Added more data types to OCL flip() and rotate() perf tests #26115
Connected PR with updated sanity data: https://github.com/opencv/opencv_extra/pull/1206
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Avoid uninitialized value read in resize. #26084
When there is no point falling right, an hypothetical value is computed (but unused) using an uninitialized ofst. This triggers warnings in the sanitizers.
Including those values in the for loops is also possible but messy when SIMD is involved.
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Remove the redundant codes of cv::convertMaps and mRGBA2RGBA<uchar> #26071
(1) cv::convertMaps: the branch [else if( m1type == CV_32FC2 && dstm1type == CV_16SC2 ) if( nninterpolate )] is unreachable,
as the condition is satisfied in lines 1959 to 1961, calculated in advance and return directly.
(2) mRGBA2RGBA<uchar>: dst[0], dst[1], dst[2] and dst[3] is calculated repeatedly. Introduced in https://github.com/opencv/opencv/pull/13440
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Update test_tiff.cpp #26093
related #22090
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Added offset for HAL as ofs2idx expects 1-based index #26080
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DNN(ONNX): Enabled several OpenCL conformance tests #26053
The tests also work in 5.x
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Fixed the simd bugs of iPow8u and iPow16u #26061
Add the following cases in opencv_perf_core:
* OCL_PowFixture_iPow.iPow/0, where GetParam() = (640x480, 8UC1)
* OCL_PowFixture_iPow.iPow/2, where GetParam() = (640x480, 16UC1)
iPow8u and iPow16u failed to call to simd accelerating while executing.
Fix the bug by changing the input type of iPow_SIMD function.
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Einsum buffer allocation fix#26059
This PR fixed buffer allocation issue in Einsum layer that causes segmentation fault on 32bit platforms. Related issue #26008
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Imgproc: use double to determine whether the corners points are within src #26022close#26016
Related https://github.com/opencv/opencv_contrib/pull/3778
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Split Javascript white-list to support contrib modules #25986
Single whitelist converted to several per-module json files. They are concatenated automatically and can be overriden by user config.
Related to https://github.com/opencv/opencv/pull/25656
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Increase neighbors search radius for corners in ChessBoardDetector:findQuadNeighbors #26014
I didn't do everything right the way I wanted at #25991. I forgot that `edge_len` is edge **squared** length as well as `thresh_scale` is threshold for **squared** scale. So, I wanted to increase scale by `sqrt(2)` times (idea is to use quad diagonal instead of quad side) and therefore `thresh_scale` should be equal to `sqrt(2)^2 = 2`.
And refactor variables names to explicitly indicate that they are squared, so that no one else falls into this trap
I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```
PR increases detected chessboards number by `1/2%`:
```
cell_img_size = 100 (default)
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.941667 13560 14400 0.596726
Total detected time: 136.68963200000007 sec
after
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.952083 13710 14400 0.595984
Total detected time: 136.55770600000014 sec
----------------------------------------------------------------------------------------------------------------------------------------------
cell_img_size = 10
before
category detected chessboard total detected chessboard total chessboard average detected error chessboard
all 0.579167 8340 14400 4.198448
Total detected time: 2.535998999999999 sec
after
category detected chessboard total detected chessboard total chessboard average detected error
all 0.591389 8516 14400 4.155250
Total detected time: 2.700832999999997 sec
```
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dnn: add ONNX TopK #23279
Merge with https://github.com/opencv/opencv_extra/pull/1200
Partially fixes#22890 and #20258
To-do:
- [x] TopK forward impl
- [x] add tests
- [x] support Opset 1 & 10 if possible
- [ ] ~Support other backends~ (TopK has two outputs, which is not supported by other backends, such as openvino)
Perf:
M1 (time in millisecond)
| input shape | axis | dnn | ort |
| --------------- | ---- | ---- | ---- |
| (1000, 100) | 0 | 1.68 | 4.07 |
| (1000, 100) K5 | 0 | 1.13 | 0.12 |
| (1000, 100) | 1 | 0.96 | 0.77 |
| (100, 100, 100) | 0 | 10.00 | 31.13 |
| (100, 100, 100) | 1 | 7.33 | 9.17 |
| (100, 100, 100) | 2 | 7.52 | 9.48 |
M2 (time in milisecond)
| input shape | axis | dnn | ort |
| --------------- | ---- | ---- | ---- |
| (1000, 100) | 0 | 0.76 | 2.44 |
| (1000, 100) K5 | 0 | 0.68 | 0.07 |
| (1000, 100) | 1 | 0.41 | 0.50 |
| (100, 100, 100) | 0 | 4.83 | 17.52|
| (100, 100, 100) | 1 | 3.60 | 5.08 |
| (100, 100, 100) | 2 | 3.73 | 5.10 |
ONNXRuntime performance testing script: https://gist.github.com/fengyuentau/a119f94fd16721ec9974b8c7b0a45d4c
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Correct Bayer2Gray u8 SIMD #25968
SIMD version of CV_DESCALE is not correct. It should be implemented using v_dotprod.
What's more, the stop condition of vector operation should be `bayer < bayer_end - 14` because we just need to make sure result is safely stored into `dst`.
Closes: https://github.com/opencv/opencv/issues/25823
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Unified build.gradle files into one template #26009
Issue #24686
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