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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)

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;
}

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

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