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PatchMatch based Inpainting | |
===================================== | |
This library implements the PatchMatch based inpainting algorithm. It provides both C++ and Python interfaces. | |
This implementation is heavily based on the implementation by Younesse ANDAM: | |
(younesse-cv/PatchMatch)[https://github.com/younesse-cv/PatchMatch], with some bugs fix. | |
Usage | |
------------------------------------- | |
You need to first install OpenCV to compile the C++ libraries. Then, run `make` to compile the | |
shared library `libpatchmatch.so`. | |
For Python users (example available at `examples/py_example.py`) | |
```python | |
import patch_match | |
image = ... # either a numpy ndarray or a PIL Image object. | |
mask = ... # either a numpy ndarray or a PIL Image object. | |
result = patch_match.inpaint(image, mask, patch_size=5) | |
``` | |
For C++ users (examples available at `examples/cpp_example.cpp`) | |
```cpp | |
#include "inpaint.h" | |
int main() { | |
cv::Mat image = ... | |
cv::Mat mask = ... | |
cv::Mat result = Inpainting(image, mask, 5).run(); | |
return 0; | |
} | |
``` | |
README and COPYRIGHT by Younesse ANDAM | |
------------------------------------- | |
@Author: Younesse ANDAM | |
@Contact: younesse.andam@gmail.com | |
Description: This project is a personal implementation of an algorithm called PATCHMATCH that restores missing areas in an image. | |
The algorithm is presented in the following paper | |
PatchMatch A Randomized Correspondence Algorithm | |
for Structural Image Editing | |
by C.Barnes,E.Shechtman,A.Finkelstein and Dan B.Goldman | |
ACM Transactions on Graphics (Proc. SIGGRAPH), vol.28, aug-2009 | |
For more information please refer to | |
http://www.cs.princeton.edu/gfx/pubs/Barnes_2009_PAR/index.php | |
Copyright (c) 2010-2011 | |
Requirements | |
------------------------------------- | |
To run the project you need to install Opencv library and link it to your project. | |
Opencv can be download it here | |
http://opencv.org/downloads.html | |