DeepLearning_Project

Transformer applied in Skeleton-based human action recognition

Getting start

0. download the projet via git:

git clone https://github.com/Annelise2019/DeepLearning_Project.git

1. download the dataset NTU-60
   And then, this command should be used to build the database for training or evaluation:

python tools/ntu_gendata.py --data_path <path to nturgbd+d_skeletons>

2. change the data path in these files

• data_process/skeleton_feeder.py
• config.py

3. change the gpu setting in these files

• config.py

4. run the model using this command:

python classify.py

6. result:

• a folder named "log" will be created to store all the logging traces
• a folder named "checkpoint" will be created to store the model parameters and thus you can retrain your model by changing relative parameters in config.py