Skip to content

Latest commit

 

History

History
41 lines (21 loc) · 1.63 KB

README.md

File metadata and controls

41 lines (21 loc) · 1.63 KB

RhythmFormer

framework

🔧 Setup

STEP 1: bash setup.sh

STEP 2: conda activate rppg-toolbox

STEP 3: pip install -r ./requirements.txt

The codes are based on rPPG-toolbox

💻 Example of Using Pre-trained Models

Please use config files under ./configs/infer_configs

For example, if you want to run The model trained on UBFC-rPPG and tested on MMPD, use python main.py --config_file ./configs/infer_configs/UBFC-rPPG_MMPD_RHYTHMFORMER.yaml

💻 Examples of Neural Network Training

Please use config files under ./configs/train_configs

Intra-dataset on MMPD With RhythmFormer

STEP 1: Download the MMPD raw data by asking the paper authors

STEP 2: Modify ./configs/train_configs/intra/0MMPD_RHYTHMFORMER.yaml

STEP 3: Run python main.py --config_file ./configs/train_configs/intra/0MMPD_RHYTHMFORMER.yaml

Cross-dataset - Training on PURE and testing on UBFC-rPPG With RhythmFormer

STEP 1: Download the PURE raw data by asking the paper authors.

STEP 2: Download the UBFC-rPPG raw data via link

STEP 3: Modify ./configs/train_configs/cross/PURE_UBFC-rPPG_RHYTHMFORMER.yaml

STEP 4: Run python main.py --config_file ./configs/train_configs/cross/PURE_UBFC-rPPG_RHYTHMFORMER.yaml