Project: face_landmark_dnn (GitHub Link)

facial-landmark-dnn

Facial landmark detection using Convolutional Neural Networks for Mobile Device

[ Requirements ]

tensorflow==1.5.0
Keras==2.1.3
coremltools==0.8

[ Data Preprocessing ]

Raw-Data
1. 300W
2. 300VW
3. Ibug
4. Our own Korean face dataset

Dataset in Google Drive: Image Dataset Landmarks Dataset

# Example: Load Dataset
X = np.load(PATH + "basic_dataset_img.npz")
y = np.load(PATH + "basic_dataset_pts.npz")
X = X['arr_0']
y = y['arr_0'].reshape(-1, 136)

[ Modeling ]

[ Result ]

Face detector: opencv ssd detector
Facial Landmark detector: Mobilenet based model

Youtube Video 1 Youtube Video 2

[ Converter for Mobile ]

IOS - Keras to CoreML
Android (TODO)
1. Import model in Tensorflow
  - Convert Keras to Tensorflow use this code
  - Build Android app and call tensflow. check this tutorial and this official demo from google to learn how to do it.
2. Import model in Java
  - deeplearning4j a java library allow to import keras model: tutorial link
  - Use deeplearning4j in Android: it is easy since you are in java world. check this tutorial

[ Reference ]