CANN (Compute Architecture of Neural Networks), developped by Huawei, is
a heterogeneous computing architecture for AI. Opencv DNN has already
suppoted CANN backend [#22634](https://github.com/opencv/opencv/pull/22634).
There are more and more users using [Ascend NPU](https://www.hiascend.com/)
and programming with CANN, and the number is still growing rapidly.
AI training and inference are inseparable from data preprocessing.
When users use OpenCV to work with CANN backend, data preprocessing can
only run on CPUs, resulting in inefficiency.
The purpose of this commit is to enable OpenCV operators on CANN backend.
The usage of CANN backend is consistent, Please refer to OpenCV DNN: [CANN backend manual]
(https://gist.github.com/fengyuentau/083f7f339592545c1f1d2c1fde6a53dc#file-a_ocv_cann-md):
1. [Install dependencies]
(https://gist.github.com/fengyuentau/083f7f339592545c1f1d2c1fde6a53dc#install-dependencies)
2. [Install CANN]
(https://gist.github.com/fengyuentau/083f7f339592545c1f1d2c1fde6a53dc#install-cann)
3. [Compile OpenCV with CANN]
(https://gist.github.com/fengyuentau/083f7f339592545c1f1d2c1fde6a53dc#build-opencv-with-cann)
The CANN backend is used in a similar way to CUDA:
| Object | CANN | CUDA |
| --------- | ------------ | -------- |
| Namespace | cv::cann | cv::cuda |
| Matrix | AscendMat | GpuMat |
| Stream | AscendStream | Stream |
| Event | AscendEvent | Event |
The current commit provides CANN backend operator support framework, In
order to make code viewing easy, only a few basic interfaces are
implemented, all of the following operators are tested and compared
result with CPU backend.
More operators will continue implement in new independent commits.
Co-authored-by: CaoMengqing <cmq0113@163.com>
cudacodec::VideoReader: allow frame seek on initialization #3542
Allow seeking of video source on initialization of `cudacodec::VideoReader` when new variable `VideoReaderInitParams::iFirstFrame` != 0.
Dependant on https://github.com/opencv/opencv/pull/24012
Fixes https://github.com/opencv/opencv_contrib/issues/3541.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Fix typing error
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
* fix(wechat_qrcode): Initialize nBytes after the count value is determined
* fix(wechat_qrcode): Incorrect count data repair
* chore: format expr
* fix(wechat_qrcode): Avoid null pointer exception
* fix(wechat_qrcode): return when bytes_ is empty
* test(wechat_qrcode): add test case
---------
Co-authored-by: GZTime <Time.GZ@outlook.com>
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