makeup

Prerequisites

1. dlib
2. openface
3. flask (optional, for running server)
4. Models:
   dlib_face_recognition_resnet_model_v1.dat (for dlib usage)
   shape_predictor_68_face_landmarks.dat (for openface usage)
   and put those 2 in ./models/dlib/

To train:

1. Delete ./data/generated-embeddings and ./data/aligned-images
2. Run these commands from terminal: ./util/align-dlib.py ./data/training-images/ align outerEyesAndNose ./data/aligned-images/ --size 96 ./batch-represent/main.lua -outDir ./data/generated-embeddings/ -data ./data/aligned-images/ ./demos/classifier.py train ./data/generated-embeddings/

Test with your data

./demos/classifier.py infer ./data/generated-embeddings/classifier.pkl ./data/shane.jpg

Run test from server

To run test from server, you must have flask installed, and run from virtualenv.    
Activate server: python server.py        
Your server will run at http://127.0.0.0:5000  
Go to http://127.0.0.1:5000/detect_face_shape/shane/ to test or http://127.0.0.1:5000/detect_face_shape/<image_name>/
whereas ./data/<image_name>.jpg is your test image to classify