├── result.jpg
├── .gitmodules
└── README.md


/result.jpg:
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https://raw.githubusercontent.com/zengxianyu/facepf/HEAD/result.jpg


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/.gitmodules:
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1 | [submodule "photometric_optimization"]
2 | 	path = photometric_optimization
3 | 	url = https://github.com/zengxianyu/photometric_optimization
4 | 	branch = master
5 | 


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/README.md:
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 1 | # facepf
 2 | A python implementation of the face profiling described in the 3DDFA paper. 
 3 | The older version of this implementation can be found in the branch ``face3d". 
 4 | Then I migrate everything to FLAME[2] face model as I found it's easy to obtain and their code to fit 2d landmarks performs well. 
 5 | 
 6 | ## Usage
 7 | 1. Install required envs the same as in [2] or following [there](https://github.com/zengxianyu/photometric_optimization)
 8 | 2. add [my folk of [2]](https://github.com/zengxianyu/photometric_optimization) as a submodule
 9 | ```
10 | git clone https://github.com/zengxianyu/facepf.git
11 | cd facepf
12 | git submodule init
13 | git submodule update
14 | ```
15 | 3. run the script (you may change the angles in line 81 to get the result after rotation of desired angles)
16 | ```
17 | cd photometric_optimization
18 | python image_renderer.py
19 | ```
20 | 
21 | ## How to get the npy file
22 | Following [there](https://github.com/zengxianyu/photometric_optimization)
23 | 
24 | ## Result
25 | Input image and output after inplane rotation:
26 | 
27 | ![](https://raw.githubusercontent.com/zengxianyu/facepf/master/result.jpg)
28 | 
29 | ## Reference
30 | [1] 3DDFA. https://github.com/cleardusk/3DDFA/issues/182
31 | 
32 | [2] FLAME photometric optimization. https://github.com/HavenFeng/photometric_optimization
33 | 


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