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.

Installation

pip install PyPatchMatch

Wheels for Linux, macOS and Windows ship the compiled library including the required OpenCV runtime, so no compiler or OpenCV installation is needed. On other platforms pip builds from the source distribution, which requires a C++17 compiler, CMake and the OpenCV development files (e.g. apt install libopencv-dev or brew install opencv).

Usage

Python (see examples/py_example.py):

import patchmatch

image = ...  # HxWx3 uint8 numpy array or PIL image
mask = ...  # HxW uint8 or bool numpy array or PIL image, non-zero marks the holes
result = patchmatch.inpaint(image, mask, patch_size=3)

The mask must have the same height and width as the image. If mask is omitted, all pure white pixels are treated as holes. patchmatch.patchmatch_available tells whether the native library could be loaded. The previous import path from patchmatch import patch_match keeps working.

C++ (see examples/cpp_example.cpp, build and run it with examples/cpp_example_run.sh):

#include "inpaint.h"

int main() {
    cv::Mat image = ...;
    cv::Mat mask = ...;

    auto metric = PatchSSDDistanceMetric(5);
    cv::Mat result = Inpainting(image, mask, &metric).run();
}

The library is built with CMake; PATCHMATCH_BUILD_EXAMPLES builds the example and PATCHMATCH_WITH_HIGHGUI enables the debug visualization of Inpainting::run.

Development

The project is managed with uv:

uv sync                        # create .venv, build the library, install dev deps
uv run pre-commit install      # enable ruff and the other hooks on commit
uv run pytest                  # run the test suite
uv run pytest -m "not e2e"     # only the fast unit tests

Releases are published to PyPI by creating a GitHub release; the version is taken from its tag (e.g. v1.1.0).

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