyuentau:halide_cleanup_5.x
dnn: cleanup of halide backend for 5.x #24231

Merge with https://github.com/opencv/opencv_extra/pull/1092.

### 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
2023-10-13 16:53:18 +03:00
Liutong HAN
a287605c3e Clean up the Universal Intrinsic API. 2023-10-13 19:23:30 +08:00
Yuantao Feng
0507043a55
Merge pull request #24386 from fengyuentau:fix_dtype_nary_eltwise
dnn: fix inconsistent input dtype for nary eltwise layers #24386

Resolves https://github.com/opencv/opencv/issues/24385
Merge with https://github.com/opencv/opencv_extra/pull/1107
Relates https://github.com/opencv/opencv/pull/24092#discussion_r1353964405

### 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
2023-10-13 11:56:18 +03:00
Alexander Smorkalov
58285e5468
Merge pull request #24359 from asmorkalov:as/FastNeuralStyle_eccv16_tuning
Tuned threshold for FastNeuralStyle_eccv16 test
2023-10-13 10:29:41 +03:00
Alexander Smorkalov
cd7cbe3d41
Merge pull request #24324 from hanliutong:rewrite-fluid
Rewrite Universal Intrinsic code: gapi module (fluid part).
2023-10-13 10:25:07 +03:00
Alexander Smorkalov
b3d3acf75f
Merge pull request #24370 from LiuPeiqiCN:4.x
Fix imshow icons missing when linking the static opencv library
2023-10-12 21:57:41 +03:00
Dmitry Kurtaev
5ddf3de4ce
Merge pull request #24350 from dkurt:py_return_non_utf8_string
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
2023-10-12 17:39:57 +03:00
Alexander Smorkalov
3859ac921a
Merge pull request #24355 from AleksandrPanov:dynamic_window_in_aruco_cornerRefinement
add dynamic window in aruco cornerRefinement
2023-10-12 10:52:56 +03:00
Alexander Smorkalov
7e17f01b7b
Merge pull request #24368 from mshabunin:rvv-clang-17
RISC-V: added v0.12 intrinsics compatibility header
2023-10-12 10:28:54 +03:00
definitelyuncertain
a1028efdcf
Merge pull request #24333 from definitelyuncertain:CvtRGB2YUV422
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
- [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
- [x] The feature is well documented and sample code can be built with the project CMake
2023-10-12 10:18:24 +03:00
Yuantao Feng
590f150d5e
dnn: hotfixes for fast gemm (#24315)
* 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
2023-10-07 21:48:44 +03:00
刘佩其
631f229827 Fix the issue of missing imshow icons when linking OpenCV as a static library (https://github.com/opencv/opencv-python/issues/585) 2023-10-07 11:18:32 +08:00
Maksim Shabunin
8edf37903d RISC-V: added v0.12 intrinsics compatibility header 2023-10-06 20:16:57 +03:00
Alex
fd4af21350 add dynamic window in aruco cornerRefinement 2023-10-06 16:44:09 +03:00
Sean McBride
5fb3869775
Merge pull request #23109 from seanm:misc-warnings
* Fixed clang -Wnewline-eof warnings
* Fixed all trivial clang -Wextra-semi and -Wc++98-compat-extra-semi warnings
* Removed trailing semi from various macros
* Fixed various -Wunused-macros warnings
* Fixed some trivial -Wdocumentation warnings
* Fixed some -Wdocumentation-deprecated-sync warnings
* Fixed incorrect indentation
* Suppressed some clang warnings in 3rd party code
* Fixed QRCodeEncoder::Params documentation.

---------

Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>
2023-10-06 13:33:21 +03:00
jvuillaumier
24fd39538e
Merge pull request #24233 from jvuillaumier:rotate_flip_hal_hooks
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
2023-10-06 12:31:53 +03:00
HAN Liutong
07bf9cb013
Merge pull request #24325 from hanliutong:rewrite
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
2023-10-05 17:57:25 +03:00
Alexander Smorkalov
3dcaf1f287
Merge pull request #24362 from dkurt:enable_ov_2023_tests
Skip less tests with OpenVINO 2023.0
2023-10-05 15:51:54 +03:00
Dmitry Kurtaev
2c92eb3175 Enable more tests for OpenVINO 2023.0 2023-10-05 12:51:55 +03:00
Alexander Smorkalov
0976765c62
Merge pull request #24357 from Kumataro:fix24121
imgproc: move stb_truetype functions into cv namespace
2023-10-05 09:37:08 +03:00
Alexander Smorkalov
33d64d0491 Tuned threshold for FastNeuralStyle_eccv16 test for systems without AVX2. 2023-10-04 16:19:13 +03:00
Alexander Smorkalov
7b6d65cf20
Merge pull request #24337 from mshabunin:bump-ade-012c
3rdparty: update ade version
2023-10-04 14:59:16 +03:00
Wanli
62b5470b78
Merge pull request #24298 from WanliZhong:extend_perf_net_test
Extend performance test models #24298

**Merged With https://github.com/opencv/opencv_extra/pull/1095**

This PR aims to extend the performance tests. 

- **YOLOv5** for object detection
- **YOLOv8** for object detection
- **EfficientNet** for classification

Models from OpenCV Zoo:

- **YOLOX** for object detection
- **YuNet** for face detection
- **SFace** for face recognization
- **MPPalm** for palm detection
- **MPHand** for hand landmark
- **MPPose** for pose estimation
- **ViTTrack** for object tracking
- **PPOCRv3** for text detection
- **CRNN** for text recognization
- **PPHumanSeg** for human segmentation

If other models should be added, **please leave some comments**. Thanks!



Build opencv with script:
```shell
-DBUILD_opencv_python2=OFF
-DBUILD_opencv_python3=OFF
-DBUILD_opencv_gapi=OFF
-DINSTALL_PYTHON_EXAMPLES=OFF
-DINSTALL_C_EXAMPLES=OFF
-DBUILD_DOCS=OFF
-DBUILD_EXAMPLES=OFF
-DBUILD_ZLIB=OFF
-DWITH_FFMPEG=OFF
```



Performance Test on **Apple M2 CPU**
```shell
MacOS 14.0
8 threads
```

**1 thread:**
| Name of Test | 4.5.5-1th | 4.6.0-1th | 4.7.0-1th | 4.8.0-1th | 4.8.1-1th |
|--------------|:---------:|:---------:|:---------:|:---------:|:---------:|
| CRNN         |  76.244   |  76.611   |  62.534   |  57.678   |  57.238   |
| EfficientNet |    ---    |    ---    |  109.224  |  130.753  |  109.076  |
| MPHand       |    ---    |    ---    |  19.289   |  22.727   |  27.593   |
| MPPalm       |  47.150   |  47.061   |  41.064   |  65.598   |  40.109   |
| MPPose       |    ---    |    ---    |  26.592   |  32.022   |  26.956   |
| PPHumanSeg   |  41.672   |  41.790   |  27.819   |  27.212   |  30.461   |
| PPOCRv3      |    ---    |    ---    |  140.371  |  187.922  |  170.026  |
| SFace        |  43.830   |  43.834   |  27.575   |  30.653   |  26.387   |
| ViTTrack     |    ---    |    ---    |    ---    |  14.617   |  15.028   |
| YOLOX        | 1060.507  | 1061.361  |  495.816  |  533.309  |  549.713  |
| YOLOv5       |    ---    |    ---    |    ---    |  191.350  |  193.261  |
| YOLOv8       |    ---    |    ---    |  198.893  |  218.733  |  223.142  |
| YuNet        |  27.084   |  27.095   |  26.238   |  30.512   |  34.439   |
| MobileNet_SSD_Caffe         |  44.742   |  44.565   |  33.005   |  29.421   |  29.286   |
| MobileNet_SSD_v1_TensorFlow |  49.352   |  49.274   |  35.163   |  32.134   |  31.904   |
| MobileNet_SSD_v2_TensorFlow |  83.537   |  83.379   |  56.403   |  42.947   |  42.148   |
| ResNet_50                   |  148.872  |  148.817  |  77.331   |  67.682   |  67.760   |


**n threads:**
| Name of Test | 4.5.5-nth | 4.6.0-nth | 4.7.0-nth | 4.8.0-nth | 4.8.1-nth |
|--------------|:---------:|:---------:|:---------:|:---------:|:---------:|
| CRNN         |  44.262   |  44.408   |  41.540   |  40.731   |  41.151   |
| EfficientNet |    ---    |    ---    |  28.683   |  42.676   |  38.204   |
| MPHand       |    ---    |    ---    |   6.738   |  13.126   |   8.155   |
| MPPalm       |  16.613   |  16.588   |  12.477   |  31.370   |  17.048   |
| MPPose       |    ---    |    ---    |  12.985   |  19.700   |  16.537   |
| PPHumanSeg   |  14.993   |  15.133   |  13.438   |  15.269   |  15.252   |
| PPOCRv3      |    ---    |    ---    |  63.752   |  85.469   |  76.190   |
| SFace        |  10.685   |  10.822   |   8.127   |   8.318   |   7.934   |
| ViTTrack     |    ---    |    ---    |    ---    |  10.079   |   9.579   |
| YOLOX        |  417.358  |  422.977  |  230.036  |  234.662  |  228.555  |
| YOLOv5       |    ---    |    ---    |    ---    |  74.249   |  75.480   |
| YOLOv8       |    ---    |    ---    |  63.762   |  88.770   |  70.927   |
| YuNet        |   8.589   |   8.731   |  11.269   |  16.466   |  14.513   |
| MobileNet_SSD_Caffe         |  12.575   |  12.636   |  11.529   |  12.114   |  12.236   |
| MobileNet_SSD_v1_TensorFlow |  13.922   |  14.160   |  13.078   |  12.124   |  13.298   |
| MobileNet_SSD_v2_TensorFlow |  25.096   |  24.836   |  22.823   |  20.238   |  20.319   |
| ResNet_50                   |  41.561   |  41.296   |  29.092   |  30.412   |  29.339   |


Performance Test 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)
```shell
Ubuntu 22.04.2 LTS
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
```


**1 thread:**
| Name of Test | 4.5.5-1th | 4.6.0-1th | 4.7.0-1th | 4.8.0-1th | 4.8.1-1th |
|--------------|:---------:|:---------:|:---------:|:---------:|:---------:|
| CRNN         |  16.752   |  16.851   |  16.840   |  16.625   |  16.663   |
| EfficientNet |    ---    |    ---    |  61.107   |  76.037   |  53.890   |
| MPHand       |    ---    |    ---    |   8.906   |   9.969   |   8.403   |
| MPPalm       |  24.243   |  24.638   |  18.104   |  35.140   |  18.387   |
| MPPose       |    ---    |    ---    |  12.322   |  16.515   |  12.355   |
| PPHumanSeg   |  15.249   |  15.303   |  10.203   |  10.298   |  10.353   |
| PPOCRv3      |    ---    |    ---    |  87.788   |  144.253  |  90.648   |
| SFace        |  15.583   |  15.884   |  13.957   |  13.298   |  13.284   |
| ViTTrack     |    ---    |    ---    |    ---    |  11.760   |  11.710   |
| YOLOX        |  324.927  |  325.173  |  235.986  |  253.653  |  254.472  |
| YOLOv5       |    ---    |    ---    |    ---    |  102.163  |  102.621  |
| YOLOv8       |    ---    |    ---    |  87.013   |  103.182  |  103.146  |
| YuNet        |  12.806   |  12.645   |  10.515   |  12.647   |  12.711   |
| MobileNet_SSD_Caffe         |  23.556   |  23.768   |  24.304   |  22.569   |  22.602   |
| MobileNet_SSD_v1_TensorFlow |  26.136   |  26.276   |  26.854   |  24.828   |  24.961   |
| MobileNet_SSD_v2_TensorFlow |  43.521   |  43.614   |  46.892   |  44.044   |  44.682   |
| ResNet_50                   |  73.588   |  73.501   |  75.191   |  66.893   |  65.144   |


**n thread:**
| Name of Test | 4.5.5-nth | 4.6.0-nth | 4.7.0-nth | 4.8.0-nth | 4.8.1-nth | 
|--------------|:---------:|:---------:|:---------:|:---------:|:---------:|
| CRNN         |   8.665   |   8.827   |  10.643   |   7.703   |   7.743   | 
| EfficientNet |    ---    |    ---    |  16.591   |  12.715   |   9.022   |   
| MPHand       |    ---    |    ---    |   2.678   |   2.785   |   1.680   |           
| MPPalm       |   5.309   |   5.319   |   3.822   |  10.568   |   4.467   |       
| MPPose       |    ---    |    ---    |   3.644   |   6.088   |   4.608   |        
| PPHumanSeg   |   4.756   |   4.865   |   5.084   |   5.179   |   5.148   |        
| PPOCRv3      |    ---    |    ---    |  32.023   |  50.591   |  32.414   |      
| SFace        |   3.838   |   3.980   |   4.629   |   3.145   |   3.155   |       
| ViTTrack     |    ---    |    ---    |    ---    |  10.335   |  10.357   |   
| YOLOX        |  68.314   |  68.081   |  82.801   |  74.219   |  73.970   |      
| YOLOv5       |    ---    |    ---    |    ---    |  47.150   |  47.523   |    
| YOLOv8       |    ---    |    ---    |  32.195   |  30.359   |  30.267   |    
| YuNet        |   2.604   |   2.644   |   2.622   |   3.278   |   3.349   |    
| MobileNet_SSD_Caffe         |  13.005   |   5.935   |   8.586   |   4.629   |   4.713   |
| MobileNet_SSD_v1_TensorFlow |   7.002   |   7.129   |   9.314   |   5.271   |   5.213   |
| MobileNet_SSD_v2_TensorFlow |  11.939   |  12.111   |  22.688   |  12.038   |  12.086   |
| ResNet_50                   |  18.227   |  18.600   |  26.150   |  15.584   |  15.706   |
2023-10-04 13:05:32 +03:00
Alexander Smorkalov
670c52f75e
Merge pull request #24356 from VadimLevin:dev/vlevin/typing-re-export
feat: re-export cv2.typing module as typing
2023-10-04 09:14:51 +03:00
Kumataro
3a424b7f1c imgproc: move stb_trutype functions into cv namespace 2023-10-03 20:45:23 +00:00
Alexander Smorkalov
6bcf3d4311
Merge pull request #24354 from asmorkalov:as/charuco_ub
Removed invalid reference usage in charuco detector
2023-10-03 17:45:42 +03:00
Alexander Smorkalov
3d0e2cc46c
Merge pull request #24351 from sergiomb2:master
`numpy.distutils` is removed in numpy 1.26 on Python 3.12.
2023-10-03 17:44:41 +03:00
Dmitry Kurtaev
d752bac43f
Merge pull request #24234 from dkurt:distanceTransform_max_dist
Change max distance at distanceTransform #24234

### Pull Request Readiness Checklist

resolves https://github.com/opencv/opencv/issues/23895
related: https://github.com/opencv/opencv/pull/12278

* DIST_MASK_3 and DIST_MASK_5 maximal distance increased from 8192 to 65533 +/- 1
* Fix squares processing at DIST_MASK_PRECISE
* - [ ] TODO: Check with IPP

```cpp
    cv::Mat gray = cv::imread("opencv/samples/data/stuff.jpg", cv::ImreadModes::IMREAD_GRAYSCALE);

    cv::Mat gray_resize;
    cv::resize(gray, gray_resize, cv::Size(70000,70000), 0.0, 0.0, cv::INTER_LINEAR);

    gray_resize = gray_resize >= 100;

    cv::Mat dist;
    cv::distanceTransform(gray_resize, dist, cv::DIST_L2, cv::DIST_MASK_5, CV_32F);

    double minVal, maxVal;
    minMaxLoc(dist, &minVal, &maxVal);
    dist = 255 * (dist - minVal) / (maxVal - minVal);
    std::cout << minVal << " " << maxVal << std::endl;

    cv::Mat dist_resize;
    cv::resize(dist, dist_resize, cv::Size(1024,1024), 0.0, 0.0, cv::INTER_LINEAR);

    cv::String outfilePath = "test_mask_5.png";
    cv::imwrite(outfilePath, dist_resize);
```

mask | 4.x | PR |
----------|--------------|--------------
DIST_MASK_3 | <img src="https://github.com/opencv/opencv/assets/25801568/23e5de76-a8ba-4eb8-ab03-fa55672834be" width="128"> | <img src="https://github.com/opencv/opencv/assets/25801568/e1149f6a-49d6-47bd-a2a8-20bb7e4dafa4" width="128"> |
DIST_MASK_5 | <img src="https://github.com/opencv/opencv/assets/25801568/98aba29b-8865-4b9a-8066-669b16d175c9" width="128"> | <img src="https://github.com/opencv/opencv/assets/25801568/54f62ed2-9ef6-485f-bd63-48cc96accd7d" width="128"> |
DIST_MASK_PRECISE | <img src="https://github.com/opencv/opencv/assets/25801568/c4d79451-fd7a-461f-98fc-13060c63f473" width="128"> | <img src="https://github.com/opencv/opencv/assets/25801568/b5bfcaf5-bc48-40ba-b8e3-d000e5ab48db" width="128">|

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
2023-10-03 17:23:32 +03:00
Maksim Shabunin
1bccc14e05
Merge pull request #24343 from mshabunin:fix-test-writes
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.
2023-10-03 16:34:25 +03:00
Yuriy Chernyshov
9f74982a54
Merge pull request #24323 from georgthegreat:akaze-variadic 2023-10-03 16:16:41 +03:00
Sérgio M. Basto
00ca8f455e numpy.distutils is removed in numpy 1.26 on Python 3.12.
so we don't use numpy.distutils to get includes dirs of python-numpy
2023-10-03 12:28:10 +01:00
Vadim Levin
4708d1aed7 feat: re-export cv2.typing module as typing
Import Python typing module as `_typing` to avoid name clashes.
2023-10-03 14:12:55 +03:00
alexlyulkov
9bd14d5417
Merge pull request #24353 from alexlyulkov:al/fixed-cumsum-layer
Fixed CumSum dnn layer #24353

Fixes #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.
2023-10-03 13:58:25 +03:00
Alexander Smorkalov
c497fe05a0 Removed invalid reference usage in charuco detector. 2023-10-03 11:31:48 +03:00
Alexander Smorkalov
4e60392040
Merge pull request #24349 from AleksandrPanov:aruco_check_board_separation
add aruco board separation check
2023-10-03 10:00:03 +03:00
Alex
e5b114e5b8 Added ArUco marker size check for Aruco and Charuco boards. 2023-10-03 09:16:07 +03:00
Alexander Smorkalov
163d544ecf Merge branch 4.x 2023-10-02 10:17:23 +03:00
Alexander Smorkalov
63819c1e1f
Merge pull request #24342 from asmorkalov:as/java_test_status
Fail Java test suite, execution, if one of test failed.
2023-10-02 09:17:11 +03:00
Alexander Smorkalov
2af5815d47 Fail Java test suite, execution, if one of test failed. 2023-10-01 18:31:04 +03:00
Alexander Alekhin
f3c724d449 Merge pull request #24344 from asmorkalov:as/einsum_fallback_fix 2023-09-29 16:48:41 +00:00
Alexander Smorkalov
5caee5cc64 Fixed OpenCL PF16 fallback in Einsum layer. 2023-09-29 15:52:23 +03:00
Alexander Smorkalov
fb0479da23
Merge pull request #24341 from emmanuel-ferdman:wip
fix: update location to `samples/dnn/download_models.py`
2023-09-29 14:35:18 +03:00
Emmanuel Ferdman
8a8c0d285e
fix: update location to samples/dnn/download_models.py 2023-09-29 12:30:46 +03:00
Dmitry Kurtaev
c7ec0d599a
Merge pull request #23987 from dkurt:openvino_int8_backend
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
2023-09-28 16:24:43 +03:00
Alexander Smorkalov
b8d4ac589d
Merge pull request #24334 from fengyuentau:fix_24319
dnn onnx: fix not-found constant indices for Gather if shared
2023-09-28 13:08:26 +03:00
Maksim Shabunin
0433fe539c 3rdparty: update ade version 2023-09-28 12:45:34 +03:00
fengyuentau
7fa0493ca0 init commit 2023-09-28 11:50:21 +08:00
casualwinds
7b399c4248
Merge pull request #24280 from casualwind:parallel_opt
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
- [ ] 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
2023-09-27 16:21:20 +03:00