ViTPose (simple version w/o mmcv)

An unofficial implementation of ViTPose [Y. Xu et al., 2022]

Usage

| Inference

python inference.py --image-path './examples/img1.jpg'

| Training

python train.py --config-path config.yaml --model-name 'b'

• model_name must be in (b, l, h)

Note

1. Download the trained model (.pth)
   • ViTPose-B-Multi-COCO.pth
   • ViTPose-L-Multi-COCO.pth
   • ViTPose-H-Multi-COCO.pth
2. Set the config. according to the trained model
   • ViTPose-B-COCO-256x192
   • ViTPose-L-COCO-256x192
   • ViTPose-H-COCO-256x192

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Reference

All codes were written with reference to the official ViTPose repo.