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Update README.md

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@@ -13,7 +13,7 @@ SynthPose is a new approach that enables finetuning of pre-trained 2D human pose
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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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  [
@@ -78,7 +78,7 @@ Where the first 17 keypoints are the COCO keypoints, and the next 35 are anatomi
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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"
@@ -102,7 +102,7 @@ inferencer = MMPoseInferencer(
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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 = [result for result in result_generator]
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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