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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: [email protected]
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
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