Please see get_started.md for the basic usage of MMPose. Please refer to install.md for detailed installation guide.Ĭonda create -n openmmlab python=3.8 pytorch=1.10 cudatoolkit=11.3 torchvision -c pytorch -y : OpenMMLab Open Platform is online! Try our pose estimation demo.MMPose Webcam API is a simple yet powerful tool to develop interactive webcam applications with MMPose features. : MMPose model deployment is supported by MMDeploy v0.3.0.Update Swin models with better performance.Add RLE pre-trained model on COCO dataset.We provide detailed documentation and API reference, as well as unittests. Pose estimation framework by combining different modules. We decompose MMPose into different components and one can easily construct a customized See data_preparation.md for more information. The toolbox directly supports multiple popular and representative datasets, COCO, AIC, MPII, MPII-TRB, OCHuman etc. We achieve faster training speed and higher accuracy than other popular codebases, such as HRNet. MMPose implements multiple state-of-the-art (SOTA) deep learning models, including both top-down & bottom-up approaches. We support a wide spectrum of mainstream pose analysis tasks in current research community, including 2d multi-person human pose estimation, 2d hand pose estimation, 2d face landmark detection, 133 keypoint whole-body human pose estimation, 3d human mesh recovery, fashion landmark detection and animal pose estimation. The master branch works with PyTorch 1.5+. MMPose is an open-source toolbox for pose estimation based on PyTorch.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |