facebookresearch / frankmocap

A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator
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Add onnx runtime inference on pose model #189

Open lucasjinreal opened 2 years ago

lucasjinreal commented 2 years ago

Add onnx runtime inference on lightweight pose model. This enables more simplier inference and faster speed on CPU compare with Pytorch. More importantly, onnx make all inference code much more simpler and don't require original repo as dependencies. The onnx export can be get from:

https://github.com/jinfagang/lightweight-human-pose-estimation.pytorch

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lucasjinreal commented 2 years ago

@penincillin Can u take a look at this PR. I added onnx inference on human-pose-estimation, what's more, I also added onnx export for HMR model.

In terms of HRM, on CPU, onnxruntime runs faster than Pytorch even more, 70ms vs 90ms.

And the inference code much more simplifier. which can be easily used for deployment or some other useful scenarios such as VTuber etc.

facebook-github-bot commented 2 years ago

Thank you for signing our Contributor License Agreement. We can now accept your code for this (and any) Meta Open Source project. Thanks!