Fix bug in ChessBoardDetector::findQuadNeighbors #24597
### Pull Request Readiness Checklist
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Patch to opencv_extra has the same branch name.
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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
### Pull Request Readiness Checklist
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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.
### Pull Request Readiness Checklist
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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
### Pull Request Readiness Checklist
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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
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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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
### Pull Request Readiness Checklist
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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.
### Pull Request Readiness Checklist
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Bugfix/qrcode version estimator #24364
Fixes https://github.com/opencv/opencv/issues/24366
### Pull Request Readiness Checklist
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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
### Pull Request Readiness Checklist
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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"));
```
### Pull Request Readiness Checklist
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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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Patch to opencv_extra has the same branch name.
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Enable softmax layer vectorization on RISC-V RVV #24510
Related: https://github.com/opencv/opencv/pull/24466
### Pull Request Readiness Checklist
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Fix some of the broken urls in docs #24521
### Pull Request Readiness Checklist
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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
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
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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
### Pull Request Readiness Checklist
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Patch to opencv_extra has the same branch name.
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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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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
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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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)
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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
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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.
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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!
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* 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
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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
- [ ] 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
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
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
