* 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
Alexander Alekhin
Jonas Vautherin
Alexander Panov
Smirnov Egor
Oliver Kuckertz
Giles Payne
HAN Liutong
Jebastin Nadar
keroiber
xhawk18
Zihao Mu
YashasSamaga
Jannik Bamberger
Suleyman TURKMEN
shengyu
Tomoaki Teshima
Anatoliy Talamanov
Smirnov Alexey
Sergey Ivanov
Cavendish-Koo
Alexander Smorkalov
Nicholas Ho
thezane
easonycwang
Ruslan Garnov