This library implements the PatchMatch based inpainting algorithm.
Project description
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, with some bug fixes, and updates.
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
)
import patch_match
if patch_match.patchmatch_available:
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=3)
For C++ users (examples available at examples/cpp_example.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
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