Demo visualization code for our PoseFormer paper

• Create a conda environment: conda create -n posedemo python=3.7
• Install pytorch based on your machine. For example:
• pip3 install torch==1.7.1+cu110 torchvision==0.8.2+cu110 -f https://download.pytorch.org/whl/torch_stable.html
• Next, install the required packages:
• pip3 install -r requirements.txt

Download pretrained model for video demo

The pretrained model can be found in here, please download it and put it in the './checkpoint/poseformer_9' directory.

Demo

First, you need to download YOLOv3 and HRNet pretrained models here and put it in the './demo/lib/checkpoint' directory. Then, you need to put your in-the-wild videos in the './demo/video' directory.

Run the command below:

python demo/vis_poseformer.py --video kunkun.mp4

Licence

This project is licensed under the terms of the MIT license.