mmpose
mmselfsup
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| mmpose | mmselfsup | |
|---|---|---|
| 31 | 5 | |
| 5,002 | 3,084 | |
| 4.8% | 1.8% | |
| 8.0 | 5.3 | |
| 4 days ago | 10 months 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.
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
mmselfsup
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
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Does anyone know how a loss curve like this can happen? Details in comments
For some reason, the loss goes up shaply right at the start and slowly goes back down. I am self-supervised pretraining an image modeling with DenseCL using mmselfsup (https://github.com/open-mmlab/mmselfsup). This shape happened on the Coco-2017 dataset and my custom dataset. As you can see, it happens consistently for different runs. How could the loss increase so sharply and is it indicative of an issue with the training? The loss peaks before the first epoch is finished. Unfortunately, the library does not support validation.
- Defect Detection using RPI
- [D] State-of-the-Art for Self-Supervised (Pre-)Training of CNN architectures (e.g. ResNet)?
- Rebirth! OpenSelfSup is upgraded to MMSelfSup
What are some alternatives?
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
mmaction2 - OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
mmagic - OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.
deep-high-resolution-net.pytorch - The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
barlowtwins - Implementation of Barlow Twins paper
AdelaiDet - AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]