Script is tested on Python 3.6.1. To install required libraries run:
pip install -r requirements.txt
Data is expected to be a set of face photos and CSV file where each row represents coordinates (xi, yi) of facial keypoints for image filename:
| filename | x0 | y0 | x1 | y1 | ... | x13 | y13 |
|---|
Coordinates are indexed according to the following scheme:
You can use weights from 500 epochs training saved in weights/conv5_adam_epochs500.hdf5.
MSE error on images resized to (100, 100) shape is 5.2569.
$ python app.py augment --help
Usage: app.py augment [OPTIONS] img coords dest
Augments images stored in IMG folder with coordinates from COORDS csv file
and saves result in grayscale to DEST folder
$ python app.py train --help
Usage: app.py train [OPTIONS] img coords model
Trains model on images from IMG folder with coordinates from COORDS csv
file and saves trained model in hdf5 file MODEL
$ python app.py predict --help
Usage: app.py predict [OPTIONS] img model coords
Predicts facial keypoints coordinates for images from IMG folder using
model from file MODEL and saves results in csv file COORDS
These are some examples detected using pretrained weights:
