OpenCV-SWIG

A SWIG library for OpenCV types

This library is a collection of SWIG interface files with rules to wrap OpenCV C++ types as Python classes. The OpenCV itself has a Python binding exposing its API, this library is not that.

Hello, world!

The use case for this library is when someone writing a C++ library, which uses OpenCV types on its public API, wants create a Python binding to that library.

Let's suppose you have built a C++ library named MyLib having a my_lib.hpp header:

#ifndef MY_LIB_HPP_INCLUDED
#define MY_LIB_HPP_INCLUDED

#include <opencv2/core.hpp>
#include <iostream>

inline auto moveTo(cv::Point const& p) -> void
{
    std::cout << "cv::Point moved" << std::endl;
}

inline auto getImage() -> cv::Mat3b
{
    return cv::Mat3b(3, 5);
}

#endif /* MY_LIB_HPP_INCLUDED */

To generate a MyLib Python binding all you need is a my_lib.i SWIG file as:

%module my_lib

%include <opencv.i>
%cv_instantiate_all_defaults

%{
    #include "my_lib.hpp"
%}

%include "my_lib.hpp"

and a CMakeLists.txt:

cmake_minimum_required(VERSION 3.0)

cmake_policy(SET CMP0074 NEW)
cmake_policy(SET CMP0078 NEW)
cmake_policy(SET CMP0086 NEW)

project(MyLib)

find_package(OpenCV-SWIG REQUIRED)
find_package(SWIG REQUIRED COMPONENTS python)
find_package(Boost REQUIRED)
find_package(OpenCV REQUIRED core)
find_package(Python REQUIRED COMPONENTS Interpreter Development)

include(UseSWIG)

set_property(SOURCE my_lib.i PROPERTY CPLUSPLUS ON)
swig_add_library(my_lib LANGUAGE python SOURCES my_lib.i my_lib.hpp)
set_property(
  TARGET my_lib
  PROPERTY SWIG_INCLUDE_DIRECTORIES
    ${OpenCV-SWIG_INCLUDE_DIRS}
    ${OpenCV_INCLUDE_DIRS}
)

target_include_directories(my_lib
  PRIVATE
    ${CMAKE_CURRENT_SOURCE_DIR}
    ${Python_INCLUDE_DIRS}
    ${OpenCV_INCLUDE_DIRS}
    ${Boost_INCLUDE_DIRS}
)

target_link_libraries(my_lib
  ${OpenCV_LIBRARIES}
)

After calling:

mkdir build
cd build
cmake .. -DOpenCV-SWIG_ROOT=</path/to/OpenCV-SWIG/install/dir/if/not/on/system/dir>
make

A Python module my_lib.py will be created on the current directory, and the code below should work just fine:

import my_lib
import numpy as np
import cv2

p0 = my_lib.Point(13, 17)
my_lib.moveTo(p0)

cv_img = my_lib.getImage()
np_arr = cv2.blur(np.asarray(cv_img), (3, 3))

cv_img2 = my_lib.Mat3b.from_array(np_arr)

Install

To install, execute on the package root dir:

mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX=</path/to/install/dir>
make install

Nix

If using Nix, any Git commit can be used as buildInputs with:

opencv-swig = pkgs.callPackage (
  fetchTarball https://github.com/renatoGarcia/opencv-swig/archive/<git-commit-hash>.tar.gz
) {};

To built the Hello, World! example, a shell.nix as below will set a correct environment:

let
  pkgs = import <nixpkgs> {};
  opencv-swig = pkgs.callPackage (
    fetchTarball https://github.com/renatoGarcia/opencv-swig/archive/v1.0.1.tar.gz
  ) {};

in pkgs.mkShell {
  buildInputs = [
    opencv-swig
    pkgs.boost
    pkgs.swig
    pkgs.cmake
    pkgs.pythonPackages.opencv
  ];
}

Supported OpenCV versions

This library is known to work with all versions of OpenCV since 2.4.11. Before that no tests were performed.

Currently all new commits are tested against OpenCV versions 3.3, 3.4, 4.0, 4.1, 4.2 and 4.3. Any new release beyond that range is expected to work, and new tests will be added when due, but no guarantee can be done beforehand.

When used with an OpenCV version outside of that range, a warning like "Warning 972: Using an untested OpenCV version" will be emitted. To silent it call SWIG with the flag -w972.