Awesome

UniHCP: A Unified Model for Human-Centric Perceptions

Usage

Preparation

Install all required dependencies in requirements.txt.
Replace all path...to... in the .yaml configuration files to the absolute path to corresponding dataset locations.
Place MAE pretrained weight <a href="https://dl.fbaipublicfiles.com/mae/pretrain/mae_pretrain_vit_base.pth">mae_pretrain_vit_base.pth</a> under core\models\backbones\pretrain_weights folder.

*Only slurm-based distributed training & single-gpu testing is implemented in this repo.

Experiments

All experiment configurations files and launch scripts are located in experiments/unihcp/release folder.

To perform full multi-task training for UniHCP, replace <your partition> in train.sh launch script and run:

sh train.sh 88 coslr1e3_104k_b4324g88_h256_I2k_1_10_001_2I_fairscale_m256

To perform evaluations, keep the test_info_list assignments corresponding to the tests you want to perform , replace <your partition>, then run :

sh batch_test.sh  1 coslr1e3_104k_b4324g88_h256_I2k_1_10_001_2I_fairscale_m256

Note that in this case, the program would look for checkpoints located at experiments/unihcp/release/checkpoints/coslr1e3_104k_b4324g88_h256_I2k_1_10_001_2I_fairscale_m256

Pretrained Models

Please send the signed <a href="https://drive.google.com/file/d/1O4Z7d5b1w0Vh4T8jvQ1tj_WzX12KWnT9/view?usp=share_link">agreement</a> to mail@yuanzheng.ci to get the download link.