Update README.md
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@@ -11,7 +11,7 @@ python datasets/pretreatment_smpl.py --input_path 'Gait3D/3D_SMPLs' --output_pat
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python datasets/Gait3D/merge_two_modality.py --sils_path 'Gait3D-sils-64-64-pkl' --smpls_path 'Gait3D-smpls-pkl' --output_path 'Gait3D-merged-pkl' --link 'hard'
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```
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**Note**: If you use the processed pickle files directly, then the size of silhouette is `64x44`, which means that the pixels on both sides of the horizontal direction can no longer be cut when transforming.
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## Train
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### Baseline model:
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`CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 opengait/main.py --cfgs ./configs/baseline/baseline_Gait3D.yaml --phase train`
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@@ -28,6 +28,16 @@ booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
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year={2022}
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}
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```
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If you think the re-implementation of OpenGait is useful, please cite the following paper:
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```
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@misc{fan2022opengait,
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title={OpenGait: Revisiting Gait Recognition Toward Better Practicality},
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author={Chao Fan and Junhao Liang and Chuanfu Shen and Saihui Hou and Yongzhen Huang and Shiqi Yu},
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year={2022},
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eprint={2211.06597},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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## Acknowledgements
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This dataset was collected by the [Zheng at. al.](https://gait3d.github.io/). The pre-processing instructions are based on (https://github.com/Gait3D/Gait3D-Benchmark).
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This dataset was collected by the [Zheng at. al.](https://gait3d.github.io/). The pre-processing instructions are modified from (https://github.com/Gait3D/Gait3D-Benchmark).
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