emotion2rec

-A project on Personalization and targeted recommendations using computer vision.

Dependencies:

-Install tensorflow gpu on your cmd to install the dependencies

• Python 3.9.12
• dlib
• numpy
• cv2
• Pillow
• os
• Tkinter
• flask
• requests

Procedure

-Clone the repository https://github.com/narulanavya3/Emotion2rec.git

-Run on terminal 'flask run' and leave it running

-On another terminal run the command 'python gui.py'

-click on the option Add new face and type in an id and click on submit. Wait for the camera to click images.

Yow will see the images are being stored in the dataset

-Click on Train face recognition model and wait for the model to train the images in the dataset.

-After training is complete, click on Run application, the camera window will open for about 10 seconds to recognize face and emotions.

After 10 seconds, the dominant emotion will be sent to the flask-server which was running on the terminal flask will process it and return a specific recommendation for a playlist and a new pop window will automatically open pre-loading that playlist designed especially for the user.

Vote of Thanks

-Orriaga/face classification for providing the source to a pre-trained CNN-based emotion model the link for the same is given below (https://github.com/oarriaga/face_classification/blob/master/trained_models/emotion_models/simple_CNN.530-0.65.hdf5)