This project serves a deep learning model scoring selfie images between 1 to 10 based on image
and face attributes. You can learn the technical details of this project from this blog post. Use [resnet.torch] (https://github.com/erogol/resnet.torch), if you plan to follow all the training pipeline described on the post.
Given image is processed as follows;
Detect face.
Find landmarks
Rotate image to align face.
Fill gaps with constant pixel value.
Send into scoring model.
For an example use check notebook ExampleUse.ipynb
dlib ```sudo pip install dlib``` - face and landmark detection)
lutorpy ```sudo pip install lutorpy``` - using torch model on python
skimage ```sudo pip install skimage``` - image processing
cv2 ```sudo pip install cv2``` - OpenCV python module
What you have here useful
* Face alignment code in ```utils/img_processing.py```.
* A template for porting Torch models to python in ```utils/Classifier.py```.
* The model itself