mim
mmaction2
mim | mmaction2 | |
---|---|---|
1 | 5 | |
329 | 3,916 | |
1.2% | 2.3% | |
5.6 | 7.2 | |
6 months ago | 30 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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mim
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MIM: MIM installs OpenMMLab packages.
mmaction2
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How good does contextual action recognition get?
Mmaction2: https://github.com/open-mmlab/mmaction2 Has some examples.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMAction2: OpenMMLab's next-generation action understanding toolbox and benchmark.
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[D] Deep Learning Framework for C++.
I agree with you for most of the time this can work but there are some models that have certain layers that are not supported by ONNX. An example would be Spatiotemporal models in mmaction2 from open-mmlab.
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Textbook or blogs for video understanding
No book or blog, but a great framework: https://github.com/open-mmlab/mmaction2
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Applications of Deep Neural Networks [pdf]
shameless ad: try mmaction2, where every result is reproducible https://github.com/open-mmlab/mmaction2 . Modelzoo: https://mmaction2.readthedocs.io/en/latest/modelzoo.html
What are some alternatives?
mmgeneration - MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.
mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.
mmhuman3d - OpenMMLab 3D Human Parametric Model Toolbox and Benchmark
compare_gan - Compare GAN code.
mmpretrain - OpenMMLab Pre-training Toolbox and Benchmark
mmflow - OpenMMLab optical flow toolbox and benchmark
mmcv - OpenMMLab Computer Vision Foundation
temporal-shift-module - [ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
Video-Dataset-Loading-Pytorch - Generic PyTorch dataset implementation to load and augment VIDEOS for deep learning training loops.
mmdetection3d - OpenMMLab's next-generation platform for general 3D object detection.
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark