Commit Graph

23631 Commits

Author SHA1 Message Date
zihaomu
51281f8d69 support the split node of onnx opset >= 13 2023-04-11 16:18:50 +08:00
Kumataro
d2dbaa4cd1
Merge pull request #23433 from Kumataro:4.x-fix23416
imgcodecs: tiff: Support to encode for CV_32S with compression params

Fix https://github.com/opencv/opencv/issues/23416

### 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.
- [ ] The feature is well documented and sample code can be built with the project CMake
2023-04-11 10:50:47 +03:00
Alexander Alekhin
f9ce3f4b91 Merge pull request #23469 from gottagofaster236:use_nv12_for_obs_camera 2023-04-10 13:39:15 +00:00
Alexander Alekhin
daf9de7463 Merge pull request #23383 from mshabunin:rvv-scalable-gcc 2023-04-10 13:35:43 +00:00
TolyaTalamanov
8a95f4f0e6 Handle meta for multiple infer inputs 2023-04-10 09:54:26 +00:00
gottagofaster236
d30830d0a6 Use NV12 instead of YUY2 for OBS Virtual Camera. 2023-04-09 01:56:03 +02:00
Alexander Smorkalov
f5a92cb43f
Merge pull request #22889 from D-Alex:patch-1
core: improve doc for setNumThreads
2023-04-07 16:37:40 +03:00
Alexander Smorkalov
3bcc3e70f1 Extended setNumThreads documentation according to code review. 2023-04-07 13:56:57 +03:00
eplankin
fd8b346c3e
Merge pull request #23443 from eplankin:3.4
* Update IPPICV binaries (20230330)

* Revert "core(IPP): disable some ippsMagnitude_32f calls"

This reverts commit 8069a6b4f8.

* Reverted changes in norm() and count_non_zero()
2023-04-07 09:14:42 +00:00
Alexander Smorkalov
ce01123db2
Merge pull request #23020 from Wwupup:yunetv2
upgrade FaceDetectorYN to v2
2023-04-06 15:47:19 +03:00
Yuantao Feng
3a83a35ab0
Merge pull request #23296 from fengyuentau:fix_identifying_constant
Fix identifying initializers in ONNX graph simplification #23296

Fixes https://github.com/opencv/opencv/issues/23295

### 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
2023-04-06 15:35:31 +03:00
tantei3
8336a96cb9
Merge pull request #23446 from tantei3:bmp_fix
**Merge with extra**: https://github.com/opencv/opencv_extra/pull/1050

For 32 bits per pixel with 3 or 4 channel destination images, apply scale factor and mask to parse BMP files correctly

closes #23445 

### Pull Request Readiness Checklist
- [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.
- [ ] The feature is well documented and sample code can be built with the project CMake
2023-04-06 14:34:36 +03:00
Maksim Shabunin
b12c14514a RISC-V: allow building scalable RVV support with GCC, LLVM 16 support 2023-04-05 14:18:58 +03:00
gottagofaster236
b4e3359448 Fix OBS Virtual Camera capture. 2023-04-05 08:04:35 +02:00
Alexander Smorkalov
2b32eee3f4
Merge pull request #23451 from Zero2key:4.x
add opencv.js imread function can use OffscreenCanvas
2023-04-04 11:05:53 +03:00
Alexander Smorkalov
51f5ee6f19
Merge pull request #23448 from dmatveev:dm/gapi_fix_standalone_47
G-API: Fix compilation error in Standalone mode
2023-04-03 14:21:31 +03:00
Alexander Smorkalov
66a5ecb7ec
Merge pull request #23350 from spikethehobbitmage:4.x
Fix reference counting errors in registerNewType
2023-04-03 14:08:32 +03:00
Zero2key
4e050e85ad
add opencv.js imread function can use OffscreenCanvas 2023-04-03 10:33:20 +08:00
Dmitry Matveev
3871984028 G-API: Fix compilation error in Standalone mode
- Point3f was added to type traits but was missing in the "own" package; fixed.
2023-04-02 17:52:53 +03:00
Alexander Smorkalov
20eee64426
Merge pull request #23390 from just-gull:bugfix.21401.fix-macos-crash-when-keypress-does-nothing
check keydown event characters length on macos
2023-04-02 12:29:55 +03:00
Alexander Smorkalov
d8c80ff5a4
Merge pull request #23419 from dkurt:onnx_fixes
Several fixes for ONNX importer: Expand, Gather
2023-04-02 11:40:56 +03:00
Alexander Smorkalov
3cf367c9c4
Merge pull request #23271 from stefan523:aruco_testcase_fixes
Aruco/Charuco test case fixes for floating point for loops
2023-03-30 11:22:14 +03:00
Alex
c643af0b85 fix test 2023-03-29 15:29:56 +03:00
Dmitry Kurtaev
5e1d33329b Several fixes for ONNX importer: Expand, Gather 2023-03-27 22:15:26 +03:00
HAN Liutong
a809ae4e88 Fix HAL compatibility layer and modify use cases. 2023-03-27 21:30:47 +08:00
Kumataro
1c6c3dfa8d remove tail whitespace 2023-03-26 18:33:54 +09:00
Kumataro
83a49b4f6a imgcodecs: update documentation for imwrite() to support images formats. 2023-03-26 09:03:16 +09:00
Alexander Smorkalov
352f92e437
Merge pull request #23402 from LaurentBerger:I23400
Typo in enum cv::QuatEnum::EulerAnglesType
2023-03-24 18:11:48 +03:00
Alexander Smorkalov
f5fd3e7d65
Merge pull request #23367 from LaurentBerger:msmf_doc
Note for MSMF in doc
2023-03-24 17:16:52 +03:00
unknown
ee302b063f Typo in enum cv::QuatEnum::EulerAnglesType 2023-03-24 14:03:14 +01:00
Alexander Smorkalov
d7dd014a6e
Merge pull request #23399 from AleksandrPanov:aruco_fix_board
Fix create aruco Board in Python
2023-03-24 15:38:53 +03:00
Alexander Smorkalov
b56a52c49b
Merge pull request #22471 from anna-khakimova:ak/fix_resize4lpi_tests
Increasing tolerance for Preproc4lpiTest set on ARM
2023-03-24 15:31:48 +03:00
Anna Khakimova
0bb84096a2 Fix tolerance for Preproc4lpiTest set 2023-03-24 14:20:22 +03:00
Alexander Smorkalov
36a03dbdbf
Merge pull request #23307 from alalek:simd_comparison_fix_misused_64f_guard
core(simd): 64-bit integer EQ/NE without misused 64F guard
2023-03-24 12:46:18 +03:00
Alex
02bdc10062 fix assert, add test 2023-03-24 11:52:05 +03:00
Alexander Smorkalov
d3cc507380 Added reference to Media Foundation. 2023-03-23 16:58:22 +03:00
Alexander Smorkalov
1af790ecc3
Merge pull request #23388 from simonlynen:patch-2
Make LineSegmentDetector deterministic by using stable_sort
2023-03-23 16:18:29 +03:00
Alexander Smorkalov
8c64adb000
Merge pull request #23019 from tkram01:sampleIdxFix
Fix for using sampleIdx to limit training data
2023-03-22 11:59:34 +03:00
Sergey Petrenko
6ffe686ba8 check keydown event characters length before returning the pressed character code 2023-03-22 10:24:22 +03:00
tkram01
ea7efd57d8 Fix for using sampleIdx to limit training data 2023-03-22 09:50:58 +03:00
Christian Henkel
c9e42c5050 two typos 2023-03-22 09:17:41 +03:00
Simon Lynen
6033599c88
Make LineSegmentDetector deterministic by using stable_sort for ordering keypoints prior to region growing
This makes LineSegmentDetector deterministic by using stable_sort for ordering points by norm. Without this change the region growing in LSD is non-determinstic and thus the returned lines are changing between invocations.

This is a replacement for https://github.com/opencv/opencv/pull/23370
2023-03-22 04:12:51 +01:00
Alexander Smorkalov
a4ff46aab7
Merge pull request #23250 from tintou:./tintou/glib-req
highgui: Set hard GLib requirement to >=2.32
2023-03-21 15:22:34 +03:00
Alexander Smorkalov
e6bd4c9f85
Merge pull request #23275 from genciberisha:bug/issue-23249_detected_but_not_decoded_bug
Added QR_Code data flip support, flip and retry after first ECC failure
2023-03-21 15:03:30 +03:00
Alexander Smorkalov
0d082ce6fd
Merge pull request #23344 from anderskiaer:singlefilejs
Add possibility for disabling inlining `wasm` in `opencv.js`
2023-03-21 15:01:52 +03:00
Dmitry Kurtaev
5df6b4a756
Merge pull request #23325 from dkurt:dnn_input_info
Propagate inputs info for ONNX and TFLite models

### Pull Request Readiness Checklist

Needed for generic applications such as benchmarking pipelines. So OpenCV can tell about the default input shapes specified in the models.

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
2023-03-21 14:50:53 +03:00
ippei.i
a60408cda5
Merge pull request #23300 from ippei-i:CAP_PROP_AUTO_WB-and-CAP_PROP_WHITE_BALANCE_BLUE_U_support_in_CAP_DSHOW
Support VideoCapture CAP_PROP_AUTO_WB and CV_CAP_PROP_WHITE_BALANCE_BLUE_U for DShow

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [OK] I agree to contribute to the project under Apache 2 License.
- [OK] 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
- [OK] The PR is proposed to the proper branch
- [OK] There is a reference to the original bug report and related work
https://github.com/opencv/opencv/issues/19621
https://github.com/opencv/opencv/issues/21408

### Before apply this pull request console output.

before AWB setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

after AWB disable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

after AWB enable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

after Manual WB(and Disable AWB) setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: -1

### After apply this pull request console output.

before AWB setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: 0

after AWB disable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 4000
CAP_PROP_AUTO_WB: 0

after AWB enable setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 4000
CAP_PROP_AUTO_WB: 1

after Manual WB(and Disable AWB) setting
CAP_PROP_WHITE_BALANCE_BLUE_U: 2000
CAP_PROP_AUTO_WB: 0

### Test Code
[OpenCvVideoCapTest.zip](https://github.com/opencv/opencv/files/10825399/OpenCvVideoCapTest.zip)
2023-03-21 14:29:24 +03:00
Wwupup
da3a4dcbc1 upgrade FaceDetectorYN to v2 2023-03-21 12:41:02 +08:00
Genci Berisha
a1b4aa5e88
Added QR_Code data flip support, flip and retry after first EEC failure
Added regression test for the flipped images
2023-03-20 14:26:11 +01:00
Labib Asari
c4226f0457
Merge pull request #23196 from labeeb-7z:printOptionInRoiSelector
Added argument to print notice in `roiSelector.cpp`

Related Issue : https://github.com/opencv/opencv/issues/23175

I've added a printNotice argument to `selectROI` (and it's overload) and `selectROIs` functions.
I've also updated the function declarations in `highgui.hpp`.
Tested by building locally.

### 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
- [ ] 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
2023-03-20 10:06:57 +03:00
Maksim Shabunin
aef1fc087d cmake: fix V4L config verification conflict with OBSENSOR 2023-03-19 10:58:47 +03:00
unknown
a2e04718ec te for MSMF in doc 2023-03-17 13:36:47 +01:00
Alexander Smorkalov
924a65413a
Merge pull request #23357 from zihaomu:fix_winograd_error_32bit
DNN : fix bug in 32 bit cpu
2023-03-15 11:24:54 +03:00
zihaomu
6bac5453d1 fix bug in 32 bit cpu 2023-03-15 08:24:55 +08:00
Alexander Smorkalov
ccbc784195
Merge pull request #23354 from zihaomu:issue_23351
DNN : fix bug in layer fusion
2023-03-14 17:23:25 +03:00
Vladimir Ponomarev
b204c39815
Merge pull request #23276 from vovka643:flann_corrections
Fixed potential memory leak in flann

Issue #22426

### 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
2023-03-14 15:00:44 +03:00
zihaomu
386be97ce2 fix bug in layer fusion 2023-03-14 19:06:06 +08:00
tingbo.liao
7d032de7e8 Fix bugs of test case failure
4 failed tests in open_test_dnn listed below:
* Test_Caffe_layers.Conv_Elu/0, where GetParam() = OCV/CPU
* Test_ONNX_layers.ConvResizePool1d/0, where GetParam() = OCV/CPU
* Test_TensorFlow_layers.tf_reshape_nhwc/0, where GetParam() = OCV/CPU
* Test_Torch_layers.net_inception_block/0, where GetParam() = OCV/CPU

In winofunc_AtXA_8x8_f32 and winofunc_BtXB_8x8_f32
implementation, incorrect input parameters cause tests failure.

Add four new different variables for the last four input parameters of
v_transpose4x4 to fix bugs, and update related comments.

Signed-off-by: tingbo.liao <tingbo.liao@starfivetech.com>
2023-03-14 17:05:19 +08:00
Alexander Smorkalov
de2f7666fb
Merge pull request #23260 from tintou:tintou/gtk-reduce-diff
highgui: Reduce the difference between GTK+2 and GTK+3 version
2023-03-14 09:11:53 +03:00
Spike
95f087cd0b Fix reference counting errors in registerNewType 2023-03-13 23:22:57 -06:00
Alexander Smorkalov
22a52766dc
Merge pull request #23343 from zihaomu:fix_test_onnx_conf
DNN Test ONNX: Fix the logic of the test case
2023-03-13 21:48:41 +03:00
Yuantao Feng
b94e13c8ae
Merge pull request #23319 from fengyuentau:fix_zoo_issue_136
Related issue: https://github.com/opencv/opencv_zoo/issues/136

Features added:

- Support operators with multiple output: ONNX Split.
- Support Slice without steps.

Bugs fixed:

- Wrong settings in ClipByValue (Relu6).
- Wrong calculation of pads in convolution layer (It is wrong generally but only fixed specifically for CANN for now).

### Pull Request Readiness Checklist

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
2023-03-13 21:46:33 +03:00
zihaomu
ee3740af00 move global skip out of if loop, and add opencv_deny_list 2023-03-13 22:16:51 +08:00
Alexander Smorkalov
9f2182abbb
Merge pull request #23261 from vovka643:3.4
Remove separator between trackbars.
2023-03-13 13:51:56 +03:00
anderskiaer
6c763e1ea5 Add possibility for disabling inlining wasm in opencv.js 2023-03-11 21:03:18 +01:00
Zihao Mu
e03e2e7f94
Merge pull request #23192 from zihaomu:clean_up_SIMD_code
### Purpose of this PR:
- Move all dispatch and SIMD code of `convolution layer` into `simd.hpp` file.
- Support Winograd at AVX-only machine.
- Re-name the folder from `fast_conv` to `cpu_kernels`. In the future, we can put other layers of CPU optimization into it, like `GEMM` or `MatMul`.

## Performance Test
Since this patch just focuses on the code style, the performance is expected as the same as before.
Test with the following script: 
`./bin/opencv_perf_dnn '--gtest_filter=*conv*' --gtest_output="xml:../1-0th.xml" --perf_threads=1`

### Test on X86 platform
Min (ms)
|Name of Test|4.x | patch | 4.x vs patch (x-factor)|
|---|:-:|:-:|:-:|
|conv1d::Conv1D::(GFLOPS=0.000, K=[3], IN={1, 2, 19}, OCN=2, G=2, S=2, P=(1, 1), BIAS, OCV/CPU)|0.001|0.001|0.98|
|conv1d::Conv1D::(GFLOPS=0.000, K=[3], IN={1, 2, 25}, OCN=2, G=2, P=(2, 2), PM=SAME, OCV/CPU)|0.001|0.001|0.95|
|conv1d::Conv1D::(GFLOPS=0.000, K=[3], IN={1, 6, 10}, OCN=6, PM=VALID, BIAS, OCV/CPU)|0.001|0.001|0.97|
|conv3d::Conv3D::(GFLOPS=0.000, K=[1 x 1 x 1], IN={1, 4, 9, 10, 10}, OCN=4, S=[1 x 1 x 2], P=(1, 1) x (1, 1) x (1, 1), PM=VALID, OCV/CPU)|0.002|0.002|1.04|
|conv3d::Conv3D::(GFLOPS=0.000, K=[1 x 1 x 1], IN={1, 8, 1, 10, 10}, OCN=8, G=8, P=(1, 1) x (1, 1) x (1, 1), BIAS, OCV/CPU)|0.002|0.002|0.94|
|conv3d::Conv3D::(GFLOPS=0.000, K=[3 x 3 x 3], IN={1, 2, 19, 19, 19}, OCN=2, G=2, S=[2 x 2 x 2], P=(1, 1) x (1, 1) x (1, 1), BIAS, OCV/CPU)|0.040|0.044|0.93|
|conv3d::Conv3D::(GFLOPS=0.000, K=[3 x 4 x 2], IN={1, 4, 8, 10, 10}, OCN=4, G=4, S=[1 x 2 x 1], BIAS, OCV/CPU)|0.010|0.010|1.00|
|conv3d::Conv3D::(GFLOPS=0.001, K=[3 x 3 x 3], IN={1, 2, 25, 19, 19}, OCN=2, G=2, S=[1 x 2 x 2], P=(2, 2) x (2, 2) x (2, 2), PM=SAME, OCV/CPU)|0.106|0.103|1.03|
|conv3d::Conv3D::(GFLOPS=0.002, K=[3 x 1 x 4], IN={1, 14, 5, 10, 10}, OCN=14, PM=SAME, OCV/CPU)|0.041|0.040|1.03|
|conv3d::Conv3D::(GFLOPS=0.006, K=[5 x 5 x 5], IN={1, 4, 50, 19, 19}, OCN=4, S=[2 x 2 x 2], P=(1, 1) x (1, 1) x (1, 1), PM=VALID, OCV/CPU)|0.340|0.329|1.03|
|conv3d::Conv3D::(GFLOPS=0.027, K=[3 x 3 x 3], IN={1, 6, 10, 38, 50}, OCN=6, PM=VALID, BIAS, OCV/CPU)|0.590|0.567|1.04|
|conv3d::Conv3D::(GFLOPS=0.030, K=[5 x 5 x 5], IN={1, 6, 19, 19, 19}, OCN=6, G=2, OCV/CPU)|1.374|1.314|1.05|
|conv3d::Conv3D::(GFLOPS=0.045, K=[7 x 7 x 7], IN={1, 2, 38, 38, 38}, OCN=2, S=[1 x 2 x 1], OCV/CPU)|3.715|3.528|1.05|
|conv3d::Conv3D::(GFLOPS=0.053, K=[3 x 3 x 3], IN={1, 10, 98, 10, 10}, OCN=10, PM=SAME, OCV/CPU)|1.181|1.166|1.01|
|conv3d::Conv3D::(GFLOPS=0.071, K=[7 x 7 x 7], IN={1, 6, 15, 19, 19}, OCN=6, S=[2 x 1 x 1], P=(3, 3) x (3, 3) x (3, 3), PM=SAME, BIAS, OCV/CPU)|2.689|2.587|1.04|
|conv3d::Conv3D::(GFLOPS=0.093, K=[5 x 5 x 5], IN={1, 4, 40, 75, 75}, OCN=4, S=[2 x 2 x 2], OCV/CPU)|4.754|4.500|1.06|
|conv3d::Conv3D::(GFLOPS=0.116, K=[5 x 5 x 5], IN={1, 2, 21, 75, 100}, OCN=2, BIAS, OCV/CPU)|9.612|9.112|1.05|
|conv3d::Conv3D::(GFLOPS=1.267, K=[5 x 5 x 5], IN={1, 3, 75, 75, 100}, OCN=3, PM=SAME, BIAS, OCV/CPU)|69.000|64.676|1.07|
|conv3d::Conv3D::(GFLOPS=1.343, K=[3 x 3 x 3], IN={1, 11, 9, 150, 200}, OCN=11, PM=VALID, BIAS, OCV/CPU)|20.248|18.451|1.10|
|conv::Conv::(GFLOPS=0.177, K=[1 x 1], IN={1, 512, 26, 26}, OCN=256, OCV/CPU)|1.395|1.392|1.00|
|conv::Conv::(GFLOPS=0.177, K=[1 x 1], IN={1, 1024, 13, 13}, OCN=512, OCV/CPU)|1.990|1.984|1.00|
|conv::Conv::(GFLOPS=0.178, K=[1 x 1], IN={1, 256, 52, 52}, OCN=128, OCV/CPU)|1.393|1.360|1.02|
|conv::Conv::(GFLOPS=0.210, K=[1 x 1], IN={1, 576, 38, 50}, OCN=96, PM=SAME, BIAS, OCV/CPU)|1.813|1.744|1.04|
|conv::Conv::(GFLOPS=0.231, K=[3 x 3], IN={1, 128, 56, 56}, OCN=32, P=[1 x 1], OCV/CPU)|1.190|1.191|1.00|
|conv::Conv::(GFLOPS=0.231, K=[3 x 3], IN={1, 256, 14, 14}, OCN=256, P=[1 x 1], OCV/CPU)|1.286|1.284|1.00|
|conv::Conv::(GFLOPS=0.280, K=[1 x 1], IN={1, 576, 38, 50}, OCN=128, PM=SAME, BIAS, OCV/CPU)|2.295|2.279|1.01|
|conv::Conv::(GFLOPS=0.302, K=[3 x 3], IN={1, 64, 64, 64}, OCN=64, PM=SAME, OCV/CPU)|1.322|1.331|0.99|
|conv::Conv::(GFLOPS=0.357, K=[1 x 1], IN={1, 64, 208, 208}, OCN=64, OCV/CPU)|3.784|3.533|1.07|
|conv::Conv::(GFLOPS=0.420, K=[3 x 3], IN={1, 96, 38, 50}, OCN=128, PM=SAME, BIAS, OCV/CPU)|1.838|1.844|1.00|
|conv::Conv::(GFLOPS=0.472, K=[3 x 3], IN={1, 128, 40, 40}, OCN=128, PM=SAME, OCV/CPU)|1.957|1.959|1.00|
|conv::Conv::(GFLOPS=0.472, K=[3 x 3], IN={1, 256, 20, 20}, OCN=256, PM=SAME, OCV/CPU)|2.596|2.573|1.01|
|conv::Conv::(GFLOPS=0.472, K=[3 x 3], IN={1, 512, 10, 10}, OCN=512, PM=SAME, OCV/CPU)|4.183|4.083|1.02|
|conv::Conv::(GFLOPS=0.561, K=[3 x 3], IN={1, 128, 38, 50}, OCN=128, PM=SAME, BIAS, OCV/CPU)|2.413|2.406|1.00|
|conv::Conv::(GFLOPS=0.624, K=[3 x 3], IN={1, 128, 46, 46}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|2.538|2.546|1.00|
|conv::Conv::(GFLOPS=0.701, K=[3 x 3], IN={1, 128, 38, 50}, OCN=160, PM=SAME, BIAS, OCV/CPU)|2.972|2.980|1.00|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 64, 104, 104}, OCN=64, P=[1 x 1], OCV/CPU)|3.452|3.464|1.00|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 128, 52, 52}, OCN=128, P=[1 x 1], OCV/CPU)|3.082|3.105|0.99|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 256, 26, 26}, OCN=256, P=[1 x 1], OCV/CPU)|4.043|3.919|1.03|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 512, 13, 13}, OCN=512, P=[1 x 1], OCV/CPU)|5.538|5.531|1.00|
|conv::Conv::(GFLOPS=0.830, K=[3 x 3], IN={1, 64, 75, 100}, OCN=96, PM=SAME, BIAS, OCV/CPU)|3.393|3.418|0.99|
|conv::Conv::(GFLOPS=0.958, K=[3 x 3], IN={1, 192, 38, 38}, OCN=192, PM=SAME, OCV/CPU)|4.325|4.234|1.02|
|conv::Conv::(GFLOPS=0.958, K=[3 x 3], IN={1, 384, 19, 19}, OCN=384, PM=SAME, OCV/CPU)|6.009|5.908|1.02|
|conv::Conv::(GFLOPS=1.022, K=[3 x 3], IN={1, 576, 19, 19}, OCN=273, PM=SAME, BIAS, OCV/CPU)|6.557|6.376|1.03|
|conv::Conv::(GFLOPS=1.112, K=[3 x 3], IN={1, 512, 10, 10}, OCN=1206, P=[1 x 1], BIAS, OCV/CPU)|10.114|9.472|1.07|
|conv::Conv::(GFLOPS=1.181, K=[3 x 3], IN={1, 64, 160, 200}, OCN=128, S=[2 x 2], P=[1 x 1], BIAS, OCV/CPU)|10.373|9.879|1.05|
|conv::Conv::(GFLOPS=1.182, K=[3 x 3], IN={1, 32, 320, 400}, OCN=64, S=[2 x 2], P=[1 x 1], BIAS, OCV/CPU)|12.782|11.624|1.10|
|conv::Conv::(GFLOPS=1.195, K=[9 x 9], IN={1, 32, 240, 320}, OCN=3, P=[4 x 4], BIAS, OCV/CPU)|90.931|90.552|1.00|
|conv::Conv::(GFLOPS=1.196, K=[3 x 3], IN={1, 384, 26, 26}, OCN=256, P=[1 x 1], OCV/CPU)|6.091|5.818|1.05|
|conv::Conv::(GFLOPS=1.210, K=[3 x 3], IN={1, 32, 256, 256}, OCN=32, PM=SAME, OCV/CPU)|7.083|6.643|1.07|
|conv::Conv::(GFLOPS=1.245, K=[3 x 3], IN={1, 64, 75, 75}, OCN=192, PM=SAME, BIAS, OCV/CPU)|5.054|5.059|1.00|
|conv::Conv::(GFLOPS=1.245, K=[3 x 3], IN={1, 96, 75, 100}, OCN=96, PM=SAME, BIAS, OCV/CPU)|5.005|4.931|1.02|
|conv::Conv::(GFLOPS=1.248, K=[3 x 3], IN={1, 256, 46, 46}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|4.951|5.065|0.98|
|conv::Conv::(GFLOPS=1.258, K=[3 x 3], IN={1, 1280, 10, 10}, OCN=546, PM=SAME, BIAS, OCV/CPU)|11.957|11.293|1.06|
|conv::Conv::(GFLOPS=1.261, K=[3 x 3], IN={1, 192, 38, 50}, OCN=192, PM=SAME, BIAS, OCV/CPU)|5.328|5.250|1.01|
|conv::Conv::(GFLOPS=1.416, K=[3 x 3], IN={1, 128, 62, 82}, OCN=128, BIAS, OCV/CPU)|5.544|5.292|1.05|
|conv::Conv::(GFLOPS=1.500, K=[3 x 3], IN={1, 128, 64, 84}, OCN=128, BIAS, OCV/CPU)|6.186|5.893|1.05|
|conv::Conv::(GFLOPS=1.586, K=[3 x 3], IN={1, 128, 66, 86}, OCN=128, BIAS, OCV/CPU)|6.153|5.834|1.05|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 256, 26, 26}, OCN=512, P=[1 x 1], OCV/CPU)|8.154|8.107|1.01|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 256, 52, 52}, OCN=512, S=[2 x 2], P=[1 x 1], OCV/CPU)|12.699|12.256|1.04|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 512, 13, 13}, OCN=1024, P=[1 x 1], OCV/CPU)|11.355|11.217|1.01|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 512, 26, 26}, OCN=1024, S=[2 x 2], P=[1 x 1], OCV/CPU)|19.062|17.814|1.07|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 64, 104, 104}, OCN=128, P=[1 x 1], OCV/CPU)|6.820|6.531|1.04|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 64, 208, 208}, OCN=128, S=[2 x 2], P=[1 x 1], OCV/CPU)|14.502|13.483|1.08|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 128, 52, 52}, OCN=256, P=[1 x 1], OCV/CPU)|6.270|6.123|1.02|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 128, 104, 104}, OCN=256, S=[2 x 2], P=[1 x 1], OCV/CPU)|13.173|12.451|1.06|
|conv::Conv::(GFLOPS=1.598, K=[3 x 3], IN={1, 32, 208, 208}, OCN=64, P=[1 x 1], OCV/CPU)|8.326|7.652|1.09|
|conv::Conv::(GFLOPS=1.598, K=[3 x 3], IN={1, 32, 416, 416}, OCN=64, S=[2 x 2], P=[1 x 1], OCV/CPU)|17.605|16.465|1.07|
|conv::Conv::(GFLOPS=1.659, K=[3 x 3], IN={1, 960, 10, 10}, OCN=960, PM=SAME, OCV/CPU)|15.675|14.771|1.06|
|conv::Conv::(GFLOPS=1.660, K=[3 x 3], IN={1, 128, 75, 75}, OCN=128, G=128, P=[1 x 1], BIAS, OCV/CPU)|0.420|0.423|0.99|
|conv::Conv::(GFLOPS=1.660, K=[3 x 3], IN={1, 128, 75, 75}, OCN=128, PM=SAME, OCV/CPU)|6.788|6.491|1.05|
|conv::Conv::(GFLOPS=1.675, K=[3 x 3], IN={1, 128, 68, 88}, OCN=128, BIAS, OCV/CPU)|6.456|6.168|1.05|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 256, 38, 38}, OCN=256, G=256, P=[1 x 1], BIAS, OCV/CPU)|0.263|0.261|1.01|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 256, 38, 38}, OCN=256, PM=SAME, OCV/CPU)|7.690|7.398|1.04|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 512, 19, 19}, OCN=512, G=512, P=[1 x 1], BIAS, OCV/CPU)|0.200|0.202|0.99|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 512, 19, 19}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|10.542|10.464|1.01|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 512, 19, 19}, OCN=512, PM=SAME, OCV/CPU)|10.876|10.728|1.01|
|conv::Conv::(GFLOPS=1.766, K=[3 x 3], IN={1, 128, 70, 90}, OCN=128, BIAS, OCV/CPU)|7.194|6.768|1.06|
|conv::Conv::(GFLOPS=1.859, K=[3 x 3], IN={1, 128, 72, 92}, OCN=128, BIAS, OCV/CPU)|7.099|6.731|1.05|
|conv::Conv::(GFLOPS=1.888, K=[3 x 3], IN={1, 1024, 10, 10}, OCN=1024, G=1024, P=[1 x 1], BIAS, OCV/CPU)|0.147|0.162|0.91|
|conv::Conv::(GFLOPS=1.888, K=[3 x 3], IN={1, 1024, 10, 10}, OCN=1024, PM=SAME, OCV/CPU)|18.558|17.141|1.08|
|conv::Conv::(GFLOPS=1.954, K=[3 x 3], IN={1, 128, 74, 94}, OCN=128, BIAS, OCV/CPU)|7.641|7.219|1.06|
|conv::Conv::(GFLOPS=1.995, K=[9 x 9], IN={1, 3, 320, 400}, OCN=32, P=[4 x 4], BIAS, OCV/CPU)|22.666|20.999|1.08|
|conv::Conv::(GFLOPS=2.052, K=[3 x 3], IN={1, 128, 76, 96}, OCN=128, BIAS, OCV/CPU)|8.523|7.921|1.08|
|conv::Conv::(GFLOPS=2.100, K=[3 x 3], IN={1, 144, 75, 75}, OCN=144, PM=SAME, OCV/CPU)|8.514|8.109|1.05|
|conv::Conv::(GFLOPS=2.153, K=[3 x 3], IN={1, 128, 78, 98}, OCN=128, BIAS, OCV/CPU)|8.300|7.878|1.05|
|conv::Conv::(GFLOPS=2.156, K=[3 x 3], IN={1, 576, 19, 19}, OCN=576, PM=SAME, OCV/CPU)|13.403|13.131|1.02|
|conv::Conv::(GFLOPS=2.255, K=[3 x 3], IN={1, 128, 80, 100}, OCN=128, BIAS, OCV/CPU)|8.920|8.357|1.07|
|conv::Conv::(GFLOPS=2.719, K=[3 x 3], IN={1, 96, 256, 256}, OCN=96, S=[2 x 2], PM=SAME, OCV/CPU)|28.827|27.616|1.04|
|conv::Conv::(GFLOPS=3.319, K=[3 x 3], IN={1, 128, 75, 75}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|12.895|12.670|1.02|
|conv::Conv::(GFLOPS=3.321, K=[3 x 3], IN={1, 64, 150, 150}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|14.120|13.078|1.08|
|conv::Conv::(GFLOPS=3.398, K=[7 x 7], IN={1, 128, 46, 46}, OCN=128, P=[3 x 3], BIAS, OCV/CPU)|27.541|27.582|1.00|
|conv::Conv::(GFLOPS=3.407, K=[3 x 3], IN={1, 512, 19, 19}, OCN=1024, D=[6 x 6], P=[6 x 6], BIAS, OCV/CPU)|32.367|31.140|1.04|
|conv::Conv::(GFLOPS=3.408, K=[3 x 3], IN={1, 256, 38, 38}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|14.934|14.910|1.00|
|conv::Conv::(GFLOPS=4.247, K=[3 x 3], IN={1, 480, 32, 32}, OCN=480, PM=SAME, OCV/CPU)|18.289|18.491|0.99|
|conv::Conv::(GFLOPS=4.247, K=[5 x 5], IN={1, 144, 128, 128}, OCN=144, S=[2 x 2], PM=SAME, OCV/CPU)|37.857|36.845|1.03|
|conv::Conv::(GFLOPS=4.566, K=[7 x 7], IN={1, 172, 46, 46}, OCN=128, P=[3 x 3], BIAS, OCV/CPU)|37.402|36.566|1.02|
|conv::Conv::(GFLOPS=4.993, K=[3 x 3], IN={1, 256, 46, 46}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|19.031|19.164|0.99|
|conv::Conv::(GFLOPS=4.993, K=[3 x 3], IN={1, 512, 46, 46}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|19.019|19.135|0.99|
|conv::Conv::(GFLOPS=4.994, K=[3 x 3], IN={1, 128, 92, 92}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|20.077|19.400|1.03|
|conv::Conv::(GFLOPS=4.997, K=[3 x 3], IN={1, 64, 184, 184}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|21.883|21.302|1.03|
|conv::Conv::(GFLOPS=5.780, K=[5 x 5], IN={1, 672, 32, 32}, OCN=672, S=[2 x 2], PM=SAME, OCV/CPU)|51.288|49.851|1.03|
|conv::Conv::(GFLOPS=6.116, K=[3 x 3], IN={1, 1152, 16, 16}, OCN=1152, PM=SAME, OCV/CPU)|27.349|28.359|0.96|
|conv::Conv::(GFLOPS=6.118, K=[3 x 3], IN={1, 144, 128, 128}, OCN=144, PM=SAME, OCV/CPU)|24.915|25.130|0.99|
|conv::Conv::(GFLOPS=6.637, K=[3 x 3], IN={1, 256, 75, 75}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|25.488|25.899|0.98|
|conv::Conv::(GFLOPS=6.638, K=[3 x 3], IN={1, 128, 150, 150}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|27.346|27.390|1.00|
|conv::Conv::(GFLOPS=6.641, K=[3 x 3], IN={1, 64, 150, 200}, OCN=192, PM=SAME, BIAS, OCV/CPU)|28.033|28.301|0.99|
|conv::Conv::(GFLOPS=6.641, K=[3 x 3], IN={1, 64, 300, 300}, OCN=64, P=[1 x 1], BIAS, OCV/CPU)|50.216|49.970|1.00|
|conv::Conv::(GFLOPS=6.814, K=[3 x 3], IN={1, 512, 38, 38}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|29.670|29.513|1.01|
|conv::Conv::(GFLOPS=8.025, K=[3 x 3], IN={1, 1024, 19, 19}, OCN=1206, P=[1 x 1], BIAS, OCV/CPU)|50.565|49.634|1.02|
|conv::Conv::(GFLOPS=9.986, K=[3 x 3], IN={1, 512, 46, 46}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|37.900|37.814|1.00|
|conv::Conv::(GFLOPS=9.987, K=[3 x 3], IN={1, 256, 92, 92}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|41.367|39.742|1.04|
|conv::Conv::(GFLOPS=9.989, K=[3 x 3], IN={1, 128, 184, 184}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|49.128|50.350|0.98|
|conv::Conv::(GFLOPS=9.993, K=[3 x 3], IN={1, 64, 368, 368}, OCN=64, P=[1 x 1], BIAS, OCV/CPU)|79.643|80.645|0.99|
|conv::Conv::(GFLOPS=10.087, K=[3 x 3], IN={1, 576, 38, 50}, OCN=512, PM=SAME, BIAS, OCV/CPU)|41.439|40.895|1.01|
|conv::Conv::(GFLOPS=10.701, K=[3 x 3], IN={1, 512, 38, 38}, OCN=804, P=[1 x 1], BIAS, OCV/CPU)|46.504|46.220|1.01|
|conv::Conv::(GFLOPS=11.797, K=[5 x 5], IN={1, 240, 64, 64}, OCN=240, PM=SAME, OCV/CPU)|98.086|96.842|1.01|
|conv::Conv::(GFLOPS=11.797, K=[5 x 5], IN={1, 480, 32, 32}, OCN=480, PM=SAME, OCV/CPU)|102.447|97.299|1.05|
|conv::Conv::(GFLOPS=16.987, K=[5 x 5], IN={1, 1152, 16, 16}, OCN=1152, PM=SAME, OCV/CPU)|145.047|144.996|1.00|
|conv::Conv::(GFLOPS=23.122, K=[5 x 5], IN={1, 672, 32, 32}, OCN=672, PM=SAME, OCV/CPU)|206.104|195.543|1.05|


### Test on M1(ARM) platform
|Name of Test|4.x|patch|4.x vs patch (x-factor)|
|---|:-:|:-:|:-:|
|conv1d::Conv1D::(GFLOPS=0.000, K=[3], IN={1, 2, 19}, OCN=2, G=2, S=2, P=(1, 1), BIAS, OCV/CPU)|0.001|0.001|0.97|
|conv1d::Conv1D::(GFLOPS=0.000, K=[3], IN={1, 2, 25}, OCN=2, G=2, P=(2, 2), PM=SAME, OCV/CPU)|0.001|0.001|0.94|
|conv1d::Conv1D::(GFLOPS=0.000, K=[3], IN={1, 6, 10}, OCN=6, PM=VALID, BIAS, OCV/CPU)|0.002|0.002|0.92|
|conv3d::Conv3D::(GFLOPS=0.000, K=[1 x 1 x 1], IN={1, 4, 9, 10, 10}, OCN=4, S=[1 x 1 x 2], P=(1, 1) x (1, 1) x (1, 1), PM=VALID, OCV/CPU)|0.003|0.003|1.00|
|conv3d::Conv3D::(GFLOPS=0.000, K=[1 x 1 x 1], IN={1, 8, 1, 10, 10}, OCN=8, G=8, P=(1, 1) x (1, 1) x (1, 1), BIAS, OCV/CPU)|0.003|0.003|1.00|
|conv3d::Conv3D::(GFLOPS=0.000, K=[3 x 3 x 3], IN={1, 2, 19, 19, 19}, OCN=2, G=2, S=[2 x 2 x 2], P=(1, 1) x (1, 1) x (1, 1), BIAS, OCV/CPU)|0.031|0.031|1.00|
|conv3d::Conv3D::(GFLOPS=0.000, K=[3 x 4 x 2], IN={1, 4, 8, 10, 10}, OCN=4, G=4, S=[1 x 2 x 1], BIAS, OCV/CPU)|0.009|0.009|1.00|
|conv3d::Conv3D::(GFLOPS=0.001, K=[3 x 3 x 3], IN={1, 2, 25, 19, 19}, OCN=2, G=2, S=[1 x 2 x 2], P=(2, 2) x (2, 2) x (2, 2), PM=SAME, OCV/CPU)|0.066|0.066|1.01|
|conv3d::Conv3D::(GFLOPS=0.002, K=[3 x 1 x 4], IN={1, 14, 5, 10, 10}, OCN=14, PM=SAME, OCV/CPU)|0.102|0.102|1.00|
|conv3d::Conv3D::(GFLOPS=0.006, K=[5 x 5 x 5], IN={1, 4, 50, 19, 19}, OCN=4, S=[2 x 2 x 2], P=(1, 1) x (1, 1) x (1, 1), PM=VALID, OCV/CPU)|0.328|0.328|1.00|
|conv3d::Conv3D::(GFLOPS=0.027, K=[3 x 3 x 3], IN={1, 6, 10, 38, 50}, OCN=6, PM=VALID, BIAS, OCV/CPU)|0.693|0.747|0.93|
|conv3d::Conv3D::(GFLOPS=0.030, K=[5 x 5 x 5], IN={1, 6, 19, 19, 19}, OCN=6, G=2, OCV/CPU)|1.268|1.266|1.00|
|conv3d::Conv3D::(GFLOPS=0.045, K=[7 x 7 x 7], IN={1, 2, 38, 38, 38}, OCN=2, S=[1 x 2 x 1], OCV/CPU)|3.530|3.581|0.99|
|conv3d::Conv3D::(GFLOPS=0.053, K=[3 x 3 x 3], IN={1, 10, 98, 10, 10}, OCN=10, PM=SAME, OCV/CPU)|1.186|1.188|1.00|
|conv3d::Conv3D::(GFLOPS=0.071, K=[7 x 7 x 7], IN={1, 6, 15, 19, 19}, OCN=6, S=[2 x 1 x 1], P=(3, 3) x (3, 3) x (3, 3), PM=SAME, BIAS, OCV/CPU)|2.682|2.683|1.00|
|conv3d::Conv3D::(GFLOPS=0.093, K=[5 x 5 x 5], IN={1, 4, 40, 75, 75}, OCN=4, S=[2 x 2 x 2], OCV/CPU)|4.490|4.501|1.00|
|conv3d::Conv3D::(GFLOPS=0.116, K=[5 x 5 x 5], IN={1, 2, 21, 75, 100}, OCN=2, BIAS, OCV/CPU)|8.914|8.938|1.00|
|conv3d::Conv3D::(GFLOPS=1.267, K=[5 x 5 x 5], IN={1, 3, 75, 75, 100}, OCN=3, PM=SAME, BIAS, OCV/CPU)|69.819|69.876|1.00|
|conv3d::Conv3D::(GFLOPS=1.343, K=[3 x 3 x 3], IN={1, 11, 9, 150, 200}, OCN=11, PM=VALID, BIAS, OCV/CPU)|24.058|22.420|1.07|
|conv::Conv::(GFLOPS=0.177, K=[1 x 1], IN={1, 512, 26, 26}, OCN=256, OCV/CPU)|2.240|2.236|1.00|
|conv::Conv::(GFLOPS=0.177, K=[1 x 1], IN={1, 1024, 13, 13}, OCN=512, OCV/CPU)|3.132|3.136|1.00|
|conv::Conv::(GFLOPS=0.178, K=[1 x 1], IN={1, 256, 52, 52}, OCN=128, OCV/CPU)|1.920|1.919|1.00|
|conv::Conv::(GFLOPS=0.210, K=[1 x 1], IN={1, 576, 38, 50}, OCN=96, PM=SAME, BIAS, OCV/CPU)|2.343|2.346|1.00|
|conv::Conv::(GFLOPS=0.231, K=[3 x 3], IN={1, 128, 56, 56}, OCN=32, P=[1 x 1], OCV/CPU)|1.234|1.116|1.11|
|conv::Conv::(GFLOPS=0.231, K=[3 x 3], IN={1, 256, 14, 14}, OCN=256, P=[1 x 1], OCV/CPU)|1.109|1.121|0.99|
|conv::Conv::(GFLOPS=0.280, K=[1 x 1], IN={1, 576, 38, 50}, OCN=128, PM=SAME, BIAS, OCV/CPU)|3.197|3.084|1.04|
|conv::Conv::(GFLOPS=0.302, K=[3 x 3], IN={1, 64, 64, 64}, OCN=64, PM=SAME, OCV/CPU)|1.123|1.148|0.98|
|conv::Conv::(GFLOPS=0.357, K=[1 x 1], IN={1, 64, 208, 208}, OCN=64, OCV/CPU)|4.836|5.061|0.96|
|conv::Conv::(GFLOPS=0.420, K=[3 x 3], IN={1, 96, 38, 50}, OCN=128, PM=SAME, BIAS, OCV/CPU)|1.535|1.463|1.05|
|conv::Conv::(GFLOPS=0.472, K=[3 x 3], IN={1, 128, 40, 40}, OCN=128, PM=SAME, OCV/CPU)|1.756|1.584|1.11|
|conv::Conv::(GFLOPS=0.472, K=[3 x 3], IN={1, 256, 20, 20}, OCN=256, PM=SAME, OCV/CPU)|1.821|1.820|1.00|
|conv::Conv::(GFLOPS=0.472, K=[3 x 3], IN={1, 512, 10, 10}, OCN=512, PM=SAME, OCV/CPU)|7.049|6.672|1.06|
|conv::Conv::(GFLOPS=0.561, K=[3 x 3], IN={1, 128, 38, 50}, OCN=128, PM=SAME, BIAS, OCV/CPU)|1.967|1.922|1.02|
|conv::Conv::(GFLOPS=0.624, K=[3 x 3], IN={1, 128, 46, 46}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|1.943|1.977|0.98|
|conv::Conv::(GFLOPS=0.701, K=[3 x 3], IN={1, 128, 38, 50}, OCN=160, PM=SAME, BIAS, OCV/CPU)|2.464|2.310|1.07|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 64, 104, 104}, OCN=64, P=[1 x 1], OCV/CPU)|2.860|2.904|0.98|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 128, 52, 52}, OCN=128, P=[1 x 1], OCV/CPU)|2.428|2.483|0.98|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 256, 26, 26}, OCN=256, P=[1 x 1], OCV/CPU)|2.955|2.983|0.99|
|conv::Conv::(GFLOPS=0.798, K=[3 x 3], IN={1, 512, 13, 13}, OCN=512, P=[1 x 1], OCV/CPU)|4.328|4.484|0.97|
|conv::Conv::(GFLOPS=0.830, K=[3 x 3], IN={1, 64, 75, 100}, OCN=96, PM=SAME, BIAS, OCV/CPU)|2.712|2.778|0.98|
|conv::Conv::(GFLOPS=0.958, K=[3 x 3], IN={1, 192, 38, 38}, OCN=192, PM=SAME, OCV/CPU)|3.205|3.331|0.96|
|conv::Conv::(GFLOPS=0.958, K=[3 x 3], IN={1, 384, 19, 19}, OCN=384, PM=SAME, OCV/CPU)|4.193|4.412|0.95|
|conv::Conv::(GFLOPS=1.022, K=[3 x 3], IN={1, 576, 19, 19}, OCN=273, PM=SAME, BIAS, OCV/CPU)|5.026|4.565|1.10|
|conv::Conv::(GFLOPS=1.112, K=[3 x 3], IN={1, 512, 10, 10}, OCN=1206, P=[1 x 1], BIAS, OCV/CPU)|14.490|14.213|1.02|
|conv::Conv::(GFLOPS=1.181, K=[3 x 3], IN={1, 64, 160, 200}, OCN=128, S=[2 x 2], P=[1 x 1], BIAS, OCV/CPU)|14.886|14.003|1.06|
|conv::Conv::(GFLOPS=1.182, K=[3 x 3], IN={1, 32, 320, 400}, OCN=64, S=[2 x 2], P=[1 x 1], BIAS, OCV/CPU)|15.923|15.184|1.05|
|conv::Conv::(GFLOPS=1.195, K=[9 x 9], IN={1, 32, 240, 320}, OCN=3, P=[4 x 4], BIAS, OCV/CPU)|45.136|41.696|1.08|
|conv::Conv::(GFLOPS=1.196, K=[3 x 3], IN={1, 384, 26, 26}, OCN=256, P=[1 x 1], OCV/CPU)|4.995|4.631|1.08|
|conv::Conv::(GFLOPS=1.210, K=[3 x 3], IN={1, 32, 256, 256}, OCN=32, PM=SAME, OCV/CPU)|6.402|6.261|1.02|
|conv::Conv::(GFLOPS=1.245, K=[3 x 3], IN={1, 64, 75, 75}, OCN=192, PM=SAME, BIAS, OCV/CPU)|4.478|3.965|1.13|
|conv::Conv::(GFLOPS=1.245, K=[3 x 3], IN={1, 96, 75, 100}, OCN=96, PM=SAME, BIAS, OCV/CPU)|3.908|3.978|0.98|
|conv::Conv::(GFLOPS=1.248, K=[3 x 3], IN={1, 256, 46, 46}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|4.176|4.206|0.99|
|conv::Conv::(GFLOPS=1.258, K=[3 x 3], IN={1, 1280, 10, 10}, OCN=546, PM=SAME, BIAS, OCV/CPU)|21.509|21.136|1.02|
|conv::Conv::(GFLOPS=1.261, K=[3 x 3], IN={1, 192, 38, 50}, OCN=192, PM=SAME, BIAS, OCV/CPU)|4.426|4.082|1.08|
|conv::Conv::(GFLOPS=1.416, K=[3 x 3], IN={1, 128, 62, 82}, OCN=128, BIAS, OCV/CPU)|4.098|4.289|0.96|
|conv::Conv::(GFLOPS=1.500, K=[3 x 3], IN={1, 128, 64, 84}, OCN=128, BIAS, OCV/CPU)|4.646|5.105|0.91|
|conv::Conv::(GFLOPS=1.586, K=[3 x 3], IN={1, 128, 66, 86}, OCN=128, BIAS, OCV/CPU)|4.746|4.724|1.00|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 256, 26, 26}, OCN=512, P=[1 x 1], OCV/CPU)|5.614|5.779|0.97|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 256, 52, 52}, OCN=512, S=[2 x 2], P=[1 x 1], OCV/CPU)|21.909|20.718|1.06|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 512, 13, 13}, OCN=1024, P=[1 x 1], OCV/CPU)|8.256|8.290|1.00|
|conv::Conv::(GFLOPS=1.595, K=[3 x 3], IN={1, 512, 26, 26}, OCN=1024, S=[2 x 2], P=[1 x 1], OCV/CPU)|25.196|23.267|1.08|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 64, 104, 104}, OCN=128, P=[1 x 1], OCV/CPU)|5.721|5.172|1.11|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 64, 208, 208}, OCN=128, S=[2 x 2], P=[1 x 1], OCV/CPU)|20.066|18.322|1.10|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 128, 52, 52}, OCN=256, P=[1 x 1], OCV/CPU)|4.448|4.542|0.98|
|conv::Conv::(GFLOPS=1.596, K=[3 x 3], IN={1, 128, 104, 104}, OCN=256, S=[2 x 2], P=[1 x 1], OCV/CPU)|19.193|19.013|1.01|
|conv::Conv::(GFLOPS=1.598, K=[3 x 3], IN={1, 32, 208, 208}, OCN=64, P=[1 x 1], OCV/CPU)|6.009|5.964|1.01|
|conv::Conv::(GFLOPS=1.598, K=[3 x 3], IN={1, 32, 416, 416}, OCN=64, S=[2 x 2], P=[1 x 1], OCV/CPU)|20.169|20.009|1.01|
|conv::Conv::(GFLOPS=1.659, K=[3 x 3], IN={1, 960, 10, 10}, OCN=960, PM=SAME, OCV/CPU)|22.584|23.423|0.96|
|conv::Conv::(GFLOPS=1.660, K=[3 x 3], IN={1, 128, 75, 75}, OCN=128, G=128, P=[1 x 1], BIAS, OCV/CPU)|0.372|0.504|0.74|
|conv::Conv::(GFLOPS=1.660, K=[3 x 3], IN={1, 128, 75, 75}, OCN=128, PM=SAME, OCV/CPU)|5.426|5.456|0.99|
|conv::Conv::(GFLOPS=1.675, K=[3 x 3], IN={1, 128, 68, 88}, OCN=128, BIAS, OCV/CPU)|4.945|5.221|0.95|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 256, 38, 38}, OCN=256, G=256, P=[1 x 1], BIAS, OCV/CPU)|0.210|0.261|0.81|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 256, 38, 38}, OCN=256, PM=SAME, OCV/CPU)|5.720|5.997|0.95|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 512, 19, 19}, OCN=512, G=512, P=[1 x 1], BIAS, OCV/CPU)|0.149|0.161|0.93|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 512, 19, 19}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|7.154|7.225|0.99|
|conv::Conv::(GFLOPS=1.704, K=[3 x 3], IN={1, 512, 19, 19}, OCN=512, PM=SAME, OCV/CPU)|7.184|7.223|0.99|
|conv::Conv::(GFLOPS=1.766, K=[3 x 3], IN={1, 128, 70, 90}, OCN=128, BIAS, OCV/CPU)|5.324|5.343|1.00|
|conv::Conv::(GFLOPS=1.859, K=[3 x 3], IN={1, 128, 72, 92}, OCN=128, BIAS, OCV/CPU)|5.114|5.238|0.98|
|conv::Conv::(GFLOPS=1.888, K=[3 x 3], IN={1, 1024, 10, 10}, OCN=1024, G=1024, P=[1 x 1], BIAS, OCV/CPU)|0.111|0.121|0.92|
|conv::Conv::(GFLOPS=1.888, K=[3 x 3], IN={1, 1024, 10, 10}, OCN=1024, PM=SAME, OCV/CPU)|25.907|26.804|0.97|
|conv::Conv::(GFLOPS=1.954, K=[3 x 3], IN={1, 128, 74, 94}, OCN=128, BIAS, OCV/CPU)|5.695|5.654|1.01|
|conv::Conv::(GFLOPS=1.995, K=[9 x 9], IN={1, 3, 320, 400}, OCN=32, P=[4 x 4], BIAS, OCV/CPU)|27.435|27.566|1.00|
|conv::Conv::(GFLOPS=2.052, K=[3 x 3], IN={1, 128, 76, 96}, OCN=128, BIAS, OCV/CPU)|6.944|6.164|1.13|
|conv::Conv::(GFLOPS=2.100, K=[3 x 3], IN={1, 144, 75, 75}, OCN=144, PM=SAME, OCV/CPU)|7.180|6.717|1.07|
|conv::Conv::(GFLOPS=2.153, K=[3 x 3], IN={1, 128, 78, 98}, OCN=128, BIAS, OCV/CPU)|6.817|6.050|1.13|
|conv::Conv::(GFLOPS=2.156, K=[3 x 3], IN={1, 576, 19, 19}, OCN=576, PM=SAME, OCV/CPU)|9.225|8.660|1.07|
|conv::Conv::(GFLOPS=2.255, K=[3 x 3], IN={1, 128, 80, 100}, OCN=128, BIAS, OCV/CPU)|7.496|6.625|1.13|
|conv::Conv::(GFLOPS=2.719, K=[3 x 3], IN={1, 96, 256, 256}, OCN=96, S=[2 x 2], PM=SAME, OCV/CPU)|35.520|36.056|0.99|
|conv::Conv::(GFLOPS=3.319, K=[3 x 3], IN={1, 128, 75, 75}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|9.990|9.702|1.03|
|conv::Conv::(GFLOPS=3.321, K=[3 x 3], IN={1, 64, 150, 150}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|10.517|10.746|0.98|
|conv::Conv::(GFLOPS=3.398, K=[7 x 7], IN={1, 128, 46, 46}, OCN=128, P=[3 x 3], BIAS, OCV/CPU)|36.702|36.731|1.00|
|conv::Conv::(GFLOPS=3.407, K=[3 x 3], IN={1, 512, 19, 19}, OCN=1024, D=[6 x 6], P=[6 x 6], BIAS, OCV/CPU)|41.035|38.280|1.07|
|conv::Conv::(GFLOPS=3.408, K=[3 x 3], IN={1, 256, 38, 38}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|10.981|10.573|1.04|
|conv::Conv::(GFLOPS=4.247, K=[3 x 3], IN={1, 480, 32, 32}, OCN=480, PM=SAME, OCV/CPU)|12.863|12.384|1.04|
|conv::Conv::(GFLOPS=4.247, K=[5 x 5], IN={1, 144, 128, 128}, OCN=144, S=[2 x 2], PM=SAME, OCV/CPU)|50.437|54.088|0.93|
|conv::Conv::(GFLOPS=4.566, K=[7 x 7], IN={1, 172, 46, 46}, OCN=128, P=[3 x 3], BIAS, OCV/CPU)|50.650|50.635|1.00|
|conv::Conv::(GFLOPS=4.993, K=[3 x 3], IN={1, 256, 46, 46}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|14.696|14.606|1.01|
|conv::Conv::(GFLOPS=4.993, K=[3 x 3], IN={1, 512, 46, 46}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|16.201|15.426|1.05|
|conv::Conv::(GFLOPS=4.994, K=[3 x 3], IN={1, 128, 92, 92}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|16.061|14.292|1.12|
|conv::Conv::(GFLOPS=4.997, K=[3 x 3], IN={1, 64, 184, 184}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|17.743|18.250|0.97|
|conv::Conv::(GFLOPS=5.780, K=[5 x 5], IN={1, 672, 32, 32}, OCN=672, S=[2 x 2], PM=SAME, OCV/CPU)|77.909|78.165|1.00|
|conv::Conv::(GFLOPS=6.116, K=[3 x 3], IN={1, 1152, 16, 16}, OCN=1152, PM=SAME, OCV/CPU)|21.579|21.879|0.99|
|conv::Conv::(GFLOPS=6.118, K=[3 x 3], IN={1, 144, 128, 128}, OCN=144, PM=SAME, OCV/CPU)|20.424|19.589|1.04|
|conv::Conv::(GFLOPS=6.637, K=[3 x 3], IN={1, 256, 75, 75}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|19.389|19.461|1.00|
|conv::Conv::(GFLOPS=6.638, K=[3 x 3], IN={1, 128, 150, 150}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|21.319|20.358|1.05|
|conv::Conv::(GFLOPS=6.641, K=[3 x 3], IN={1, 64, 150, 200}, OCN=192, PM=SAME, BIAS, OCV/CPU)|22.609|21.826|1.04|
|conv::Conv::(GFLOPS=6.641, K=[3 x 3], IN={1, 64, 300, 300}, OCN=64, P=[1 x 1], BIAS, OCV/CPU)|25.497|25.789|0.99|
|conv::Conv::(GFLOPS=6.814, K=[3 x 3], IN={1, 512, 38, 38}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|21.966|22.108|0.99|
|conv::Conv::(GFLOPS=8.025, K=[3 x 3], IN={1, 1024, 19, 19}, OCN=1206, P=[1 x 1], BIAS, OCV/CPU)|35.883|33.470|1.07|
|conv::Conv::(GFLOPS=9.986, K=[3 x 3], IN={1, 512, 46, 46}, OCN=512, P=[1 x 1], BIAS, OCV/CPU)|31.041|29.314|1.06|
|conv::Conv::(GFLOPS=9.987, K=[3 x 3], IN={1, 256, 92, 92}, OCN=256, P=[1 x 1], BIAS, OCV/CPU)|29.922|28.145|1.06|
|conv::Conv::(GFLOPS=9.989, K=[3 x 3], IN={1, 128, 184, 184}, OCN=128, P=[1 x 1], BIAS, OCV/CPU)|31.624|31.148|1.02|
|conv::Conv::(GFLOPS=9.993, K=[3 x 3], IN={1, 64, 368, 368}, OCN=64, P=[1 x 1], BIAS, OCV/CPU)|38.564|39.164|0.98|
|conv::Conv::(GFLOPS=10.087, K=[3 x 3], IN={1, 576, 38, 50}, OCN=512, PM=SAME, BIAS, OCV/CPU)|31.502|30.269|1.04|
|conv::Conv::(GFLOPS=10.701, K=[3 x 3], IN={1, 512, 38, 38}, OCN=804, P=[1 x 1], BIAS, OCV/CPU)|34.248|34.589|0.99|
|conv::Conv::(GFLOPS=11.797, K=[5 x 5], IN={1, 240, 64, 64}, OCN=240, PM=SAME, OCV/CPU)|130.211|134.120|0.97|
|conv::Conv::(GFLOPS=11.797, K=[5 x 5], IN={1, 480, 32, 32}, OCN=480, PM=SAME, OCV/CPU)|127.490|132.874|0.96|
|conv::Conv::(GFLOPS=16.987, K=[5 x 5], IN={1, 1152, 16, 16}, OCN=1152, PM=SAME, OCV/CPU)|199.834|200.081|1.00|
|conv::Conv::(GFLOPS=23.122, K=[5 x 5], IN={1, 672, 32, 32}, OCN=672, PM=SAME, OCV/CPU)|247.346|247.523|1.00|


### 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


```
force_builders=Linux AVX2,Custom Win
build_image:Custom Win=msvs2019
CPU_BASELINE:Custom Win=AVX512_SKX
```
2023-03-10 11:59:49 +03:00
Alexey Shtern
c6e5f60525
Merge pull request #23301 from shtern:fix_quaternion
Fixed strict type in slerp and spline; Fixed nlerp usage condition

Fixes #23293

The PR is fixing the issue described in [Issue #23293 ](https://github.com/opencv/opencv/issues/23293)

- [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
2023-03-10 11:37:43 +03:00
Alexander Smorkalov
29cc675375
Merge pull request #23268 from VadimLevin:dev/vlevin/bindings-io-arg-modifiers-fix
fix: remove extra '/O' modifier for '/IO' arguments
2023-03-10 11:05:03 +03:00
Bhavit Patel
7ea6b356c7
Merge pull request #23305 from bhavitp:fix/calib3d/undistortion_grid
Resolves https://github.com/opencv/opencv/issues/23304

Fixes the incorrect pixel grid
Switches type to double to avoid precision loss as all callers use doubles

### 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
2023-03-10 09:50:36 +03:00
Vincent Rabaud
8ad8ec679f
Merge pull request #22441 from vrabaud:hls_while
In case of huge (and probably invalid) input, make sure we do not
rely only on the while loops for truncation.

### 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
2023-03-07 15:05:38 +03:00
Alexander Alekhin
0052d46b8e Merge pull request #23237 from hzcyf:feature/orbbec_femto_mega_support 2023-03-01 07:13:22 +00:00
Corentin Noël
a035608100 highgui: Reduce the difference between GTK+2 and GTK+3 version
Make the GTK+3 API the default one by wrapping the missing GTK+2 functions in defines
Make sure to always guard with GTK_VERSION2 or GTK_VERSION3 to allow future addition
of Gtk4
2023-02-28 00:48:39 +01:00
Alexander Alekhin
fe59a5695f core(simd): 64-bit integer EQ/NE without misused 64F guard 2023-02-27 19:51:55 +00:00
Alexander Alekhin
9eb5e39ff3 dnn(tflite): fix wrong axis normalization 2023-02-21 21:20:37 +00:00
Alexander Alekhin
5a227352b4 Merge pull request #23274 from alalek:dnn_flatbuffers_builtin 2023-02-21 18:42:49 +00:00
Alexander Alekhin
bdff0949bb dnn(tflite): add 3rdparty flatbuffers with pre-generated schema 2023-02-21 16:06:19 +00:00
Alexander Alekhin
4262127854 Merge pull request #23246 from mshabunin:rvv07-support 2023-02-20 18:06:30 +00:00
Vadim Pisarevsky
ca48e217f1
fixed another SIFT constructor (#23272) 2023-02-18 00:07:45 +03:00
Vadim Pisarevsky
f48939c2d7
temporarily set "enable_precise_upscale=false" by default to avoid sporadic failures in regression tests (#23270) 2023-02-17 18:57:38 +03:00
Stefan Becker
39e2ebbde4 Aruco/Charuco test case fixes for floating point for loops 2023-02-17 16:45:18 +01:00
Maksim Shabunin
903ec0ec60 RISC-V: support RVV 0.7 in mainline RVV intrinsics 2023-02-17 18:17:11 +03:00
Zihao Mu
20dac7ea48
Merge pull request #23255 from zihaomu:fused_cuda_naryeltwise
DNN: fuse conv+naryEletwise on CUDA backend.
2023-02-17 10:18:13 +00:00
Vadim Levin
642942a72f fix: remove extra '/O' modifier for '/IO' arguments 2023-02-17 13:07:28 +03:00
Vaclav Vavra
923dbcc58f
different interpolation by double image (#23124)
* different interpolation by double image

* fixing scaling mapping

* fixing a test

* added an option to enable previous interpolation

* added doxygen entries for the new parameter

* ASSERT_TRUE -> ASSERT_EQ

* changed log message when using old upscale mode
2023-02-17 10:35:54 +03:00
Vladimir Ponomarev
2ab7b7c09e
Remove separator between trackbars.
Remove separator between 2 or more trackbars. This separator has zero thickness and creates bags in toolbar.
2023-02-16 15:18:30 +03:00
Anatoliy Talamanov
6c235c8edb
Merge pull request #23211 from TolyaTalamanov:at/pipeline-modeling-tool-perf-alignment
[G-API] Pipeline modeling tool: Refactor calculating performance statistics

* Add warmup execution

* Align perf metrics

* Add busy wait mode for source

* Small fix for late frames

* pl_fn to src_fn

* Change show statistics

* Correct warm-up iteration

* Properly calculate drop frames

* Enable frame dropping for streaming mode

* Enable frame dropping for streaming mode

* Fix comments to review

* Fix typos

* Cosmetic
2023-02-15 14:04:14 +03:00
Lilit Grigoryan
a87b9fb4b6 Fix focal length estimation from homography matrix 2023-02-14 21:51:09 +03:00
Alexander Alekhin
58d8a2702a Merge pull request #23243 from WanliZhong:accelerate_palm_det 2023-02-14 16:25:02 +00:00
Corentin Noël
f1f14ce403 highgui: Set hard GLib requirement to >=2.32
This version has been released 10 years ago.
2023-02-14 13:28:42 +01:00
Dmitry Kurtaev
76350cd30f
Merge pull request #23161 from dkurt:dnn_tflite
TFLite models importer

* initial commit

* Refactor TFLiteImporter

* Better FlatBuffers detection

* Add permute before 4D->3D reshape

* Track layers layout

* TFLite Convolution2DTransposeBias layer

* Skip TFLite tests without FlatBuffers

* Fix check of FlatBuffers in tests. Add readNetFromTFLite from buffer

* TFLite Max Unpooling test

* Add skip for TFLite unpooling test

* Revert DW convolution workaround

* Fix ObjC bindings

* Better errors handling

* Regenerate TFLite schema using flatc

* dnn(tflite): more checks, better logging

* Checks for unimplemented fusion. Fix tests
2023-02-13 14:00:20 +00:00
Alexander Alekhin
47293f28cf Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2023-02-11 18:35:00 +00:00
hzcyf
325fe7e663 add support for Orbbec Femto Mega RGB-D camera 2023-02-11 16:22:35 +08:00
Yannis Guyon
56102737d7
Merge pull request #23131 from y-guyon:align_ptr_intrin_sse
Fix misaligned-pointer-use in intrin_sse.hpp

* Fix misaligned-pointer-use in intrin_sse.hpp

* Use _mm_loadu_si32() instead of memcpy()

* Use CV_DECL_ALIGNED instead of _mm_loadu_si32()
2023-02-10 22:46:21 +00:00
Yuantao Feng
c2b7c1f13b
Merge pull request #23219 from fengyuentau:add_gelu
Add GELU layer for vision transformers

* add gelu and gelu approximation

* drop setKernelParams
2023-02-10 18:03:29 +00:00
wanli
c8f5e228fc release MUL and ADD operator on CUDA 2023-02-10 19:33:59 +08:00
Alexander Alekhin
96a45e842e
Merge pull request #23061 from WanliZhong:gemm_cuda
DNN: make GEMM can be supported with transA and transB in CUDA
2023-02-09 00:06:32 +03:00
Ibai Gorordo
c280cd7290
Merge pull request #23210 from ibaiGorordo:rect_nfa_bugfix
Fix rect_nfa (lsd)

* Fix missing log_gamma in nfa()

Comparing the nfa function with the function in the binomial_nfa repository (https://github.com/rafael-grompone-von-gioi/binomial_nfa/blob/main/C99/log_binomial_nfa.c#L152), the first log_gamma call is missing.

* Fix rect_nfa pixel index

* Replace std::rotate

* Rename tmp to v_tmp

* Replace auto and std::min_element

* Change slope equality check to int

* Fix left limit check
2023-02-08 17:33:06 +00:00
Alexander Alekhin
44290af516 Merge pull request #23224 from VadimLevin:dev/vlevin/cxx-named-arguments 2023-02-08 17:31:30 +00:00
Alexander Alekhin
649841e6bf Merge pull request #23225 from mshabunin:fix-clang-warnings 2023-02-08 17:28:07 +00:00
Maksim Shabunin
e4acd74e87 Fix some clang 14 warnings 2023-02-07 01:19:00 +03:00
Vadim Levin
b07031b594 feat: named arguments handling in Python interface 2023-02-06 22:14:58 +03:00
Alexander Smorkalov
3d635cb4a7 Warning supression fix for XCode 13.1 and newer. Backport #23203 2023-02-06 11:12:05 +03:00
keith siilats
b0aace31ec
Update charuco_detector.cpp
Delete the debug print statements accidentally left in
2023-02-05 19:39:25 -05:00
Tinson Lai
f8f425e34c
Change custom_hal.hpp output location 2023-02-03 18:21:15 +08:00
Alexander Smorkalov
c855dcc52f Supressed tones of Wdeprecated-copy that jump out of GTes after XCode update to 13.1 on Mac M1. 2023-02-02 13:54:47 +03:00
whuaegeansea
400572b19f Fix bug 2023-02-01 11:25:31 +08:00
wanli
4718a4bf81 make GEMM can be supported with transA and transB in CUDA 2023-01-31 15:14:17 +08:00
Maksim Shabunin
9efaa3cce7 RISC-V/RVV 0.7: v_add/v_sub saturation and avoiding 64-bit register in v_check_ 2023-01-30 23:25:53 +03:00
Alexander Smorkalov
ff8af10cfe
Merge pull request #23168 from genciberisha/bug/issue-22205_and_23105_encodeStructuredAppend_problem
Fix encodeStructuredAppend() resulting in only one QR code problem, and false output data fix.
2023-01-30 09:15:18 +03:00
Alexander Alekhin
cd44aa0bb1 Merge pull request #23162 from zihaomu:issue_23151 2023-01-28 13:00:43 +00:00
Alexander Alekhin
d3ae175bca Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2023-01-28 10:01:23 +00:00
Rostislav Vasilikhin
deaf632881
Merge pull request #23179 from savuor:port34_stddev_calib_fisheye
Backport to 3.4 of the fisheye calibration uncertainty fix

* uncertainties fix

* trailing whitespace

* comment added
2023-01-28 09:56:13 +00:00
Alexander Alekhin
c67d4fc633 Merge pull request #23076 from inayd:22012-bugfixFillPoly 2023-01-28 09:55:02 +00:00
zihaomu
f45a12439a fix depth wise issue. 2023-01-28 11:41:00 +08:00
Yuantao Feng
4d918ba40b
Merge pull request #23047 from fengyuentau:layer_norm
dnn: add layer normalization for vision transformers

* add layer norm onnx parser, impl and tests

* add onnx graph simplifier for layer norm expanded

* handle the case when constants are of type Initializer

* add test case for layer norm expanded with initializers

* use CV_Assert & CV_CheckType in place of CV_Assert_N; use forward_fallback for OCL_FP16

* use const ref / ref in parameters of invoker::run; extract inner const if from nested loop; use size_t in place of ull

* template hasBias

* remove trailing whitespace

* use pointer parameter with null check; move normSize division & mean_square division outside of loop; use std::max to ensure positive value before std::sqrt

* refactor implementation, optimize parallel_for

* disable layer norm expanded

* remove the removal of layer norm optional outputs
2023-01-27 16:35:59 +03:00
Yannis Guyon
bf29a4d746 Avoid double-checked locking with TSAN in parallel
Omit the first check of the double-checked locking pattern in
recordException() in parallel.cpp when CV_THREAD_SANITIZER is defined.
This should only slow recordException() down when the thread sanitizer
is used, and avoids the TSAN data race warning.
2023-01-27 13:36:33 +01:00
Genci Berisha
743d4ecf7b generateQR() method data loss fix
Added regression parameterized test for Structure Append mode

final_qr_code clear outside generateQR() method
2023-01-26 23:30:14 +01:00
Alexander Alekhin
52855a39ad Merge pull request #23165 from labeeb-7z:optimizeDistanceTransform 2023-01-25 16:52:46 +00:00
Lilo Huang
cb7fe597a5
Merge pull request #23172 from lilohuang:master
Adding HEVC/H265 FourCC support to MSMF video writer

* Adding HEVC/H265 fourcc to MSMF video writer

Adding HEVC/H265 fourcc to MSMF video writer. I have verified it with my own video input stream, and it works well on my workstation.

* Update video io testing

* Adding macro fence to get rid of compiler error

H265/HEVC encoder is only available in Windows or later. https://learn.microsoft.com/en-us/windows/win32/medfound/h-265---hevc-video-encoder

* Update test_video_io.cpp
2023-01-25 04:49:08 +00:00
Alexander Alekhin
8ffc06ff72 Merge pull request #23173 from tomoaki0705:fix_warning_master 2023-01-23 15:33:16 +00:00
Tomoaki Teshima
186c18668c suppress warning 2023-01-23 22:47:43 +09:00
Rostislav Vasilikhin
4009bca59a
Merge pull request #23025 from savuor:backport3_stddev_calib_fix
Backport of #22992 to 3.4

### 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
2023-01-23 14:59:43 +03:00
Alexander Alekhin
18cbfa4a4f Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2023-01-23 00:11:12 +00:00
Alexander Alekhin
b71a168937 Merge pull request #23154 from tomoaki0705:handleNonBitExact 2023-01-21 18:14:25 +00:00
Labib Asari
35c17f35be removed redundant code 2023-01-21 00:16:48 +05:30
Alexander Smorkalov
3085fc6345
Merge pull request #23073 from savuor:fix_graphcut_used_edges_dense
USAC fix: GraphCut fails to allocate big dense matrices
2023-01-20 14:55:40 +03:00
Alexander Alekhin
17e860a288 Merge pull request #16189 from mshabunin:enable-two-channels 2023-01-20 08:51:46 +00:00
Tomoaki Teshima
1833b034fe make test tolerate to rounding error 2023-01-19 22:06:52 +09:00
Alexander Alekhin
69020666fe test: reproducible results, enabled 2-channel tests, increased some thresholds 2023-01-19 15:39:33 +03:00
Alexander Alekhin
53144ee0eb perf: drop runtime time adjustment calibration 2023-01-18 22:13:30 +00:00
Funatomi Takuya
dbdd357b0a Extend USAC coverage.
Add `estimateSE2(...)`, `estimateSE3(...)`, `estimateSIM2(...)`, `estimateSIM3(...)` for estimating an geometric transformation with rotation and translation (with scaling for SIM) using USAC: as alternative for `estimateAffinePartial2D` and `estimateAffine3D`.

Modified test module.

Remove unused variables.

Remove initializer of unused variable.

Add interfaces to accept UsacParams() and corresponding test codes.

Revise test code.

PartialNd removed

Umeyama rewritten for code quality & speed

comments & minors

rise number of points

fix, and +30% faster!

only one number should be that big

remove USAC code, leave fix only

big number
2023-01-18 02:12:57 +01:00
Rostislav Vasilikhin
f3a03aefad cvIsInf(double) fix + regression test 2023-01-17 23:06:39 +01:00
Maksim Shabunin
c1e5c16ff3 Backport C-API cleanup (imgproc) from 5.x 2023-01-16 23:29:50 +03:00
Yuantao Feng
c63d79c5b1
Merge pull request #23095 from fengyuentau:fix_omp_macos
* fix openmp include and link issue on macos

* turn off have_openmp if OpenMP_CXX_INCLUDE_DIRS is empty

* test commit

* use condition HAVE_OPENMP and OpenMP_CXX_LIBRARIES for linking

* remove trailing whitespace

* remove notes

* update conditions

* use OpenMP_CXX_LIBRARIES for linking
2023-01-16 12:44:13 +03:00
Alexander Alekhin
a9d02f096e Merge pull request #23126 from cudawarped:fix_issue_3412 2023-01-13 13:08:27 +00:00
Ihsan Soydemir
6a7d54f550
Merge pull request #23128 from Isydmr:update-fastNlMeansDenoising-documentation
Fix broken paper link for fastNlMeansDenoising

* Fix broken link

* Move citation to `opencv.bib`

* Cite researchgate reference

* Correct citation label

* Use semantic scholar BibTex
2023-01-12 19:54:40 +03:00
Alexander Alekhin
3d5e3a910f Merge pull request #23096 from zihaomu:issue_23074 2023-01-12 00:51:04 +00:00
Xxfore
ef0fcb9238
Merge pull request #22938 from Xxfore:4.x
Use reinterpret instead of c-style casting for GCC

Co-authored-by: Xu Zhang <xu.zhang@hexintek.com>
Co-authored-by: Maksim Shabunin <maksim.shabunin@gmail.com>
2023-01-11 14:11:16 +00:00
cudawarped
b5bf756ca0 core: define cuda test size with row/col of 1 2023-01-11 14:52:46 +02:00
zihaomu
840b1d5c94 add depthwise add fuse 2023-01-11 08:42:51 +08:00
Alexander Alekhin
974102bc7f Merge pull request #23120 from alalek:fixup_22246_2 2023-01-10 10:01:17 +00:00
Alexander Alekhin
5bacd8753b build: eliminate GCC9 warning from sift.simd.hpp 2023-01-10 01:38:12 +00:00
Alexander Alekhin
65c2d6a2be Merge pull request #23112 from zihaomu:fix_x86_winograd 2023-01-09 19:37:29 +00:00
Yang Chao
e0aa677388 Open CV_CPU_NEON_DOTPROD on Apple silicon devices 2023-01-09 19:27:35 +08:00
Alexander Alekhin
36815fe3f3 videoio(test): skip unstable Media.audio test 2023-01-09 10:06:10 +00:00
Christoph Rackwitz
a64b51dd94
Merge pull request #23108 from crackwitz:issue-23107
Usage of imread(): magic number 0, unchecked result

* docs: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()

* samples, apps: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()

* tests: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()

* doc/py_tutorials: check imread() result
2023-01-09 09:55:31 +00:00
zihaomu
82616eec41 fix possible segmentation fault error in winograd on x86 2023-01-09 13:40:04 +08:00
inayd
54449b614b Fix occuring artifacts in fillPoly 2023-01-03 16:29:13 +01:00
Alexander Alekhin
9208dcb07c Merge tag '4.7.0' 2022-12-28 15:23:46 +00:00
Alexander Smorkalov
725e440d27 release: OpenCV 4.7.0 2022-12-28 17:31:52 +03:00
Alexander Panov
121034876d
Merge pull request #22986 from AleksandrPanov:move_contrib_charuco_to_main_objdetect
merge with https://github.com/opencv/opencv_contrib/pull/3394

move Charuco API from contrib to main repo:

- add CharucoDetector:
```
CharucoDetector::detectBoard(InputArray image, InputOutputArrayOfArrays markerCorners, InputOutputArray markerIds, 
                             OutputArray charucoCorners, OutputArray charucoIds) const // detect charucoCorners and/or markerCorners
CharucoDetector::detectDiamonds(InputArray image, InputOutputArrayOfArrays _markerCorners,
                                InputOutputArrayOfArrays _markerIds, OutputArrayOfArrays _diamondCorners,
                                OutputArray _diamondIds) const
```

- add `matchImagePoints()` for `CharucoBoard`
- remove contrib aruco dependencies from interactive-calibration tool
- move almost all aruco tests to objdetect

### Pull Request Readiness Checklist

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
2022-12-28 17:28:59 +03:00
Alexander Alekhin
9627ab9462 Merge pull request #23050 from zihaomu:fix_memory 2022-12-28 10:04:25 +00:00
zihaomu
71765858dc fix invalid memory access 2022-12-28 17:16:11 +08:00
Alexander Alekhin
9a2a34f94e dnn(openvino): remove undefined status 2022-12-28 06:55:00 +00:00
Alexander Alekhin
38f7cd7173 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2022-12-27 08:58:28 +00:00
Alexander Alekhin
eab7faf536 Merge tag '3.4.19' 2022-12-27 08:41:49 +00:00
Alexander Alekhin
83391ac59d release: OpenCV 3.4.19 2022-12-27 03:50:12 +00:00
Alexander Alekhin
a8a93a57e7 Merge pull request #23029 from savuor:backport3_fix_fisheye_aspect_ratio 2022-12-27 03:47:01 +00:00
Alexander Alekhin
f637629c5a Merge pull request #23037 from cudawarped:fix_for_cuda_12 2022-12-27 03:43:59 +00:00
Rostislav Vasilikhin
93aa94e71e backported changes
no lambda

whitespace

fixing build Java tests
2022-12-27 00:54:39 +01:00
Alexander Alekhin
86b46a27cf Merge pull request #23039 from alalek:cmake_3.5_fix 2022-12-26 20:31:39 +00:00
Alexander Alekhin
1bc3077890 cmake: VERSION_GREATER_EQUAL is not supported in CMake 3.5.1 2022-12-26 17:41:53 +00:00
Alexander Alekhin
fc27a343e9 Merge pull request #22905 from zihaomu:clean_up_conv3d_1d 2022-12-26 17:39:18 +00:00
cudawarped
692d6168b3 cuda: fix CUDA 12.0 build errors 2022-12-26 15:25:29 +02:00
Alexander Alekhin
de9787a6ac Merge pull request #23036 from asmorkalov:as/blobdetect_range_fix 2022-12-26 12:47:45 +00:00
Alexander Smorkalov
b7292bc899 Fixed blob detector parameters range. 2022-12-26 15:02:24 +03:00
Alexander Alekhin
dbd4a0e5e6 videoio(ffmpeg): update tests with new Windows wrapper 2022-12-26 02:32:11 +00:00
Alexander Alekhin
b42c11de82 pre: OpenCV 4.7.0 (version++) 2022-12-25 17:00:22 +00:00
Alexander Alekhin
a494c75bfe pre: OpenCV 3.4.19 (version++) 2022-12-25 16:59:47 +00:00
Alexander Alekhin
bc8c912c7a Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2022-12-24 13:54:58 +00:00
zihaomu
8e6aae0d7a Add spaces to make links clickable. 2022-12-24 15:26:42 +08:00
Dmitry Kurtaev
8681686d8f
Merge pull request #22957 from dkurt:new_openvino_api
Switch to new OpenVINO API after 2022.1 release

* Pass Layer_Test_Convolution_DLDT.Accuracy/0 test

* Pass test Test_Caffe_layers.Softmax

* Failed 136 tests

* Fix Concat. Failed 120 tests

* Custom nGraph ops. 19 failed tests

* Set and get properties from Core

* Read model from buffer

* Change MaxPooling layer output names. Restore reshape

* Cosmetic changes

* Cosmetic changes

* Override getOutputsInfo

* Fixes for OpenVINO < 2022.1

* Async inference for 2021.4 and less

* Compile model with config

* Fix serialize for 2022.1

* Asynchronous inference with 2022.1

* Handle 1d outputs

* Work with model with dynamic output shape

* Fixes with 1d output for old API

* Control outputs by nGraph function for all OpenVINO versions

* Refer inputs in PrePostProcessor by indices

* Fix cycled dependency between InfEngineNgraphNode and InfEngineNgraphNet.
Add InferRequest callback only for async inference. Do not capture InferRequest object.

* Fix tests thresholds

* Fix HETERO:GPU,CPU plugin issues with unsupported layer
2022-12-23 16:58:41 +00:00
Alexander Smorkalov
9012e6dd9b
Merge pull request #22965 from vrabaud:numpy_fix
Remove references to deprecated NumPy type aliases.
2022-12-23 15:34:02 +03:00
Alexander Smorkalov
4930516652
Merge pull request #22898 from fengyuentau:slice_neg_steps
dnn: support ONNX Slice with negative steps by adding and using cv::flipND
2022-12-23 14:15:06 +03:00
Vincent Rabaud
ad568edd7f Remove references to deprecated NumPy type aliases.
This change replaces references to a number of deprecated NumPy
type aliases (np.bool, np.int, np.float, np.complex, np.object,
np.str) with their recommended replacement (bool, int, float,
complex, object, str).

Those types were deprecated in 1.20 and are removed in 1.24,
cf https://github.com/numpy/numpy/pull/22607.
2022-12-23 13:53:49 +03:00
Maxim Milashchenko
62b3a20da5
Merge pull request #22930 from MaximMilashchenko:gstreamer_support
Support one-time audio video reading

* stream switching functionality

* audio+video pipeline with switch stream functionality

* audio video sync

* fixed sync

* removed switch swtream functionality

* changed test for gstreamer audio

* fixed error

* fixed error

* fixed issue

* fixed issue

* fixed error

* fixed error

* fixed error
2022-12-23 10:15:22 +00:00
Alexander Alekhin
1f41d06f9a Merge pull request #23008 from mshabunin:fix-yolov4-tiny-hash 2022-12-23 10:14:25 +00:00
Sergei Shutov
1339c7f30c Define the number of dstChannels for Lab, Luv, YCrCb and XYZ conversions 2022-12-23 12:04:30 +02:00
Alexander Smorkalov
734fb18c4d
Merge pull request #23017 from asmorkalov:as/qrcode_valgrind
Valgrind issues fix in QRCode detector.
2022-12-23 12:10:29 +03:00
zihaomu
71c6339af0 remove old convolution branch, and optimize conv3d and conv1d. 2022-12-23 16:50:28 +08:00
fengyuentau
34a0897f90 add cv::flipND; support onnx slice with negative steps via cv::flipND 2022-12-23 16:39:53 +08:00
Alexander Smorkalov
a32100d9ba Valgrind issues fix in QRCode detector. 2022-12-23 10:50:31 +03:00
Alexander Alekhin
b5400902a7
Merge pull request #23002 from alalek:issue_22206
* obj-c: de-duplicate values of nested enums

- prefix with outer class name

* obj-c: handle enum names change in assigned values

* obj-c: switch on 'const_fix'

* obj-c: add NS_SWIFT_NAME
2022-12-22 14:01:21 +00:00
Maksim Shabunin
d35fbe6bfc dnn: updated YOLOv4-tiny model and tests 2022-12-22 15:49:21 +03:00
Alexander Smorkalov
44dfe62af0
Merge pull request #22914 from tozanski:tomoz/ransac-bugfix
Bugfix for solvePnPRansac with SOLVEPNP_ITERATIVE
2022-12-22 11:58:14 +03:00
Alexander Alekhin
4acb267cf4 Merge pull request #23014 from alalek:ffmpeg_default_threads 2022-12-22 07:57:24 +00:00
Alexander Alekhin
8676d19dc3 videoio(ffmpeg): limit number of default threads 2022-12-22 04:45:29 +00:00
Alexander Alekhin
6b4f3e5fab Merge pull request #22993 from alalek:fixup_21738 2022-12-21 19:50:51 +00:00
Vincent Rabaud
b774753922 Fix self converTo.
We still need images[i] = img because it is used below in buildPyramid.
2022-12-21 18:28:26 +01:00
Marco Feuerstein
bc8d494617
Merge pull request #22959 from feuerste:parallel_mertens
Parallelize implementation of HDR MergeMertens.

* Parallelize MergeMertens.

* Added performance tests for HDR.

* Ran clang-format.

* Optimizations.

* Fix data path for Windows.

* Remove compiiation warning on Windows.

* Remove clang-format for existing file.

* Addressing reviewer comments.

* Ensure correct summation order.

* Add test for determinism.

* Move result pyramid into sync struct.

* Reuse sync for first loop as well.

* Use OpenCV's threading primitives.

* Remove cout.
2022-12-21 14:10:59 +00:00
Alexander Smorkalov
1ab259df9a
Merge pull request #23005 from alalek:objdetect_cleanup_aruco_ptr_filestorage
aruco(cleanup): don't use Ptr<FileStorage>
2022-12-21 16:45:14 +03:00
augustinmanecy
0bd54a60e9
Merge pull request #20367 from augustinmanecy:features2d-rw
**Merge with contrib**: https://github.com/opencv/opencv_contrib/pull/3003

### 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 other license that is incompatible with OpenCV
- [x] The PR is proposed to proper branch
- [ ] There is reference to original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2022-12-21 16:03:00 +03:00
Alexander Smorkalov
63b6b24cd0
Merge pull request #22967 from stopmosk:usac-maxiters-bugfix
Fix maxIter parameter in usac findEssentialMat
2022-12-21 15:58:44 +03:00
Alexander Alekhin
c6a15e1835 aruco(cleanup): don't use Ptr<FileStorage> 2022-12-21 10:52:43 +00:00
Alexander Smorkalov
91ac790249
Merge pull request #23001 from alalek:videoio_init_vars
videoio(v4l): initialize variables
2022-12-21 09:56:55 +03:00
Sergei Shutov
3cfe737581 Fix hardcoded maxIters 2022-12-21 09:51:59 +03:00
Yuantao Feng
a2b3acfc6e
dnn: add the CANN backend (#22634)
* cann backend impl v1

* cann backend impl v2: use opencv parsers to build models for cann

* adjust fc according to the new transA and transB

* put cann net in cann backend node and reuse forwardLayer

* use fork() to create a child process and compile cann model

* remove legacy code

* remove debug code

* fall bcak to CPU backend if there is one layer not supoorted by CANN backend

* fix netInput forward
2022-12-21 09:04:41 +03:00
Alexander Alekhin
f4b23de9dd videoio(v4l): initialize variables 2022-12-21 03:28:09 +00:00
Alexander Alekhin
a08c98cdfb Merge pull request #22995 from alalek:dnn_fix_opencl_matmul 2022-12-20 14:52:35 +00:00
Alexander Smorkalov
279e2be56b
Merge pull request #22963 from cudawarped:replace_texture_ref_with_texture_obj
Replace all instances of CUDA texture references with texture objects
2022-12-20 15:07:10 +03:00