# Clone the repository
git clone https://github.com/duclvQ/improved_DDNet.git
# Navigate to the project directory
cd improved_DDNet
pip -r install requirements.txt
./data/COBOT/train.pickle
./data/COBOT/test.pickle
./pose_new_v2
python train.py --run_name {run name} # find the list of "run_name" in "models/DDNet_Original.py"
find pretrained weights at this 'link'.
Visit 'online.py' then set the value of 'exp' corresponding to run_name in the previous step, this action will return a folder of numpy files for all videos in test list.
After the prediction step, the frame-wise Acc is measured in 'online_local.ipynb', remember to read and set carefully every variable in these 2 files when you run.
draw_cfm.ipynb and visualize.ipynb also contain helpful functions.