Fisheye test has been updated to use new enum cv::fisheye::CALIB_ZERO_DISPARITY and included CV_StaticAssert(...) to ensure cv::CALIB_ZERO_DISPARITY == cv::fisheye::CALIB_ZERO_DISPARITY.
- detect case with infinite loop and raise NoConv exception
- handle such exception
- add support for case with missing `blobDetector` (image contains Point2f array of candidates)
- add regression test
- undone rectification for "failed" detections too
- drop redirectError() usage
Enable frame timestamp tests for MSMF
Add functional test for camera live timestamps
Remove trailing whitespace
Add timestamp test to all functional tests. Protect div by 0
Add Timestamps to MSMF Video Capture by index
- Suppressed FFMPEG + h264, h265 as it does not pass tests with CI configuration.
- Suppressed MediaFoundation backend as it always returns zero for now.
Support for Pool1d layer for OpenCV and OpenCL targets
* Initial version of Pool1d support
* Fix variable naming
* Fix 1d pooling for OpenCL
* Change support logic, remove unnecessary variable, split the tests
* Remove other depricated variables
* Fix warning. Check tests
* Change support check logic
* Change support check logic, 2
Added SQPnP algorithm to SolvePnP
* Added sqpnp
* Fixed test case
* Added fix for duplicate point checking and inverse func reuse
* Changes for 3x speedup
Changed norm method (significant speed increase), changed nearest rotation computation to FOAM
* Added symmetric 3x3 inverse and unrolled loops
* Fixed error with SVD
* Fixed error from with indices
Indices were initialized negative. When nullspace is large, points coplanar, and rotation near 0, indices not changed.
Fixing dnn Resize layer for variable input size
* Fix onnx loading of resize/upsample layers for different opset
* group all DynamicResize tests
* cleaned up scales checks
* Simplify branching
The most of target machine use one type cpu unit resource
to execute some one type of instruction, e.g.
all vx_load API use load/store cpu unit,
and v_muladd API use mul/mula cpu unit, we interleave
vx_load and v_muladd to improve performance on most targets like
RISCV or ARM.
Fix loading issue for Faster RCNN model from #16783
* Add a reproducer with multi-output Gather
* Fix an issue with ONNX graph simplifier
* fix build
* Move checks to correct class
* Minor changes for better code appearence
Add support for Conv1D on OpenCV backend
* Add support for Conv1D on OpenCV backend
* disable tests on other targets/backends
* Fix formatting
* Restore comment
* Remove unnecessary flag and fix test logic
* Fix perf test
* fix braces
* Fix indentation, assert check and remove unnecessary condition
* Remove unnecessary changes
* Add test cases for variable weights and bias
* dnn(conv): fallback on OpenCV+CPU instead of failures
* coding style
Detection and decoding of curved QR-codes
* temp changes for curved qrcodes
* added api for curved qr code decoding
* fixed prototypes
* refactored curved qr code decoding
* refactored curved qr code decoding 2nd part
* refactored curved qr code decoding 3rd part
* refactored curved qr code decoding 4th part
* added tests for curved qr code decoding
* refactored curved qr code decoding 5th part
Fixes two errors when building with the options WITH_CUDA=ON and BUILD_CUDA_STUBS=ON on a machine without CUDA.
In the cudaarithm module, make sure cuda_runtime.h only gets included when CUDA is installed.
In the stitching module, don't assume that cuda is present just because cudaarithm and cudawarping are present (as is the case when building with the above options).
[GSoC] OpenCV.js: WASM SIMD optimization 2.0
* gsoc_2020_simd Add perf test for filter2d
* add perf test for kernel scharr and kernel gaussianBlur
* add perf test for blur, medianBlur, erode, dilate
* fix the errors for the opencv PR robot
fix the trailing whitespace.
* add perf tests for kernel remap, warpAffine, warpPersepective, pyrDown
* fix a bug in modules/js/perf/perf_imgproc/perf_remap.js
* add function smoothBorder in helpfun.js and remove replicated function in perf test of warpAffine and warpPrespective
* fix the trailing white space issues
* add OpenCV.js loader
* Implement the Loader with help of WebAssembly Feature Detection, remove trailing whitespaces
* modify the explantion for loader in js_setup.markdown and fix bug in loader.js
Fix loading of ONNX models with Resize operation with Opset 11 for newer versions of Pytorch
* Add reproducer for Resize operation from newer versions of Pytorch
* Fix loading of scales parameter for Resize layer
* Change check type for better diagnostic messages
Fix KD Tree kNN Implementation
* Make KDTree mode in kNN functional
remove docs and revert change
Make KDTree mode in kNN functional
spacing
Make KDTree mode in kNN functional
fix window compilations warnings
Make KDTree mode in kNN functional
fix window compilations warnings
Make KDTree mode in kNN functional
casting
Make KDTree mode in kNN functional
formatting
Make KDTree mode in kNN functional
* test coding style
Bit exact gaussian blur for 16bit unsigned int
* bit-exact gaussian kernel for CV_16U
* SIMD optimization
* template GaussianBlurFixedPoint
* remove template specialization
* simd support for h3N121 uint16
* test for u16 gaussian blur
* remove unnecessary comments
* fix return type of raw()
* add typedef of native internal type in fixedpoint
* update return type of raw()
Bit-exact Nearest Neighbor Resizing
* bit exact resizeNN
* change the value of method enum
* add bitexact-nn to ResizeExactTest
* test to compare with non-exact version
* add perf for bit-exact resizenn
* use cvFloor-equivalent
* 1/3 scaling is not stable for floating calculation
* stricter test
* bugfix: broken data in case of 6 or 12bytes elements
* bugfix: broken data in default pix_size
* stricter threshold
* use raw() for floor
* use double instead of int
* follow code reviews
* fewer cases in perf test
* center pixel convention
* Fix ONNX loading in issues opencv#17516, opencv#17531
* Add tests for Linear and Matmul layers
* Disable tests for IE versions lower than 20.4
* Skip unstable tests with OpenCL FP16 on Intel GPU
* Add correct test filtering for OpenCL FP16 tests
- OpenCL kernel cleanup processing is asynchronous and can be called even after forced clFinish()
- buffers are released later in asynchronous mode
- silence these false positive cases for asynchronous cleanup