Fix the CPU HRNet Nuclio function #6150
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It was broken for two reasons: * Due to some changes on the PyTorch website, the old way of installing the PyTorch packages now installs the ROCm version rather than the CPU version (and it doesn't work doe to a missing dependency). * The newest version of NumPy doesn't work with HRNet due to the latter's usage of `np.int`. Fix these problems, and in addition, rework the build recipe to avoid installing unneeded packages. Altogether, the changes massively shrink the Docker image size (from ~14 GB to ~2 GB). I didn't update the GPU version, because a) the first issue doesn't affect it, b) the second issue is already fixed in it, and c) I don't have a GPU to test it on.
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nmanovic
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May 18, 2023
### Added - Introduced a new configuration option for controlling the invocation of Nuclio functions. (<#6146>) ### Changed - Relocated SAM masks decoder to frontend operation. (<#6019>) - Switched `person-reidentification-retail-0300` and `faster_rcnn_inception_v2_coco` Nuclio functions with `person-reidentification-retail-0277` and `faster_rcnn_inception_resnet_v2_atrous_coco` respectively. (<#6129>) - Upgraded OpenVINO-based Nuclio functions to utilize the OpenVINO 2022.3 runtime. (<#6129>) ### Fixed - Resolved issues with tracking multiple objects (30 and more) using the TransT tracker. (<#6073>) - Addressed azure.core.exceptions.ResourceExistsError: The specified blob already exists. (<#6082>) - Corrected image scaling issues when transitioning between images of different resolutions. (<#6081>) - Fixed inaccurate reporting of completed job counts. (<#6098>) - Allowed OpenVINO-based Nuclio functions to be deployed to Kubernetes. (<#6129>) - Improved skeleton size checks after drawing. (<#6156>) - Fixed HRNet CPU serverless function. (<#6150>) - Prevented sending of empty list of events. (<#6154>)
mikhail-treskin
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Jul 1, 2023
<!-- Raise an issue to propose your change (https://github.com/opencv/cvat/issues). It helps to avoid duplication of efforts from multiple independent contributors. Discuss your ideas with maintainers to be sure that changes will be approved and merged. Read the [Contribution guide](https://opencv.github.io/cvat/docs/contributing/). --> <!-- Provide a general summary of your changes in the Title above --> ### Motivation and context <!-- Why is this change required? What problem does it solve? If it fixes an open issue, please link to the issue here. Describe your changes in detail, add screenshots. --> It was broken for two reasons: * Due to some changes on the PyTorch website, the old way of installing the PyTorch packages now installs the ROCm version rather than the CPU version (and it doesn't work doe to a missing dependency). * The newest version of NumPy doesn't work with HRNet due to the latter's usage of `np.int`. Fix these problems, and in addition, rework the build recipe to avoid installing unneeded packages. Altogether, the changes massively shrink the Docker image size (from ~14 GB to ~2 GB). I didn't update the GPU version, because a) the first issue doesn't affect it, b) the second issue is already fixed in it, and c) I don't have a GPU to test it on. ### How has this been tested? <!-- Please describe in detail how you tested your changes. Include details of your testing environment, and the tests you ran to see how your change affects other areas of the code, etc. --> Manual testing with CVAT. ### Checklist <!-- Go over all the following points, and put an `x` in all the boxes that apply. If an item isn't applicable for some reason, then ~~explicitly strikethrough~~ the whole line. If you don't do that, GitHub will show incorrect progress for the pull request. If you're unsure about any of these, don't hesitate to ask. We're here to help! --> - [x] I submit my changes into the `develop` branch - [x] I have added a description of my changes into the [CHANGELOG](https://github.com/opencv/cvat/blob/develop/CHANGELOG.md) file - ~~[ ] I have updated the documentation accordingly~~ - ~~[ ] I have added tests to cover my changes~~ - ~~[ ] I have linked related issues (see [GitHub docs]( https://help.github.com/en/github/managing-your-work-on-github/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword))~~ - ~~[ ] I have increased versions of npm packages if it is necessary ([cvat-canvas](https://github.com/opencv/cvat/tree/develop/cvat-canvas#versioning), [cvat-core](https://github.com/opencv/cvat/tree/develop/cvat-core#versioning), [cvat-data](https://github.com/opencv/cvat/tree/develop/cvat-data#versioning) and [cvat-ui](https://github.com/opencv/cvat/tree/develop/cvat-ui#versioning))~~ ### License - [x] I submit _my code changes_ under the same [MIT License]( https://github.com/opencv/cvat/blob/develop/LICENSE) that covers the project. Feel free to contact the maintainers if that's a concern. Co-authored-by: Boris Sekachev <boris.sekachev@yandex.ru>
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Motivation and context
It was broken for two reasons:
Due to some changes on the PyTorch website, the old way of installing the PyTorch packages now installs the ROCm version rather than the CPU version (and it doesn't work doe to a missing dependency).
The newest version of NumPy doesn't work with HRNet due to the latter's usage of
np.int.Fix these problems, and in addition, rework the build recipe to avoid installing unneeded packages. Altogether, the changes massively shrink the Docker image size (from ~14 GB to ~2 GB).
I didn't update the GPU version, because a) the first issue doesn't affect it, b) the second issue is already fixed in it, and c) I don't have a GPU to test it on.
How has this been tested?
Manual testing with CVAT.
Checklist
developbranch[ ] I have updated the documentation accordingly[ ] I have added tests to cover my changes[ ] I have linked related issues (see GitHub docs)[ ] I have increased versions of npm packages if it is necessary(cvat-canvas,
cvat-core,
cvat-data and
cvat-ui)
License
Feel free to contact the maintainers if that's a concern.