// Draw matches between two images
public static Mat getMatchesImage(Mat query, Mat pattern, MatOfKeyPoint queryKp, MatOfKeyPoint trainKp, MatOfDMatch matches, int maxMatchesDrawn)
{
Mat outImg = new Mat();
List <DMatch> matchesList = matches.toList();
if (matchesList.Count > maxMatchesDrawn)
{
matchesList.RemoveRange(maxMatchesDrawn, matchesList.Count - maxMatchesDrawn);
}
MatOfDMatch tmpMatches = new MatOfDMatch();
tmpMatches.fromList(matchesList);
Features2d.drawMatches
(
query,
queryKp,
pattern,
trainKp,
tmpMatches,
outImg,
new Scalar(0, 200, 0, 255),
Scalar.all(-1),
new MatOfByte()
);
return(outImg);
}
/// <summary>
/// Crosses the matcher.
/// </summary>
/// <returns>The matcher.</returns>
/// <param name="queryDescriptors">Query descriptors.</param>
/// <param name="trainDescriptors">Train descriptors.</param>
public static IList <DMatch> CrossMatcher(MatOfFloat queryDescriptors, MatOfFloat trainDescriptors)
{
MatOfDMatch matchQT = new MatOfDMatch(), matchTQ = new MatOfDMatch();
List <DMatch> bmatch = new List <DMatch>();
DMatch[] dmatch;
if (trainDescriptors.cols() <= 0)
{
throw new ApplicationException("CrossMatcherの引数trainDescriptorsがありません。");
}
matcher.match(queryDescriptors, trainDescriptors, matchQT);
if (queryDescriptors.cols() <= 0)
{
throw new ApplicationException("CrossMatcherの引数queryDescriptorsがありません。");
}
matcher.match(trainDescriptors, queryDescriptors, matchTQ);
for (int i = 0; i < matchQT.rows(); i++)
{
DMatch forward = matchQT.toList()[i];
DMatch backward = matchTQ.toList()[forward.trainIdx];
if (backward.trainIdx == forward.queryIdx)
{
bmatch.Add(forward);
}
}
dmatch = bmatch.ToArray();
bmatch.Clear();
return(dmatch);
}
/// <summary>
/// Refines the matches with homography.
/// </summary>
/// <returns><c>true</c>, if matches with homography was refined, <c>false</c> otherwise.</returns>
/// <param name="queryKeypoints">Query keypoints.</param>
/// <param name="trainKeypoints">Train keypoints.</param>
/// <param name="reprojectionThreshold">Reprojection threshold.</param>
/// <param name="matches">Matches.</param>
/// <param name="homography">Homography.</param>
static bool refineMatchesWithHomography
(
MatOfKeyPoint queryKeypoints,
MatOfKeyPoint trainKeypoints,
float reprojectionThreshold,
MatOfDMatch matches,
Mat homography
)
{
//Debug.Log ("matches " + matches.ToString ());
int minNumberMatchesAllowed = 8;
List <KeyPoint> queryKeypointsList = queryKeypoints.toList();
List <KeyPoint> trainKeypointsList = trainKeypoints.toList();
List <DMatch> matchesList = matches.toList();
if (matchesList.Count < minNumberMatchesAllowed)
{
return(false);
}
// Prepare data for cv::findHomography
List <Point> srcPointsList = new List <Point>(matchesList.Count);
List <Point> dstPointsList = new List <Point>(matchesList.Count);
for (int i = 0; i < matchesList.Count; i++)
{
srcPointsList.Add(trainKeypointsList[matchesList[i].trainIdx].pt);
dstPointsList.Add(queryKeypointsList[matchesList[i].queryIdx].pt);
}
// Find homography matrix and get inliers mask
using (MatOfPoint2f srcPoints = new MatOfPoint2f())
using (MatOfPoint2f dstPoints = new MatOfPoint2f())
using (MatOfByte inliersMask = new MatOfByte(new byte[srcPointsList.Count]))
{
srcPoints.fromList(srcPointsList);
dstPoints.fromList(dstPointsList);
//Debug.Log ("srcPoints " + srcPoints.ToString ());
//Debug.Log ("dstPoints " + dstPoints.ToString ());
Calib3d.findHomography(srcPoints,
dstPoints,
Calib3d.FM_RANSAC,
reprojectionThreshold,
inliersMask, 2000, 0.955).copyTo(homography);
if (homography.rows() != 3 || homography.cols() != 3)
{
return(false);
}
//Debug.Log ("homography " + homography.ToString ());
//Debug.Log ("inliersMask " + inliersMask.dump ());
List <byte> inliersMaskList = inliersMask.toList();
List <DMatch> inliers = new List <DMatch>();
for (int i = 0; i < inliersMaskList.Count; i++)
{
if (inliersMaskList[i] == 1)
{
inliers.Add(matchesList[i]);
}
}
matches.fromList(inliers);
//Debug.Log ("matches " + matches.ToString ());
}
return(matchesList.Count > minNumberMatchesAllowed);
}
void Orb()
{
p1Mat = Imgcodecs.imread(Application.dataPath + "/Textures/1.jpg", 1);
p2Mat = Imgcodecs.imread(Application.dataPath + "/Textures/3.jpg", 1);
Imgproc.cvtColor(p1Mat, p1Mat, Imgproc.COLOR_BGR2RGB);
Imgproc.cvtColor(p2Mat, p2Mat, Imgproc.COLOR_BGR2RGB);
Imgproc.resize(p2Mat, p2Mat, new Size(p1Mat.width(), p1Mat.height()));
Debug.Log(p2Mat);
/*
* //仿射变换（矩阵旋转）
* float angle = UnityEngine.Random.Range(0, 360), scale = 1.0f;
* Point center = new Point(img2Mat.cols() * 0.5f, img2Mat.rows() * 0.5f);
*
* Mat affine_matrix = Imgproc.getRotationMatrix2D(center, angle, scale);
* Imgproc.warpAffine(img1Mat, img2Mat, affine_matrix, img2Mat.size());
*
* Texture2D texture = new Texture2D(img2Mat.cols(), img2Mat.rows());
* Utils.matToTexture2D(img2Mat, texture);
* outputRawImage.texture = texture;
*/
ORB detector = ORB.create();
ORB extractor = ORB.create();
//提取图一特征点
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
Mat descriptors1 = new Mat();
detector.detect(p1Mat, keypoints1);
extractor.compute(p1Mat, keypoints1, descriptors1);
//提取图二特征点
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
Mat descriptors2 = new Mat();
detector.detect(p2Mat, keypoints2);
extractor.compute(p2Mat, keypoints2, descriptors2);
//第一次匹配结果（密密麻麻）
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMINGLUT);
MatOfDMatch matches = new MatOfDMatch();
matcher.match(descriptors1, descriptors2, matches);
//筛选（非官方）
//计算向量距离的最大值/最小值
double max_dist = 0;
double min_dist = 15; //通过距离控制需要的特征。
//（设到10，最终只有2个耳朵匹配。。。）
//（设到15，尾巴也开始匹配。。。。。。）
//新建两个容器存放筛选样本
List <DMatch> matchesArray = matches.toList(); //用Unity版API多转一步
//Debug.Log(matchesArray.Count); //500
List <DMatch> goodmatchesArray = new List <DMatch>();
//Debug.Log(img1Mat.rows()); //512
for (int i = 0; i < matchesArray.Count; i++)
{
Debug.Log("[" + i + "]" + matchesArray[i].distance);
if (matchesArray[i].distance > max_dist)
{
//max_dist = matchesArray[i].distance;
}
if (matchesArray[i].distance < min_dist)
{
min_dist = matchesArray[i].distance;
}
}
//Debug.Log("The max distance is: " + max_dist);
Debug.Log("The min distance is: " + min_dist);
for (int i = 0; i < matchesArray.Count; i++)
{
if (matchesArray[i].distance < 2 * min_dist) //
{
goodmatchesArray.Add(matchesArray[i]);
}
}
MatOfDMatch newMatches = new MatOfDMatch();
newMatches.fromList(goodmatchesArray);
Debug.Log(newMatches.toList().Count); //第二次筛选后符合的
//绘制第二次筛选结果
dstMat = new Mat();
Features2d.drawMatches(p1Mat, keypoints1, p2Mat, keypoints2, newMatches, dstMat);
Texture2D t2d = new Texture2D(dstMat.width(), dstMat.height());
Utils.matToTexture2D(dstMat, t2d);
Sprite sp = Sprite.Create(t2d, new UnityEngine.Rect(0, 0, t2d.width, t2d.height), Vector2.zero);
m_dstImage.sprite = sp;
m_dstImage.preserveAspect = true;
}