This project contains:

1. Face reconstruct(Face swap) from only a single image.
2. Face pose estimate and keypoints(68) in 3D model.

The origin python code with training is in PRNet.

1. iPhone SE, arm64
2. OpenCV 3.4.0
3. NCNN

1. Mtcnn --> resize to 256x256 --> PRNet --> UV,Z --> Render 86906 triangles in 3D --> SeamlessClone
2. Mtcnn --> resize to 256x256 --> PRNet --> 43867 vertices --> SVD to estimate pose
   Mtcnn --> resize to 256x256 --> PRNet --> 43867 vertices --> pick 68 points for sparse alignment

1. Face Swap, change the target face image(@"ref.jpg") to your own.
2. Face 3D pose estimate and face keypoints in 3D.

There's 4 config files in this project.

1. face_ind.txt

This file is the index of [0,65535], which is the region of the WHITE area of the image[256x256] below.

2. uv_kpt_ind.txt

This file is the index of coordinate(x,y) for 68 keypoints refer to face_ind.txt

3. triangles.txt

86906 triangles' vertices index refer to face_ind.txt

4. canonical_vertices.txt

canonical model for pose estimate, there's coordinate (uv,z) of 43867 vertices

1. About the Euler angles.

http://www.gregslabaugh.net/publications/euler.pdf

2. 3D points transformation matrix.

http://nghiaho.com/?page_id=671

3. Render 3D texture.

http://blackpawn.com/texts/pointinpoly/