[evolution] Stitching for OpenCV 4.0
* stitching: wrap Stitcher::create for bindings
* provide method for consistent stitcher usage across languages
* samples: add python stitching sample
* port cpp stitching sample to python
* stitching: consolidate Stitcher create methods
* remove Stitcher::createDefault, it returns Stitcher, not Ptr<Stitcher> -> inconsistent API
* deprecate cv::createStitcher and cv::createStitcherScans in favor of Stitcher::create
* stitching: avoid anonymous enum in Stitcher
* ORIG_RESOL should be double
* add documentatiton
* stitching: improve documentation in Stitcher
* stitching: expose estimator in Stitcher
* remove ABI hack
* stitching: drop try_use_gpu flag
* OCL will be used automatically through T-API in OCL-enable paths
* CUDA won't be used unless user sets CUDA-enabled classes manually
* stitching: drop FeaturesFinder
* use Feature2D instead of FeaturesFinder
* interoperability with features2d module
* detach from dependency on xfeatures2d
* features2d: fix compute and detect to work with UMat vectors
* correctly pass UMats as UMats to allow OCL paths
* support vector of UMats as output arg
* stitching: use nearest interpolation for resizing masks
* fix warnings
* Support for Matx read/write by FileStorage
* Only empty filestorage read now produces default Matx. Split Matx IO test into smaller units. Test checks for exception thrown if reading a Mat into a Matx of different size.
* moved DIS optical flow from opencv_contrib to opencv, moved TVL1 from opencv to opencv_contrib
* fixed compile warning
* TVL1 optical flow example moved to opencv_contrib
* significantly reduced OpenCV binary size by disabling IPP calls in some OpenCV functions: Sobel, Scharr, medianBlur, GaussianBlur, filter2D, mean, meanStdDev, norm, sum, minMaxIdx, sort.
* re-enable IPP in norm, since it's much faster (without adding too much space overhead)
* removed C API in the following modules: photo, video, imgcodecs, videoio
* trying to fix various compile errors and warnings on Windows and Linux
* continue to fix compile errors and warnings
* continue to fix compile errors, warnings, as well as the test failures
* trying to resolve compile warnings on Android
* Update cap_dc1394_v2.cpp
fix warning from the new GCC
G-API GPU-OpenCL backend (#13008)
* gpu/ocl backend core
* accuracy tests added and adjusted + license headers
* GPU perf. tests added; almost all adjusted to pass
* all tests adjusted and passed - ready for pull request
* missing license headers
* fix warning (workaround RGB2Gray)
* fix c++ magic
* precompiled header
* white spaces
* try to fix warning and blur test
* try to fix Blur perf tests
* more alignments with the latest cpu backend
* more gapi tests refactoring + 1 more UB issue fix + more informative tolerance exceed reports
* white space fix
* try workaround for SumTest
* GAPI_EXPORTS instead CV_EXPORTS
V4L (V4L2): Refactoring. Added missed camera properties. Fixed getting `INF` for some properties. Singlethread as always (#12893)
* cap_v4l:
1 Added cap_properties verbalization.
2 Set Get of properties elementary refactoring.
3 Removed converting parameters to/from [0,1] range.
4 Added all known conversion from V4L2_CID_* to CV_CAP_PROP_*
* cap_v4l:
1. Removed all query for parameters range.
2. Refactored capture initialization.
3. Added selecting input channel by CV_CAP_PROP_MODE. Default value -1 the channels not changed.
* cap_v4l:
1. Refactoring of Convert To RGB
* cap_v4l:
1. Fixed use of video buffer index.
2. Removed extra memcopy for grab image.
3. Removed device closing from autosetup_capture_mode_v4l2
* cap_v4l:
1. The `goto` was eliminated
2. Fixed use of temporary buffer index for V4L2_PIX_FMT_SN9C10X
3. Fixed use of the bufferIndex
4. Removed trailing spaces and unused variables.
* cap_v4l:
1. Alias for capture->buffers[capture->bufferIndex]
2. Reduced size of data for memcpy: bytesused instead of length
3. Refactoring. Code duplication. More info for debug
* cap_v4l:
1. Added the ability to grab and retrieveFrame independently several times
* cap_v4l:
1. Not need to close/open device for new capture parameters applying.
2. Removed using of device name as a flag that the capture is closed. Added sufficient function.
3. Refactoring. Added requestBuffers and createBuffers
* cap_v4l:
1. Added tryIoctl with `select` like was in mainloop_v4l2.
2. Fixed buffer request for device without closing the device.
3. Some static function moved to CvCaptureCAM_V4L
4. Removed unused defines
* cap_v4l:
1. Thread-safe now
* cap_v4l:
1. Fixed thread-safe destructor
2. Fixed FPS setting
* Missed brake
* Removed thread-safety
* cap_v4l:
1. Reverted conversion parameters to/from [0,1] by default for backward compatibility.
2. Added setting for turn off compatibility mode: set CV_CAP_PROP_MODE to 65536
3. Most static functions moved to CvCaptureCAM_V4L
4. Refactoring of icvRetrieveFrameCAM_V4L and using of frame_allocated flag
* cap_v4l:
1. Added conversion to RGB from NV12, NV21
2. Refactoring. Removed wrappers for known format conversions.
* Added `CAP_PROP_CHANNEL` to the enum VideoCaptureProperties.
CAP_V4L migrated to use VideoCaptureProperties.
* 1. Update comments.
2. Environment variable `OPENCV_VIDEOIO_V4L_RANGE_NORMALIZED` for setting default backward compatibility mode.
3. Revert getting of `CAP_PROP_MODE` as fourcc code in backward compatibility mode.
* videoio: update cap_v4l - compatibilityMode => normalizePropRange
* videoio(test): V4L2 MJPEG test
`v4l2-ctl --list-formats` should have 'MJPG' entry
* videoio: fix buffer initialization
to avoid "munmap: Invalid argument" messages
* Updated boxFilter implementations to use wide universal intrinsics
* boxFilter implementation moved to separate file
* Replaced ROUNDUP macro with roundUp() function
This is a workaround for GPU hang on heavy convolution workload (> 10 GFLOPS).
e.g. ResNet101_DUC_HDC
For the long time task, vkWaitForFences() return without error but next call on
vkQueueSubmit() return -4, i.e. "VK_ERROR_DEVICE_LOST" and driver reports GPU hang.
Need more investigation on root cause of GPU hang and need to optimize convolution shader
to reduce process time.
During the cluster-based detection of circle grids, the detected circle
pattern has to be mapped to 3D-points. When doing this the width (i.e.
more circles) and height (i.e. less circles) of the pattern need to
be identified in image coordinates.
Until now this was done by assuming that the shorter side in image
coordinates (length in pixels) corresponds to the height in 3D.
This assumption does not hold if we look at the pattern from
a perspective where the projection of the width is shorter
than the projection of the height. This in turn lead to misdetections in
although the circle pattern was clearly visible.
Instead count how many circles have been detected along two edges of the
projected quadrangle and use the one with more circles as width and the
one with less as height.
Dmitry Kurtaev
catree
Alexander Alekhin
Jiri Horner
Vadim Pisarevsky
Matt Bennett
Pavel Rojtberg
Alexander Alekhin
Ruslan Garnov
Dmitry Budnikov
Alexey Nikolaev
tompollok
unknown
Vitaly Tuzov
gineshidalgo99
Wu Zhiwen
Evgeny Latkin
lqy123000
berak
Suleyman TURKMEN
LaurentBerger
Jean Carass
fegorsch
Vitaly Tuzov