* Fix gst error handling
* Use the return value instead of the error, which gives no guarantee of being NULL in case of error
* Test err pointer before accessing it
* Remove unreachable code
* videoio(gstreamer): restore check in writer code
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Fix ORB integer overflow
* set size_t step to fix integer overflow in ptr0 offset
* added issue_537 test
* minor fix tags, points
* added size_t_step and offset to remove mixed unsigned and signed operations
* features2d: update ORB checks
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
* dnn: fix unaligned memory access crash on armv7
The getTensorContent function would return a Mat pointing to some
member of a Protobuf-encoded message. Protobuf does not make any
alignment guarantees, which results in a crash on armv7 when loading
models while bit 2 is set in /proc/cpu/alignment (or the relevant
kernel feature for alignment compatibility is disabled). Any read
attempt from the previously unaligned data member would send SIGBUS.
As workaround, this commit makes an aligned copy via existing clone
functionality in getTensorContent. The unsafe copy=false option is
removed. Unfortunately, a rather crude hack in PReLUSubgraph in fact
writes(!) to the Protobuf message. We limit ourselves to fixing the
alignment issues in this commit, and add getTensorContentRefUnaligned
to cover the write case with a safe memcpy. A FIXME marks the issue.
* dnn: reduce amount of .clone() calls
* dnn: update FIXME comment
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Make the implementation of optimization in DNN adjustable to different vector sizes with RVV intrinsics.
* Update fastGEMM for multi VLEN.
* Update fastGEMM1T for multi VLEN.
* Update fastDepthwiseConv for multi VLEN.
* Update fastConv for multi VLEN.
* Replace malloc with cv::AutoBuffer.
dnn : int8 quantized layers support in onnx importer
* added quantized layers support in onnx importer
* added more cases in eltwise node, some more checks
* added tests for quantized nodes
* relax thresholds for failed tests, address review comments
* refactoring based on review comments
* added support for unsupported cases and pre-quantized resnet50 test
* relax thresholds due to int8 resize layer
* Prefix global javascript functions with sub-namespaces
* js: handle 'namespace_prefix_override', update filtering
- avoid functions override with same name but different namespace
Co-authored-by: Alexander Alekhin <alexander.a.alekhin@gmail.com>
Add ExpandDims layer of tf_importer.cpp
* Add ExpandDims to tf_importer.
* add -1 expand test case.
* Support different dimensions of input.
* Compatible with 5-dimensional NDHWC data
* Code align
* support 3-dim input.
* 3-dim bug fixed.
* fixing error of code format.
* Add RowVec_8u32f
* Fix build errors in Linux x64 Debug and armeabi-v7a
* Reformat code to make it more clean and conventional
* Optimise with vx_load_expand_q()
Recover pose from different cameras (version 2)
* add recoverPose for two different cameras
* Address review comments from original PR
* Address new review comments
* Rename private api
Co-authored-by: tompollok <tom.pollok@gmail.com>
Co-authored-by: Zane <zane.huang@mail.utoronto.ca>
This submission is used to improve the performance of the inpaint algorithm for 3 channels images(RGB or BGR).
Reason:
The original algorithm implementation did not consider the cache hits.
The loop of channels is outside the core loop, so the perfmance is not very good.
Moving the channel loop inside the core loop can significantly improve cache hits, thereby improving performance.
Performance:
360P, about >= 30% improvement
iphone8P: 5.52ms -> 3.75ms
iphone6s: 14.04ms -> 9.15ms
G-API: Handle reshape for generic case in GExecutor
* Handle reshape for generic case for GExecutor
* Add initResources
* Add tests
* Refactor reshape method
different paddings in cvtColorTwoPlane() for biplane YUV420
* Different paddings support in cvtColorTwoPlane() for biplane YUV420
* Build fix for dispatch case.
* Resoted old behaviour for y.step==uv.step to exclude perf regressions.
Co-authored-by: amir.tulegenov <amir.tulegenov@xperience.ai>
Co-authored-by: Alexander Smorkalov <alexander.smorkalov@xperience.ai>
* feat: OpenCV extension with pure Python modules
* feat: cv2 is now a Python package instead of extension module
Python package cv2 now can handle both Python and C extension modules
properly without additional "subfolders" like "_extra_py_code".
* feat: can call native function from its reimplementation in Python
Add support for YOLOv4x-mish
* backport to 3.4 for supporting yolov4x-mish
* add YOLOv4x-mish test
* address review comments
Co-authored-by: Guo Xu <guoxu@1school.com.cn>
Add CAP_PROP_STREAM_OPEN_TIME
* Added CAP_PROP_STREAM_OPEN_TIME to videoio module - can be used to query the time at which the stream was opened, in seconds since Jan 1 1970 (midnight, UTC). Useful for RTSP and other live video where absolute timestamps are needed. Only applicable to ffmpeg backends
* use nanoseconds instead of seconds to mark the stream open time, and change the cap prop name to CAP_PROP_STREAM_OPEN_TIME_NSEC
* use microseconds for CAP_PROP_STREAM_OPEN_TIME (nanoseconds rolls over too soon, and milliseconds/seconds requires a division)
* fix whitespace issue
Add Normalize subgraph, fix Slice, Mul and Expand
* Add Normalize subgraph, support for starts<0 and axis<0 in Slice, Mul broadcasting in the middle and fix Expand's unsqueeze
* remove todos
* remove range-based for loop
* address review comments
* change >> to > > in template
* fix indexation
* fix expand that does nothing
* support PPSeg model for dnn module
* fixed README for CI
* add test case
* fixed bug
* deal with comments
* rm dnn_model_runner
* update test case
* fixed bug for testcase
* update testcase
`PyObject*` to `std::vector<T>` conversion logic:
- If user passed Numpy Array
- If array is planar and T is a primitive type (doesn't require
constructor call) that matches with the element type of array, then
copy element one by one with the respect of the step between array
elements. If compiler is lucky (or brave enough) copy loop can be
vectorized.
For classes that require constructor calls this path is not
possible, because we can't begin an object lifetime without hacks.
- Otherwise fall-back to general case
- Otherwise - execute the general case:
If PyObject* corresponds to Sequence protocol - iterate over the
sequence elements and invoke the appropriate `pyopencv_to` function.
`std::vector<T>` to `PyObject*` conversion logic:
- If `std::vector<T>` is empty - return empty tuple.
- If `T` has a corresponding `Mat` `DataType` than return
Numpy array instance of the matching `dtype` e.g.
`std::vector<cv::Rect>` is returned as `np.ndarray` of shape `Nx4` and
`dtype=int`.
This branch helps to optimize further evaluations in user code.
- Otherwise - execute the general case:
Construct a tuple of length N = `std::vector::size` and insert
elements one by one.
Unnecessary functions were removed and code was rearranged to allow
compiler select the appropriate conversion function specialization.
[G-API] Extend compileStreaming to support different overloads
* Make different overloads
* Order python compileStreaming overloads
* Fix compileStreaming bug
* Replace
gin -> descr_of
* Set error message
* Fix review comments
* Use macros for pyopencv_to GMetaArgs
* Use GAPI_PROP_RW
* Not split Prims python stuff
* Added exposure and gain props, maximized pixel clk
* removed pixel clock maximization
pixel clock maximization is not suitable for all use cases, so I removed it from PR.