sfd implementation for face recognition in pytorch. Paper at: SFD: Single Shot Scale-invariant Face Detector

• Python 3.6
• Pytorch 0.4
• TensorBoard(Optional)

• Training on wider faces.
• Inference tools and API.
• Non-maximum suppression at reference.
• TensorBoard supported.
• Evaluation.
• Image augmentation.
• Multi-class detection.

The detector.py is executable and programmable, see inference.ipynb for a quick look at how to use the detector API. Using the following command for directly use it in the command line.

python3 detector.py --image ./image/test.jpg --model ./epoch_41.pth.tar

The trained model epoch_41.pth.tar can be downloaded from Baidu Yun or Google Drive.

The detector will draw bounding boxes and the result is showing bellow

To train with the wider_face dataset, download and extract everything in one directory named wider_face. The file trees should then look like this,

└── wider_face
    ├── Submission_example.zip
    ├── wider_face_split
    │   ├── readme.txt
    │   ├── wider_face_test_filelist.txt
    │   ├── wider_face_test.mat
    │   ├── wider_face_train_bbx_gt.txt
    │   ├── wider_face_train.mat
    │   ├── wider_face_val_bbx_gt.txt
    │   └── wider_face_val.mat
    ├── wider_face_split.zip
    ├── WIDER_test
    │   └── images
    ├── WIDER_test.zip
    ├── WIDER_train
    │   └── images
    ├── WIDER_train.zip
    ├── WIDER_val
    │   └── images
    └── WIDER_val.zip

In the config.py, set the DATASET_DIR to the path of wider_face, and set the LOG_DIR to whatever but a existed directory. Now it's ready to train with the following command,

python3 main.py # there is no stdout

The training log is in LOG_DIR/log.txt, and models will be saved at LOG_DIR/models/epoch_xx.pth. There are many options in config.py(including learning rate or resumption) for you to tweak to get a better model.

If you have TensorBoard installed, set TENSOR_BOARD_ENABLED to True in the config.py, you can use the following command to quickly start the TensorBoard server.

./bin/tensorboard

To visualize how the loss is changing.