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Data: RAF-DB
GCN framework: GCNconv
Ref : MRE-CNN
Mediapipe model: face_landmarker Frontend template: free css/html template

How to run

  1. Install data from kaggle and put it in Image_data folder
  2. Install face_landmarker and put it in model folder
  3. Run RunAdjacency.py to get image matrix
  4. Run RunModel.py for the model and Grad-Cam

Finally you get a full folder structure below

path/GCNN
├─.ipynb_checkpoints
├─GradCam
├─Image_data
│  └─DATASET
│      ├─test
│      │  ├─1
│      │  ├─2
│      │  ├─3
│      │  ├─4
│      │  ├─5
│      │  ├─6
│      │  └─7
│      └─train
│          ├─1
│          ├─2
│          ├─3
│          ├─4
│          ├─5
│          ├─6
│          └─7
├─model
├─output_data
│  ├─adjacency
│  │  ├─adjacency_1
│  │  ├─adjacency_2
│  │  ├─adjacency_3
│  │  ├─adjacency_4
│  │  ├─adjacency_5
│  │  ├─adjacency_6
│  │  └─adjacency_7
│  └─landmarks

Note

Install torch with the command below to get a GPU version (if any)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/metal.html

Contributors & Collaborators

尹士文
尹士文
周宇舒
周雨舒
張藝馨
張藝馨
蕭邦宇
蕭邦宇

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