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LIU-YUXI / Adaptive-Multi-occlusion-Face-Recognition

Adaptive multi-occlusion face recognition model based on CLIP, based on FaceX-Zoo framework.
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Introdcution

Adaptive multi-occlusion face recognition (including face with mask, glasses and hat) model based on CLIP(openai/CLIP: CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image (github.com)), based on FaceX-Zoo(JDAI-CV/FaceX-Zoo: A PyTorch Toolbox for Face Recognition (github.com)) framework.

Requirements

See the detail requirements in requirements.txt

Model Training

run ./train.sh with the train dataset CASIA-Webface (baidu Pan Link)

Model Test

run ./test_lfw_adapt.sh with the test dataset LFW-MASK (baidu Pan Link), or the dataset MEGLSS(baidu Pan Link), CALFW-SUNGLASSES(baidu Pan Link), CPLFW(baidu Pan Link)

Simulate occlusion generation

You can generate a new simulated occluded dataset by running the python file mask_data_generation.py and changing the dataset path and occlusion image in the file.