OpenCV 3.2.0 Features2D + Homography to find a known object

Readme.md

Description

Features2D + Homography to find a known object http://docs.opencv.org/3.2.0/d9/d97/tutorial_table_of_content_features2d.html ported to OpenCV 3.2.0

Setup

1. git clone -b 3.2.0 --depth 1 --recursive https://github.com/opencv/opencv_contrib.git
2. git clone -b 3.2.0 --depth 1 --recursive https://github.com/opencv/opencv.git
3. Create bat script (Windows):

@echo off
REM git clone -b 3.2.0 --depth 1 --recursive https://github.com/opencv/opencv_contrib.git
REM OR Download https://github.com/opencv/opencv_contrib/archive/3.2.0.zip
REM 
REM git clone -b 3.2.0 --depth 1 --recursive https://github.com/opencv/opencv.git
REM OR Download https://github.com/opencv/opencv/archive/3.2.0.zip

REM # Create build directory
call cmake -E make_directory "build"

REM # Create build generator files
call cmake -E chdir "build" cmake -E time cmake --clean "D:\OpenCV\opencv-3\opencv" -G "Visual Studio 14 2015" -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=OFF -DOPENCV_EXTRA_MODULES_PATH="D:\OpenCV\opencv-3\opencv_contrib\modules" -DWITH_CUDA=OFF

REM # Build project
call cmake -E chdir "build" cmake -E time cmake --build . --config Release

You can change -DWITH_CUDA=OFF to -DWITH_CUDA=ON You can change path "D:\OpenCV\opencv-3\opencv" to yours You can change path "D:\OpenCV\opencv-3\opencv_contrib\modules" to yours (note "modules" in path)

Create VS 2015 project

Include dirs:

D:\OpenCV\opencv-3\opencv\modules\videostab\include;
D:\OpenCV\opencv-3\opencv\modules\superres\include;
D:\OpenCV\opencv-3\opencv\modules\stitching\include;
D:\OpenCV\opencv-3\opencv\modules\videoio\include;
D:\OpenCV\opencv-3\opencv\modules\shape\include;
D:\OpenCV\opencv-3\opencv\modules\video\include;
D:\OpenCV\opencv-3\opencv\modules\photo\include;
D:\OpenCV\opencv-3\opencv\modules\objdetect\include;
D:\OpenCV\opencv-3\opencv\modules\ml\include;
D:\OpenCV\opencv-3\opencv\modules\imgproc\include;
D:\OpenCV\opencv-3\opencv\modules\imgcodecs\include;
D:\OpenCV\opencv-3\opencv\modules\highgui\include;
D:\OpenCV\opencv-3\opencv\modules\flann\include;
D:\OpenCV\opencv-3\opencv\modules\cudev\include;
D:\OpenCV\opencv-3\opencv\modules\features2d\include;
D:\OpenCV\opencv-3\opencv\modules\cudafilters\include;
D:\OpenCV\opencv-3\opencv\modules\cudafeatures2d\include;
D:\OpenCV\opencv-3\opencv\modules\cudacodec\include;
D:\OpenCV\opencv-3\opencv\modules\cudabgsegm\include;
D:\OpenCV\opencv-3\opencv\modules\cudaarithm\include;
D:\OpenCV\opencv-3\opencv\modules\calib3d\include;
D:\OpenCV\opencv-3\opencv\modules\core\include;
D:\OpenCV\opencv-3\opencv_contrib\modules\xfeatures2d\include;
D:\OpenCV\opencv-3\opencv\include;
D:\OpenCV\opencv-3\build;

Additional lib dirs:

D:\OpenCV\opencv-3\build\3rdparty\lib\Release
D:\OpenCV\opencv-3\build\3rdparty\ippicv\ippicv_win\lib\ia32
D:\OpenCV\opencv-3\build\lib\Release

Additional deps:

opencv_aruco320.lib
opencv_bgsegm320.lib
opencv_bioinspired320.lib
opencv_calib3d320.lib
opencv_ccalib320.lib
opencv_core320.lib
opencv_datasets320.lib
opencv_dnn320.lib
opencv_dpm320.lib
opencv_face320.lib
opencv_features2d320.lib
opencv_flann320.lib
opencv_fuzzy320.lib
opencv_highgui320.lib
opencv_imgcodecs320.lib
opencv_imgproc320.lib
opencv_java320.lib
opencv_line_descriptor320.lib
opencv_ml320.lib
opencv_objdetect320.lib
opencv_optflow320.lib
opencv_phase_unwrapping320.lib
opencv_photo320.lib
opencv_plot320.lib
opencv_python2.lib
opencv_reg320.lib
opencv_rgbd320.lib
opencv_saliency320.lib
opencv_shape320.lib
opencv_stereo320.lib
opencv_stitching320.lib
opencv_structured_light320.lib
opencv_superres320.lib
opencv_surface_matching320.lib
opencv_text320.lib
opencv_tracking320.lib
opencv_ts320.lib
opencv_video320.lib
opencv_videoio320.lib
opencv_videostab320.lib
opencv_xfeatures2d320.lib
opencv_ximgproc320.lib
opencv_xobjdetect320.lib
opencv_xphoto320.lib
ippicvmt.lib
IlmImf.lib
libjasper.lib
libjpeg.lib
libpng.lib
libprotobuf.lib
libtiff.lib
libwebp.lib
zlib.lib

source.cpp

#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/xfeatures2d.hpp"
#include "opencv2/opencv.hpp"
#include "opencv2/imgcodecs.hpp"

#include <iostream>
#include <string>
#include <vector>

using namespace cv;
using namespace cv::xfeatures2d;

/** @function main */
int main(int argc, char** argv)
{
	std::string fileImgA = "box.png";
	std::string fileImgB = "box_in_scene.png";

	Mat img_object = cv::imread(fileImgA, IMREAD_GRAYSCALE);
	Mat img_scene = imread(fileImgB, IMREAD_GRAYSCALE);

	if (!img_object.data || !img_scene.data)
	{
		std::cout << " --(!) Error reading images " << std::endl; return -1;
	}

	//-- Step 1: Detect the keypoints using SURF Detector
	int minHessian = 400;

	// Use Ptr as in https://github.com/kyamagu/mexopencv/issues/154
	Ptr<SurfFeatureDetector> detector = SurfFeatureDetector::create(minHessian);

	std::vector<KeyPoint> keypoints_object, keypoints_scene;

	detector->detect(img_object, keypoints_object);
	detector->detect(img_scene, keypoints_scene);

	//-- Step 2: Calculate descriptors (feature vectors)
	// Based on http://docs.opencv.org/3.2.0/d9/d97/tutorial_table_of_content_features2d.html
	Ptr<SurfDescriptorExtractor> extractor = SurfDescriptorExtractor::create();

	Mat descriptors_object, descriptors_scene;

	extractor->compute(img_object, keypoints_object, descriptors_object);
	extractor->compute(img_scene, keypoints_scene, descriptors_scene);

	//-- Step 3: Matching descriptor vectors using FLANN matcher
	FlannBasedMatcher matcher;
	std::vector< DMatch > matches;
	matcher.match(descriptors_object, descriptors_scene, matches);

	double max_dist = 0; double min_dist = 100;

	//-- Quick calculation of max and min distances between keypoints
	for (int i = 0; i < descriptors_object.rows; i++)
	{
		double dist = matches[i].distance;
		if (dist < min_dist) min_dist = dist;
		if (dist > max_dist) max_dist = dist;
	}

	printf("-- Max dist : %f \n", max_dist);
	printf("-- Min dist : %f \n", min_dist);

	//-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
	std::vector< DMatch > good_matches;

	for (int i = 0; i < descriptors_object.rows; i++)
	{
		if (matches[i].distance < 3 * min_dist)
		{
			good_matches.push_back(matches[i]);
		}
	}

	Mat img_matches;
	drawMatches(img_object, keypoints_object, img_scene, keypoints_scene,
		good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
		std::vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);

	//-- Localize the object
	std::vector<Point2f> obj;
	std::vector<Point2f> scene;

	for (int i = 0; i < good_matches.size(); i++)
	{
		//-- Get the keypoints from the good matches
		obj.push_back(keypoints_object[good_matches[i].queryIdx].pt);
		scene.push_back(keypoints_scene[good_matches[i].trainIdx].pt);
	}

	Mat H = findHomography(obj, scene, RANSAC);

	//-- Get the corners from the image_1 ( the object to be "detected" )
	std::vector<Point2f> obj_corners(4);
	obj_corners[0] = cvPoint(0, 0); obj_corners[1] = cvPoint(img_object.cols, 0);
	obj_corners[2] = cvPoint(img_object.cols, img_object.rows); obj_corners[3] = cvPoint(0, img_object.rows);
	std::vector<Point2f> scene_corners(4);

	perspectiveTransform(obj_corners, scene_corners, H);

	//-- Draw lines between the corners (the mapped object in the scene - image_2 )
	line(img_matches, scene_corners[0] + Point2f(img_object.cols, 0), scene_corners[1] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);
	line(img_matches, scene_corners[1] + Point2f(img_object.cols, 0), scene_corners[2] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);
	line(img_matches, scene_corners[2] + Point2f(img_object.cols, 0), scene_corners[3] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);
	line(img_matches, scene_corners[3] + Point2f(img_object.cols, 0), scene_corners[0] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);

	//-- Show detected matches
	namedWindow("image", WINDOW_NORMAL);
	imshow("image", img_matches);
	// scale image to fit on screen
	resizeWindow("image", 800, 600);

	waitKey(0);
	return 0;
}