Zzier
609aa0e9aa
* Update ParsingGait * Clear up the confusion Clear up the confusion about gait3d and gait3d-parsing. * Update 0.get_started.md * Add BaseParsingCuttingTransform * Update gcn.py * Create gaitbase_gait3d_parsing_btz32x2_fixed.yaml * Add gait3d_parsing config file * Update 1.model_zoo.md Update Gait3D-Parsing checkpoints * Update 1.model_zoo.md add configuration * Update 1.model_zoo.md center text --------- Co-authored-by: Junhao Liang <43094337+darkliang@users.noreply.github.com>
44 lines
2.3 KiB
Markdown
44 lines
2.3 KiB
Markdown
# Gait3D
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This is the pre-processing instructions for the Gait3D dataset. The original dataset can be found [here](https://gait3d.github.io/). The original dataset is not publicly available. You need to request access to the dataset in order to download it. This README explains how to extract the original dataset and convert it to a format suitable for OpenGait.
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## Data Preparation
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https://github.com/Gait3D/Gait3D-Benchmark#data-preparation
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## Data Pretreatment
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```python
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python datasets/pretreatment.py --input_path 'Gait3D/2D_Silhouettes' --output_path 'Gait3D-sils-64-64-pkl'
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python datasets/Gait3D/pretreatment_smpl.py --input_path 'Gait3D/3D_SMPLs' --output_path 'Gait3D-smpls-pkl'
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(optional) python datasets/pretreatment.py --input_path 'Gait3D/2D_Silhouettes' --img_size 128 --output_path 'Gait3D-sils-128-128-pkl'
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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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## 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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### SMPLGait 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/smplgait/smplgait.yaml --phase train`
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## Citation
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If you use this dataset in your research, please cite the following paper:
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```
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@inproceedings{zheng2022gait3d,
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title={Gait Recognition in the Wild with Dense 3D Representations and A Benchmark},
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author={Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei},
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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 modified from (https://github.com/Gait3D/Gait3D-Benchmark).
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