Hope this helps & you enjoy it. ^_^

# Since triangle mesh is the most popular representation of 3D face, 
# the main part is mesh processing.
mesh/             # written in python(numpy)
|  io.py                 # read & write obj
|  vis.py                # plot mesh
|  transform.py          # transform mesh & estimate matrix
|  light.py              # add light & estimate light(to do)
|  render.py             # obj to image using rasterization render

# When can not use vercorization to optimize, loops in python are too slow to use. 
# So write core parts(loops) in c++, then use cython to compile them for python api.
mesh_cython/      # written in c++(cython)
|  render.py             # the same API as in mesh/render.py, with faster speed.
|  light.py              # the same API as in mesh/light.py, with faster speed.
|  mesh_core*            # c++ codes of core parts.

# 3DMM is one of the most popular methods to generate & reconstruct 3d face.
morphabel_model/  # witten in python(numpy)
|  morphable_model.py    # morphable model class: generate & fit
|  fit.py                # estimate shape&expression parameters. 3dmm fitting.
|  load.py               # load 3dmm data

cd ./examples

• 3dmm. python 2_3dmm.py

  left: random example generated by 3dmm

  right: fitting face with 3dmm using 68 key points

  

• transform. python 3_transform.py
  left:

  fix camera position & use orthographic projection. (often used in reconstruction)

  then transform face object: scale, change pitch angle, change yaw angle, change roll angle

  right:

  fix obj position & use perspective projection(fovy=30). (simulating real views)

  then move camera position and rotate camera: from far to near, down & up, left & right, rotate camera

  

• light. python 4_light.py

  single point light: from left to right, from up to down, from near to far

  

• image map python 6_image_map.py

  render different attributes in image pixels.

  : depth, pncc, uv coordinates

  

• uv map python 7_uv_map.py

  render different attributes in uv coordinates.

  : colors(texture map), position(2d facial image & corresponding position map)

  

• Python 2 or Python 3

• Python packages:

  • numpy
  • skimage (for reading&writing image)
  • scipy (for loading mat)
  • matplotlib (for show)
  • Cython (for compiling c++ file)

1. Clone the repository

   git clone https://github.com/YadiraF/face3d
   cd face3d

2. Compile c++ files to .so for python use (ignore if you use numpy version)

   cd face3d/mesh_cython
   python setup.py build_ext -i 

3. Prepare BFM Data (ignore if you don't use 3dmm)

   see Data/BFM/readme.md

4. Run examples

   (examples use cython version, you can change mesh_cython into mesh to use numpy version)

   cd examples
   python 1_pipeline.py