The EAP Toolkit is a set of image smoothing tools developed by the Team of Style2Paints (ToS2P), aimed at finding a solution to decompose texture or illumination from images.
The uniqueness of EAP is that it dynamically finds a set of "erasing" positions to help better pattern decompostion. Please refer to our Project Page for more details.
The codes are written in Matlab. I have spent one and a half months to convert those codes to python but finally failed. It is impossible to implement these tools in python. This is mainly because the sparse optimization in python is very weak.
Input files:
./code/matlab/tv/input.png
Output files:
./code/matlab/tv/output.png
Command:
matlab ./code/matlab/tv/run.m
Input files:
./code/matlab/tv_EAP_human/input.png
./code/matlab/tv_EAP_human/mask.png
Output files:
./code/matlab/tv_EAP_human/output.png
Command:
matlab ./code/matlab/tv_EAP_human/run.m
Input files:
./code/matlab/tv_EAP_auto/input.png
Output files:
./code/matlab/tv_EAP_auto/output.png
./code/matlab/tv_EAP_auto/mask.png
Command:
matlab ./code/matlab/tv_EAP_auto/run.m
Input files:
./code/matlab/rtv/input.png
Output files:
./code/matlab/rtv/output.png
Command:
matlab ./code/matlab/rtv/run.m
Input files:
./code/matlab/rtv_EAP_human/input.png
./code/matlab/rtv_EAP_human/mask.png
Output files:
./code/matlab/rtv_EAP_human/output.png
Command:
matlab ./code/matlab/rtv_EAP_human/run.m
Input files:
./code/matlab/rtv_EAP_auto/input.png
Output files:
./code/matlab/rtv_EAP_auto/output.png
./code/matlab/rtv_EAP_auto/mask.png
Command:
matlab ./code/matlab/rtv_EAP_auto/run.m
Input files:
./code/matlab/l0/input.png
Output files:
./code/matlab/l0/output.png
Command:
matlab ./code/matlab/l0/run.m
Input files:
./code/matlab/l0_EAP_human/input.png
./code/matlab/l0_EAP_human/mask.png
Output files:
./code/matlab/l0_EAP_human/output.png
Command:
matlab ./code/matlab/l0_EAP_human/run.m
Input files:
./code/matlab/l0_EAP_auto/input.png
Output files:
./code/matlab/l0_EAP_auto/output.png
./code/matlab/l0_EAP_auto/mask.png
Command:
matlab ./code/matlab/l0_EAP_auto/run.m
Input files:
./code/matlab/L1/input.png
Output files:
./code/matlab/L1/output.png
Command:
matlab ./code/matlab/L1/run.m
Input files:
./code/matlab/L1_EAP_human/input.png
./code/matlab/L1_EAP_human/mask.png
Output files:
./code/matlab/L1_EAP_human/output.png
Command:
matlab ./code/matlab/L1_EAP_human/run.m
Input files:
./code/matlab/L1_EAP_auto/input.png
Output files:
./code/matlab/L1_EAP_auto/output.png
./code/matlab/L1_EAP_auto/mask.png
Command:
matlab ./code/matlab/L1_EAP_auto/run.m
Our applications are from many third-party projects. Please refer to their original sites for more details.
Illumination decomposition for material recoloring with consistent interreflections
http://graphics.berkeley.edu/papers/Carroll-IDM-2011-08/index.html
Structure Extraction from Texture via Relative Total Variation
http://www.cse.cuhk.edu.hk/~leojia/projects/texturesep/
Decomposing Images into Layers via RGB-space Geometry
https://cragl.cs.gmu.edu/singleimage/
If you use this code for your research, please cite our paper:
@InProceedings{EAP2020,
author={Lvmin Zhang and Chengze Li and Yi JI and Chunping Liu and Tien-tsin Wong},
booktitle={European Conference on Computer Vision (ECCV)},
title={Erasing Appearance Preservation in Optimization-based Smoothing},
year={2020},
}
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