The task in this project is to match a face image without any occlusion with a face image covered with one of these masking approaches. This repo is a solution of summer challenge given by IITJ.

1. Clone this repository

git clone https://github.com/Garvit-32/Face-recognition-in-presence-of-Mask.git

2. Install all the dependencies

pip install -r requirements.txt

3. Download and paste the pretrained weight of face detection model in ./face_detection/weights/ using the link
4. Download the hand made dataset using the link ~ 110 MB
5. Extract and paste it in project root directory
6. (optional) You can use your dataset also but it follow a specific structure of directory

-dataset/
	-person_name_1/
		-image_01
		-image_02
	-person_name_2/
		-image_01
		-image_02

7. Run generate_database python file to virtually append mask on person face in database

python generate_database.py

8. Train the model

python train.py

1. Extract face in image using extract_face.py edit test_data_path = "to_your_test_path"

python extract_face.py

2. Test your image

python test.py