faceSearch

A face searching AI application using face detection and face embedding

The algorithms works as follows:

1. Detect face bounding boxes from input images
2. Crop detected face region and compute 128 dimension face embeddings.
3. Train a HNSW model for approximate KNN neighbours

For searching similar faces from the database use the model in step 3 to find the approximate nearest neighbours.

Training a face searcher

python3 run_face_search.py train_face_searcher --image_database_dir=<directory containing training images (jpg/png)>

you can modify/optimize the the parameters in config.yaml for trianing the model and paths for saving the model.

Searching similar faces from the database

python3 run_face_search.py search_similar_faces --input_image_file=<path to input image file> --number_of_images=<number of images to be retrieved from the database>--model_dir=<path to trained model directory> --image_database_dir=<directory containing training/database images (jpg/png)>

An example of searching using celebrity database

first row is the query/input image and rest of the rows are retrieved similar faces images

Dependencies

hnswlib
opencv-python
loguru
yaml
fire