(1)Clone the project
git clone https://github.com/HRNet/HRNet-Facial-Landmark-Detection.git
(2)Install dependencies
pip3 install -r requirements.txt
(3) download pre-trained model and test
python3 camera.py--cfg <CONFIG-FILE> --model-file <MODEL WEIGHT>
# example:
python3 camera.py --cfg experiments/face_landmark_detection_wflw_shufflenet_large.yaml --model-file pretrained/shufflenet_plus.pth
-
Download the annotations files from: Google Drive: https://drive.google.com/file/d/1W8p0MWmUtWxH1B2LsImtg3JVO-o5AU9u/view?usp=sharing
Baiduyu Link: https://pan.baidu.com/s/10l70jaoWf5ls4t6HMoFk1w Access Code: 6ipb
-
Download images (WFLW) from official websites and then put them into
images
folder for each dataset.
Your data
directory should look like this:
.
└──data
└── wflw
├── face_landmarks_wflw_test_blur.csv
├── face_landmarks_wflw_test.csv
├── face_landmarks_wflw_test_expression.csv
├── face_landmarks_wflw_test_illumination.csv
├── face_landmarks_wflw_test_largepose.csv
├── face_landmarks_wflw_test_makeup.csv
├── face_landmarks_wflw_test_occlusion.csv
├── face_landmarks_wflw_train.csv
└── images
2 directories, 8 files
python train.py --cfg <CONFIG-FILE>
# example:
python3 train.py --cfg experiments/face_alignment_wflw_hrnet_w18.yaml
NME | model_size | test | pose | illumination | occlution | blur | makeup | expression |
---|---|---|---|---|---|---|---|---|
shufflenet_plus | 13.8M | 4.79 | 8.56 | 4.73 | 5.80 | 5.47 | 4.77 | 5.15 |
HRNet | 39.2M | 4.60 | 7.86 | 4.57 | 5.42 | 5.36 | 4.26 | 4.78 |
.
├── data
│ └── wflw
│ ├── face_landmarks_wflw_test_blur.csv
│ ├── ...
│ ├── face_landmarks_wflw_train.csv
│ └── images
├── experiments
│ └── face_landmark_detection_wflw_shufflenet_large.yaml
├── output
│ ├── log
│ │ └── WFLW
│ └── WFLW
│ └── face_landmark_detection_wflw_shufflenet_large
├── README.md
├── requirements.txt
├── src
│ ├── datasets.py
│ ├── __init__.py
│ ├── loss.py
│ ├── models
│ │ ├── hrnet.py
│ │ ├── __init__.py
│ │ ├── shufflenet_bak.py
│ │ ├── shufflenet.py
│ │ └── utils.py
│ ├── transforms.py
│ └── utils.py
├── test.py
└── train.py
13 directories, 28 files
- face pose weighted
- heatmap
- graph network
- model、dataset、loss
- deployment
- video stable
https://github.com/HRNet/HRNet-Facial-Landmark-Detection