Recognizes the facial emotion and overlays emoji, equivalent to the emotion, on the persons face.

There are 4 steps :

• STEP 1 - generating the facial images

  1. cd </to/repo/root/dir>
  2. run python3 src/face_capture.py --emotion_name <emotion-name> --number_of_images <number>
     -- example: python3 src/face_capture.py --emotion_name smile --number_of_images 200

  This will open the cam and all you need to do is give the smile emotion from your face.

  • NOTE: You must change /emotion_map.json if you want another set emotions than what is already defined.
  • Do this step for all the different emotions in different lighting conditions.
  • For the above result, I used 300 images for each emotions captured in 3 different light condition (100 each).
  • You can see your images inside the 'images' folder which will contain different folder for different emotion images.

• STEP 2 - creating the dataset out of it

  1. run python3 src/dataset_creator.py
  • This will create the ready-to-use dataset as a python pickled file and will save it in the dataset folder.

• STEP 3 - training the model on the dataset and saving it

  1. run python3 src/trainer.py
  • This will start the model-training and upon the training it will save the tensorflow model in the 'model-checkpoints' folder.
  • It has the parameters that worked well for me, feel free to change it and explore.

• STEP 4 - using the trained model to make prediction

  1. run python3 src/predictor.py
  • this will open the cam, and start taking the video feed -- NOW YOU HAVE DONE IT ALL. 👏

Its time to show your emotions ❤️