Expression Snippet Transformer for Robust Video-based Facial Expression Recognition

Pytorch implementation of paper:

Expression Snippet Transformer for Robust Video-based Facial Expression Recognition

Content

• Dependencies
• Code and Data Preparation
• Training
• Testing

Dependencies

Python Version: 3.7.9

Required packages are listed in requirements.txt. You can install them by running:

pip install -r requirements.txt

Code and Data Preparation

1. Download the code from this repository and download the pre-trained ResNet-18 from Baidu Drive (1req)

2. Prepare the dataset.

   You need to unified the input video length to 105 frames. Make sure the data structure is as below.

   ├── DFEW
   └── videos
      └── 14400
          ├── 000.jpg
          ├── 001.jpg
          ├── 002.jpg
          ├── ...
      └── 14401
          ├── 000.jpg
          ├── 001.jpg
          ├── 002.jpg
          ├── ...
    └── data_list
       ├── Train_DFEW_all_clip.txt
       ├── Train_DFEW_all_clip_set_2.txt
       ├── Train_DFEW_all_clip_set_3.txt
       ├── Train_DFEW_all_clip_set_4.txt
       ├── Train_DFEW_all_clip_set_5.txt
   

Training

You can use the following command to train:

python main.py --train_video_root /data/Your_Path/data_path/DFEW/videos --train_list_root /data/Your_Path/data_path/DFEW/data_list/Train_DFEW_all_clip_set_2.txt --test_video_root /data/Your_Path/data_path/DFEW/videos --test_list_root /data/Your_Path/data_path/DFEW/data_list/Test_DFEW_all_clip_set_2.txt --dataset_name DFEW --name dfew_transformer --gpu_ids 3 --batch 8 --epochs_count 160

Testing

You can evaluate a trained model by running:

python main.py --train_video_root /data/Your_Path/data_path/DFEW/videos --train_list_root /data/Your_Path/data_path/DFEW/data_list/Train_DFEW_all_clip_set_1.txt --test_video_root /data/Your_Path/data_path/DFEW/videos --test_list_root /data/Your_Path/data_path/DFEW/data_list/Test_DFEW_all_clip_set_1.txt --dataset_name DFEW --name dfew_transformer --gpu_ids 3 --batch 8 --phase test --eval_model_path MODEL_PATH

Here, MODEL_PATH denotes for the path of the trained model.

You can download our trained model on DFEW from Baidu Drive (owu2)

IF YOU HAVE ANY PROBLEM, PLEASE CONTACT [email protected] OR COMMIT ISSUES