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.
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
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
)
#include "inpaint.h"
int main() {
cv::Mat image = ...
cv::Mat mask = ...
cv::Mat result = Inpainting(image, mask, 5).run();
return 0;
}
@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
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