mmaction2
mmpose
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| mmaction2 | mmpose | |
|---|---|---|
| 5 | 31 | |
| 3,884 | 4,969 | |
| 3.3% | 4.2% | |
| 7.8 | 8.4 | |
| 16 days ago | 23 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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
mmpose
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RTMPose: The All-In-One Real-time Pose Estimation Solution for R&D
RTMPose-m achieves 75.8% AP on COCO with 90+ FPS on an Intel i7-11700 CPU and 430+ FPS on an NVIDIA GTX 1660 Ti GPU, and RTMPose-l achieves 67.0% AP on COCO-WholeBody with 130+ FPS.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMPose: OpenMMLab pose estimation toolbox and benchmark.
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Model conversion from Pytorch to Tf using Onnx.
I downloaded pytorch2onnx.py from mmPose tools. It's big, but the top half is imports and input arguments. Line 125, I hard-coded my (image) input size. I ran it on my .pth model file, and out pop'd an onnx file.
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Finetuning Openpose for custom dataset
They have a specific repo called mmpose: https://github.com/open-mmlab/mmpose
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State of the art 2D body pose estimation [Discussion]
I would start with mmpose. It's basically a curated list of the best models ready to go.
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[P] Object detection framework : Detectron2 VS MMDetection
The [MMLab key point detection](https://github.com/open-mmlab/mmpose) is in a separate repo from detection.
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[D] Searching for open source pose estimation solution similar to open pose ?
One option is mmPose. They have a bunch of 2D/3D models implemented and support different skeleton structures.
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Human Pose Estimation Recommendation
This library is pretty good. It has implementations for a number of pose estimators. I think Darkpose is the best one from memory
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Human pose classification problem.
Check out https://github.com/open-mmlab/mmpose I think they have guides for new datasets
What are some alternatives?
compare_gan - Compare GAN code.
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
mmflow - OpenMMLab optical flow toolbox and benchmark
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
temporal-shift-module - [ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
Video-Dataset-Loading-Pytorch - Generic PyTorch dataset implementation to load and augment VIDEOS for deep learning training loops.
deep-high-resolution-net.pytorch - The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark
AdelaiDet - AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
deep-diamond - A fast Clojure Tensor & Deep Learning library
mmfewshot - OpenMMLab FewShot Learning Toolbox and Benchmark