Face-Feature-Extraction
This is a CNN which takes in 96*96 images from kaggle-dataset and predictes 15 landmark points:
- [left_eye_center_x]
- [left_eye_center_y]
- [right_eye_center_x]
- [right_eye_center_y]
- [left_eye_inner_corner_x]
- [left_eye_inner_corner_y]
- [left_eye_outer_corner_x]
- [left_eye_outer_corner_y]
- [right_eye_inner_corner_x]
- [right_eye_inner_corner_y]
- [right_eye_outer_corner_x]
- [right_eye_outer_corner_y]
- [left_eyebrow_inner_end_x]
- [left_eyebrow_inner_end_y]
- [left_eyebrow_outer_end_x]
- [left_eyebrow_outer_end_y]
- [right_eyebrow_inner_end_x]
- [right_eyebrow_inner_end_y]
- [right_eyebrow_outer_end_x]
- [right_eyebrow_outer_end_y]
- [nose_tip_x]
- [nose_tip_y]
- [mouth_left_corner_x]
- [mouth_left_corner_y]
- [mouth_right_corner_x]
- [mouth_right_corner_y]
- [mouth_center_top_lip_x]
- [mouth_center_top_lip_y]
- [mouth_center_bottom_lip_x]
- [mouth_center_bottom_lip_y]
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
Prerequisites
Libraries needed
numpy
keras
tensorflow
cv2
matplotlib
pickle
h5py
string
os
Running the tests
You can download the dataset from Kaggle website(https://www.kaggle.com/c/facial-keypoints-detection)
Run Feature_Extraction-Keras.ipynb
Model
The following model has been inspired from the research paper by Namish(https://arxiv.org/pdf/1710.00977.pdf)
Results
The Model gets an acc of 0.95 on training set and 0.79 on cv set
