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README.md
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More details are available in [OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics](https://arxiv.org/abs/2406.09788).
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This particular variant was finetuned on a set of keypoints usually found on Motion Capture setups, and include coco keypoints as well.
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The model predicts 52 markers:
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```
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## Installation
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This implementation is based on [MMPose](https://mmpose.readthedocs.io/en/latest/).
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MMpose requires torch, and the installation process is the following:
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```
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pip install -U openmim
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mim install mmengine
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mim install "mmcv>=2.0.1"
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url = "https://farm7.staticflickr.com/6105/6218847094_20deb6b938_z.jpg"
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result_generator = inferencer([url], pred_out_dir='predictions', vis_out_dir='visualizations')
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results =
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```
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## Video inference
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More details are available in [OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics](https://arxiv.org/abs/2406.09788).
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This particular variant was finetuned on a set of keypoints usually found on Motion Capture setups, and include coco keypoints as well.
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The model predicts the following 52 markers:
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```
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[
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## Installation
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This implementation is based on [MMPose](https://mmpose.readthedocs.io/en/latest/).
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MMpose requires torch, and the installation process is the following:
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```bash
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pip install -U openmim
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mim install mmengine
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mim install "mmcv>=2.0.1"
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url = "https://farm7.staticflickr.com/6105/6218847094_20deb6b938_z.jpg"
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result_generator = inferencer([url], pred_out_dir='predictions', vis_out_dir='visualizations')
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results = next(result_generator)
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```
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## Video inference
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