void ComputerVisionAlgo(IntPtr greyscale)
{
Utils.copyToMat(greyscale, imageMat);
// Inverting Image pixel values
inMat = (Mat.ones(imageMat.rows(), imageMat.cols(), CvType.CV_8UC1) * 255) - imageMat;
// Creating Detector (Yellow Circle)
// MatOfKeyPoint keyMat = new MatOfKeyPoint();
// SimpleBlobDetector detector = SimpleBlobDetector.create();
// Creating Detector (Red Circle)
MatOfKeyPoint keyMat = new MatOfKeyPoint();
SimpleBlobDetector detector = SimpleBlobDetector.create();
inMat = imageMat;
detector.read(circparam_path);
// Finding circles
detector.detect(inMat, keyMat);
if (keyMat.size().height > 0)
{
blob_x = keyMat.get(0, 0)[0];
blob_y = keyMat.get(0, 0)[1];
blob_r = keyMat.get(0, 0)[2];
}
// Visualizing detected circles
m_ImageInfo.text = string.Format("Circle Count: {0}\n Circle[0]: {1} x {2} -- {3}",
keyMat.size().height, blob_x, blob_y, blob_r);
Features2d.drawKeypoints(imageMat, keyMat, outMat);
}
// 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);
}
void getKeyPoints(Mat matImg)
{
keyPix.Clear();
submats.Clear();
MatOfKeyPoint keypts = new MatOfKeyPoint();
Mat hierarchy = new Mat();
blobber.detect(matImg, keypts);
// Debug.Log("key points are " + keypts.size());
Mat imgWithKeyPts = new Mat();
Features2d.drawKeypoints(matImg, keypts, imgWithKeyPts, new Scalar(255, 255, 255), 4);
Texture2D matToText = new Texture2D(imgWithKeyPts.cols(), imgWithKeyPts.rows(), TextureFormat.RGBA32, false);
KeyPoint[] keyPtArray = keypts.toArray();
for (int i = 0; i < keyPtArray.Length; i++)
{
//keyPix.Add(Camera.main.ScreenToWorldPoint(new Vector3((float)keyPtArray[i].pt.x, (float)keyPtArray[i].pt.y), Camera.MonoOrStereoscopicEye.Mono));
keyPix.Add(new Vector3((float)keyPtArray[i].pt.x, (float)keyPtArray[i].pt.y, keyPtArray[i].size));
//keyPix3.Add(Camera.main.ScreenToViewportPoint(new Vector3((int)keyPtArray[i].pt.x, (int)keyPtArray[i].pt.y, 0)));
}
// disposal
Destroy(matToText);
imgWithKeyPts.Dispose();
keypts.Dispose();
hierarchy.Dispose();
}
// Use this for initialization
void Start()
{
Texture2D imgTexture = Resources.Load("detect_blob") as Texture2D;
Mat imgMat = new Mat(imgTexture.height, imgTexture.width, CvType.CV_8UC1);
Utils.texture2DToMat(imgTexture, imgMat);
Debug.Log("imgMat dst ToString " + imgMat.ToString());
Mat outImgMat = new Mat();
FeatureDetector blobDetector = FeatureDetector.create(FeatureDetector.SIMPLEBLOB);
blobDetector.read(Utils.getFilePath("blobparams.yml"));
MatOfKeyPoint keypoints = new MatOfKeyPoint();
blobDetector.detect(imgMat, keypoints);
Features2d.drawKeypoints(imgMat, keypoints, outImgMat);
Texture2D texture = new Texture2D(outImgMat.cols(), outImgMat.rows(), TextureFormat.RGBA32, false);
Utils.matToTexture2D(outImgMat, texture);
gameObject.GetComponent <Renderer> ().material.mainTexture = texture;
}
protected override void OnCreate(Bundle savedInstanceState)
{
base.OnCreate(savedInstanceState);
adapter = new TabsAdapter(this, SupportFragmentManager);
pager = FindViewById <ViewPager>(Resource.Id.viewpager);
var tabs = FindViewById <TabLayout>(Resource.Id.tabs);
pager.Adapter = adapter;
tabs.SetupWithViewPager(pager);
pager.OffscreenPageLimit = 3;
pager.PageSelected += (sender, args) =>
{
var fragment = adapter.InstantiateItem(pager, args.Position) as IFragmentVisible;
fragment?.BecameVisible();
};
Toolbar.MenuItemClick += (sender, e) =>
{
var intent = new Intent(this, typeof(AddItemActivity));;
StartActivity(intent);
};
SupportActionBar.SetDisplayHomeAsUpEnabled(false);
SupportActionBar.SetHomeButtonEnabled(false);
var src = new Mat[2];
var dst = new Mat[2];
var keyPoints1 = new MatOfKeyPoint();
var keyPoints2 = new MatOfKeyPoint();
var descripter1 = new Mat();
var descripter2 = new Mat();
var dmatch = new MatOfDMatch();
var output = new Mat();
src[0] = Imgcodecs.Imread("path/to/source/1.png");
src[1] = Imgcodecs.Imread("path/to/source/2.png");
dst[0] = new Mat();
dst[1] = new Mat();
Imgproc.CvtColor(src[0], dst[0], Imgproc.COLORBayerGR2GRAY);
Imgproc.CvtColor(src[1], dst[1], Imgproc.COLORBayerGR2GRAY);
var akaze = FeatureDetector.Create(FeatureDetector.Akaze);
var executor = DescriptorExtractor.Create(DescriptorExtractor.Akaze);
akaze.Detect(dst[0], keyPoints1);
akaze.Detect(dst[1], keyPoints2);
executor.Compute(dst[0], keyPoints1, descripter1);
executor.Compute(dst[1], keyPoints2, descripter2);
var matcher = DescriptorMatcher.Create(DescriptorMatcher.BruteforceHamming);
matcher.Match(descripter1, descripter2, dmatch);
Features2d.DrawMatches(src[0], keyPoints1, src[1], keyPoints2, dmatch, output);
}
// Use this for initialization
void Start()
{
Texture2D imgTexture = Resources.Load("lena") as Texture2D;
Mat img1Mat = new Mat(imgTexture.height, imgTexture.width, CvType.CV_8UC3);
Utils.texture2DToMat(imgTexture, img1Mat);
Debug.Log("img1Mat dst ToString " + img1Mat.ToString());
Mat img2Mat = new Mat(imgTexture.height, imgTexture.width, CvType.CV_8UC3);
Utils.texture2DToMat(imgTexture, img2Mat);
Debug.Log("img2Mat dst ToString " + img2Mat.ToString());
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());
FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
Mat descriptors1 = new Mat();
detector.detect(img1Mat, keypoints1);
extractor.compute(img1Mat, keypoints1, descriptors1);
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
Mat descriptors2 = new Mat();
detector.detect(img2Mat, keypoints2);
extractor.compute(img2Mat, keypoints2, descriptors2);
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMINGLUT);
MatOfDMatch matches = new MatOfDMatch();
matcher.match(descriptors1, descriptors2, matches);
Mat resultImg = new Mat();
Features2d.drawMatches(img1Mat, keypoints1, img2Mat, keypoints2, matches, resultImg);
Texture2D texture = new Texture2D(resultImg.cols(), resultImg.rows(), TextureFormat.RGBA32, false);
Utils.matToTexture2D(resultImg, texture);
gameObject.GetComponent <Renderer> ().material.mainTexture = texture;
}
// Update is called once per frame
void Update()
{
if (webCamTextureToMatHelper.IsPlaying() && webCamTextureToMatHelper.DidUpdateThisFrame())
{
Mat rgbaMat = webCamTextureToMatHelper.GetMat();
Imgproc.cvtColor(rgbaMat, rgbMat, Imgproc.COLOR_RGBA2RGB);
detector.detect(rgbaMat, keypoints);
// Debug.Log ("keypoints.ToString() " + keypoints.ToString());
Features2d.drawKeypoints(rgbMat, keypoints, rgbaMat, Scalar.all(-1), Features2d.NOT_DRAW_SINGLE_POINTS);
Imgproc.rectangle(rgbaMat, patternRect.tl(), patternRect.br(), new Scalar(255, 0, 0, 255), 5);
Utils.matToTexture2D(rgbaMat, texture, webCamTextureToMatHelper.GetBufferColors());
}
}
// Detects Corners with Detector Framework and Draws Keypoints to outMat
void CornerDetection()
{
// Creating Detector
int octaves = 6;
float corner_thresh = 0.015f;
float dog_thresh = 0.015f;
int max_detections = 5;
HarrisLaplaceFeatureDetector detector = HarrisLaplaceFeatureDetector.create(
octaves, corner_thresh, dog_thresh, max_detections);
// Finding corners
// imageMat = cached_initMat;
Core.flip(cached_initMat, imageMat, 0);
keyMat = new MatOfKeyPoint();
detector.detect(imageMat, keyMat);
// Draw corners
Features2d.drawKeypoints(imageMat, keyMat, outMat);
}
// Detects Blobs with Detector Framework and stores Top-down view into cached_homoMat
void BlobDetection()
{
SimpleBlobDetector detector = SimpleBlobDetector.create();
Core.flip(cached_initMat, imageMat, 0);
keyMat = new MatOfKeyPoint();
detector.detect(imageMat, keyMat);
Features2d.drawKeypoints(imageMat, keyMat, outMat);
if (keyMat.rows() < 7)
{
return;
}
for (int i = 0; i < 7; i++)
{
srcPointArray[i] = new Point(keyMat.get(i, 0)[0], keyMat.get(i, 0)[1]);
}
SortBox();
}
private void Run()
{
//if true, The error log of the Native side OpenCV will be displayed on the Unity Editor Console.
Utils.setDebugMode(true);
Texture2D imgTexture = Resources.Load("detect_blob") as Texture2D;
Mat imgMat = new Mat(imgTexture.height, imgTexture.width, CvType.CV_8UC1);
Utils.texture2DToMat(imgTexture, imgMat);
Debug.Log("imgMat.ToString() " + imgMat.ToString());
Mat outImgMat = new Mat();
SimpleBlobDetector blobDetector = SimpleBlobDetector.create();
Debug.Log("blobDetector.getDefaultName() " + blobDetector.getDefaultName());
blobDetector.read(blobparams_yml_filepath);
MatOfKeyPoint keypoints = new MatOfKeyPoint();
blobDetector.detect(imgMat, keypoints);
Features2d.drawKeypoints(imgMat, keypoints, outImgMat);
Texture2D texture = new Texture2D(outImgMat.cols(), outImgMat.rows(), TextureFormat.RGBA32, false);
Utils.matToTexture2D(outImgMat, texture);
gameObject.GetComponent <Renderer>().material.mainTexture = texture;
Utils.setDebugMode(false);
}
void ComputerVisionAlgo(IntPtr greyscale)
{
Utils.copyToMat(greyscale, imageMat);
// Creating Detector (Red Circle)
MatOfKeyPoint keyMat = new MatOfKeyPoint();
HarrisLaplaceFeatureDetector detector = HarrisLaplaceFeatureDetector.create(6, 0.015f, 0.015f, 5);
// Finding circles
Debug.Log(keyMat.size());
detector.detect(imageMat, keyMat);
if (keyMat.size().height > 0)
{
double blob_x = keyMat.get(0, 0)[0];
double blob_y = keyMat.get(0, 0)[1];
double blob_r = keyMat.get(0, 0)[2];
}
// Visualizing detected circles
// m_ImageInfo.text = string.Format("Circle Count: {0}\n Circle[0]: {1} x {2} -- {3}",
// keyMat.size().height, blob_x, blob_y, blob_r);
Features2d.drawKeypoints(imageMat, keyMat, outMat);
}
private void TryProcessImage(int index)
{
if (UseWebCam == false)
{
CurrentTexture = Sources[index];
}
else
{
CurrentTexture = webCamTexture;
}
using (Mat imgMat = new Mat(CurrentTexture.height, CurrentTexture.width, CvType.CV_8UC1))
using (FeatureDetector blobDetector = FeatureDetector.create(FeatureDetector.SIMPLEBLOB))
using (Mat outImgMat = new Mat())
using (MatOfKeyPoint keypoints = new MatOfKeyPoint())
{
if (CurrentTexture is Texture2D)
{
Utils.texture2DToMat(CurrentTexture as Texture2D, imgMat);
}
else if (CurrentTexture is WebCamTexture)
{
Utils.webCamTextureToMat(CurrentTexture as WebCamTexture, imgMat);
}
else
{
Utils.textureToMat(CurrentTexture, imgMat);
}
Debug.Log("imgMat dst ToString " + imgMat.ToString());
Imgproc.threshold(imgMat, imgMat, 0, 255, Imgproc.THRESH_BINARY | Imgproc.THRESH_OTSU);
Imgproc.erode(imgMat, imgMat, erodeMat, new Point(1, 1), 5);
blobDetector.read(Utils.getFilePath("blobparams.yml"));
blobDetector.detect(imgMat, keypoints);
Features2d.drawKeypoints(imgMat, keypoints, outImgMat);
KeyPoint[] points = keypoints.toArray();
ProcessKeyPoints(points, outImgMat);
Mat finalMat = outImgMat;
if (texture != null &&
(texture.width != finalMat.cols() || texture.height != finalMat.rows()))
{
DestroyImmediate(texture);
texture = null;
}
if (texture == null)
{
texture = new Texture2D(finalMat.cols(), finalMat.rows(), TextureFormat.RGBA32, false);
}
Utils.matToTexture2D(finalMat, texture);
gameObject.GetComponent <Renderer>().material.mainTexture = texture;
}
}
public bool descriptorsORB_Old(Mat RGB, Mat cameraFeed, string targetName)//找出特徵的顏色方法三(可運行但效率不佳放棄)
{
if (RGB == null)
{
Debug.Log("RGB Mat is Null");
return(false);
}
//將傳入的RGB存入Src
Mat SrcMat = new Mat();
RGB.copyTo(SrcMat);
//比對樣本
Texture2D imgTexture = Resources.Load(targetName) as Texture2D;
// Texture2D imgTexture2 = Resources.Load("lenaK") as Texture2D;
//Texture2D轉Mat
Mat img1Mat = new Mat(imgTexture.height, imgTexture.width, CvType.CV_8UC3);
Utils.texture2DToMat(imgTexture, img1Mat);
//創建 ORB的特徵點裝置
FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
//產生存放特徵點Mat
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
Mat descriptors1 = new Mat();
MatOfKeyPoint keypointsSrc = new MatOfKeyPoint();
Mat descriptorsSrc = new Mat();
//找特徵點圖1
detector.detect(img1Mat, keypoints1);
extractor.compute(img1Mat, keypoints1, descriptors1);
//找特徵點圖Src
detector.detect(SrcMat, keypointsSrc);
extractor.compute(SrcMat, keypointsSrc, descriptorsSrc);
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMINGLUT);
MatOfDMatch matches = new MatOfDMatch();
matcher.match(descriptors1, descriptorsSrc, matches);
DMatch[] arrayDmatch = matches.toArray();
for (int i = arrayDmatch.Length - 1; i >= 0; i--)
{
// Debug.Log("match " + i + ": " + arrayDmatch[i].distance);
}
//做篩選
double max_dist = 0;
double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
double dist = new double();
for (int i = 0; i < matches.rows(); i++)
{
dist = arrayDmatch[i].distance;
if (dist < min_dist)
{
min_dist = dist;
}
if (dist > max_dist)
{
max_dist = dist;
}
}
Debug.Log("Max dist :" + max_dist);
Debug.Log("Min dist :" + min_dist);
//只畫好的點
List <DMatch> matchesGoodList = new List <DMatch>();
for (int i = 0; i < matches.rows(); i++)
{
//if (arrayDmatch[i].distance < RateDist.value * min_dist)
//{
// //Debug.Log("match " + i + ": " + arrayDmatch[i].distance);
// matchesGoodList.Add(arrayDmatch[i]);
//}
}
MatOfDMatch matchesGood = new MatOfDMatch();
matchesGood.fromList(matchesGoodList);
//Draw Keypoints
Features2d.drawKeypoints(SrcMat, keypointsSrc, SrcMat);
//做輸出的轉換予宣告
Mat resultImg = new Mat();
// Features2d.drawMatches(img1Mat, keypoints1, SrcMat, keypointsSrc, matchesGood, resultImg);
List <Point> P1 = new List <Point>();
// List<Point> P2 = new List<Point>();
List <Point> pSrc = new List <Point>();
Debug.Log("MatchCount" + matchesGoodList.Count);
for (int i = 0; i < matchesGoodList.Count; i++)
{
P1.Add(new Point(keypoints1.toArray()[matchesGoodList[i].queryIdx].pt.x, keypoints1.toArray()[matchesGoodList[i].queryIdx].pt.y));
pSrc.Add(new Point(keypointsSrc.toArray()[matchesGoodList[i].trainIdx].pt.x, keypointsSrc.toArray()[matchesGoodList[i].trainIdx].pt.y));
//Debug.Log("ID = " + matchesGoodList[i].queryIdx );
//Debug.Log("x,y =" + (int)keypoints1.toArray()[matchesGoodList[i].queryIdx].pt.x + "," + (int)keypoints1.toArray()[matchesGoodList[i].queryIdx].pt.y);
//Debug.Log("x,y =" + (int)keypoints2.toArray()[matchesGoodList[i].trainIdx].pt.x + "," + (int)keypoints2.toArray()[matchesGoodList[i].trainIdx].pt.y);
}
MatOfPoint2f p2fTarget = new MatOfPoint2f(P1.ToArray());
MatOfPoint2f p2fSrc = new MatOfPoint2f(pSrc.ToArray());
Mat matrixH = Calib3d.findHomography(p2fTarget, p2fSrc, Calib3d.RANSAC, 3);
List <Point> srcPointCorners = new List <Point>();
srcPointCorners.Add(new Point(0, 0));
srcPointCorners.Add(new Point(img1Mat.width(), 0));
srcPointCorners.Add(new Point(img1Mat.width(), img1Mat.height()));
srcPointCorners.Add(new Point(0, img1Mat.height()));
Mat originalRect = Converters.vector_Point2f_to_Mat(srcPointCorners);
List <Point> srcPointCornersEnd = new List <Point>();
srcPointCornersEnd.Add(new Point(0, img1Mat.height()));
srcPointCornersEnd.Add(new Point(0, 0));
srcPointCornersEnd.Add(new Point(img1Mat.width(), 0));
srcPointCornersEnd.Add(new Point(img1Mat.width(), img1Mat.height()));
Mat changeRect = Converters.vector_Point2f_to_Mat(srcPointCornersEnd);
Core.perspectiveTransform(originalRect, changeRect, matrixH);
List <Point> srcPointCornersSave = new List <Point>();
Converters.Mat_to_vector_Point(changeRect, srcPointCornersSave);
if ((srcPointCornersSave[2].x - srcPointCornersSave[0].x) < 5 || (srcPointCornersSave[2].y - srcPointCornersSave[0].y) < 5)
{
Debug.Log("Match Out Put image is to small");
SrcMat.copyTo(cameraFeed);
SrcMat.release();
Imgproc.putText(cameraFeed, "X-S", new Point(10, 50), 0, 1, new Scalar(255, 255, 255), 2);
return(false);
}
// Features2d.drawMatches(img1Mat, keypoints1, SrcMat, keypointsSrc, matchesGood, resultImg);
Imgproc.line(SrcMat, srcPointCornersSave[0], srcPointCornersSave[1], new Scalar(255, 0, 0), 3);
Imgproc.line(SrcMat, srcPointCornersSave[1], srcPointCornersSave[2], new Scalar(255, 0, 0), 3);
Imgproc.line(SrcMat, srcPointCornersSave[2], srcPointCornersSave[3], new Scalar(255, 0, 0), 3);
Imgproc.line(SrcMat, srcPointCornersSave[3], srcPointCornersSave[0], new Scalar(255, 0, 0), 3);
SrcMat.copyTo(cameraFeed);
keypoints1.release();
img1Mat.release();
SrcMat.release();
return(true);
}
//============================================================
//=================以下為沒有再使用的函式=====================
//============================================================
//找出特徵的顏色方法三(ORB特徵點比對)
public bool descriptorsORB(Mat RGB, Mat cameraFeed, string targetName)
{
if (RGB == null)
{
Debug.Log("RGB Mat is Null");
return(false);
}
//將傳入的RGB存入Src
Mat SrcMat = new Mat();
RGB.copyTo(SrcMat);
//比對樣本載入
Texture2D imgTexture = Resources.Load(targetName) as Texture2D;
//Texture2D轉Mat
Mat targetMat = new Mat(imgTexture.height, imgTexture.width, CvType.CV_8UC3);
Utils.texture2DToMat(imgTexture, targetMat);
//創建 ORB的特徵點裝置
FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
//產生存放特徵點Mat
MatOfKeyPoint keypointsTarget = new MatOfKeyPoint();
Mat descriptorsTarget = new Mat();
MatOfKeyPoint keypointsSrc = new MatOfKeyPoint();
Mat descriptorsSrc = new Mat();
//找特徵點圖Target
detector.detect(targetMat, keypointsTarget);
extractor.compute(targetMat, keypointsTarget, descriptorsTarget);
//找特徵點圖Src
detector.detect(SrcMat, keypointsSrc);
extractor.compute(SrcMat, keypointsSrc, descriptorsSrc);
//創建特徵點比對物件
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMINGLUT);
MatOfDMatch matches = new MatOfDMatch();
//丟入兩影像的特徵點
matcher.match(descriptorsTarget, descriptorsSrc, matches);
DMatch[] arrayDmatch = matches.toArray();
//做篩選
double max_dist = 0;
double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
double dist = new double();
for (int i = 0; i < matches.rows(); i++)
{
dist = arrayDmatch[i].distance;
if (dist < min_dist)
{
min_dist = dist;
}
if (dist > max_dist)
{
max_dist = dist;
}
}
Debug.Log("Max dist :" + max_dist);
Debug.Log("Min dist :" + min_dist);
List <DMatch> matchesGoodList = new List <DMatch>();
MatOfDMatch matchesGood = new MatOfDMatch();
matchesGood.fromList(matchesGoodList);
//Draw Keypoints
Features2d.drawKeypoints(SrcMat, keypointsSrc, SrcMat);
List <Point> pTarget = new List <Point>();
List <Point> pSrc = new List <Point>();
Debug.Log("MatchCount" + matchesGoodList.Count);
for (int i = 0; i < matchesGoodList.Count; i++)
{
pTarget.Add(new Point(keypointsTarget.toArray()[matchesGoodList[i].queryIdx].pt.x, keypointsTarget.toArray()[matchesGoodList[i].queryIdx].pt.y));
pSrc.Add(new Point(keypointsSrc.toArray()[matchesGoodList[i].trainIdx].pt.x, keypointsSrc.toArray()[matchesGoodList[i].trainIdx].pt.y));
}
MatOfPoint2f p2fTarget = new MatOfPoint2f(pTarget.ToArray());
MatOfPoint2f p2fSrc = new MatOfPoint2f(pSrc.ToArray());
Mat matrixH = Calib3d.findHomography(p2fTarget, p2fSrc, Calib3d.RANSAC, 3);
List <Point> srcPointCorners = new List <Point>();
srcPointCorners.Add(new Point(0, 0));
srcPointCorners.Add(new Point(targetMat.width(), 0));
srcPointCorners.Add(new Point(targetMat.width(), targetMat.height()));
srcPointCorners.Add(new Point(0, targetMat.height()));
Mat originalRect = Converters.vector_Point2f_to_Mat(srcPointCorners);
List <Point> srcPointCornersEnd = new List <Point>();
srcPointCornersEnd.Add(new Point(0, targetMat.height()));
srcPointCornersEnd.Add(new Point(0, 0));
srcPointCornersEnd.Add(new Point(targetMat.width(), 0));
srcPointCornersEnd.Add(new Point(targetMat.width(), targetMat.height()));
Mat changeRect = Converters.vector_Point2f_to_Mat(srcPointCornersEnd);
Core.perspectiveTransform(originalRect, changeRect, matrixH);
List <Point> srcPointCornersSave = new List <Point>();
Converters.Mat_to_vector_Point(changeRect, srcPointCornersSave);
if ((srcPointCornersSave[2].x - srcPointCornersSave[0].x) < 5 || (srcPointCornersSave[2].y - srcPointCornersSave[0].y) < 5)
{
Debug.Log("Match Out Put image is to small");
SrcMat.copyTo(cameraFeed);
SrcMat.release();
Imgproc.putText(cameraFeed, targetName, srcPointCornersSave[0], 0, 1, new Scalar(255, 255, 255), 2);
return(false);
}
//畫出框框
Imgproc.line(SrcMat, srcPointCornersSave[0], srcPointCornersSave[1], new Scalar(255, 0, 0), 3);
Imgproc.line(SrcMat, srcPointCornersSave[1], srcPointCornersSave[2], new Scalar(255, 0, 0), 3);
Imgproc.line(SrcMat, srcPointCornersSave[2], srcPointCornersSave[3], new Scalar(255, 0, 0), 3);
Imgproc.line(SrcMat, srcPointCornersSave[3], srcPointCornersSave[0], new Scalar(255, 0, 0), 3);
//畫中心
Point middlePoint = new Point((srcPointCornersSave[0].x + srcPointCornersSave[2].x) / 2, (srcPointCornersSave[0].y + srcPointCornersSave[2].y) / 2);
Imgproc.line(SrcMat, middlePoint, middlePoint, new Scalar(0, 0, 255), 10);
SrcMat.copyTo(cameraFeed);
keypointsTarget.release();
targetMat.release();
SrcMat.release();
return(true);
}
public void processFrame()
{
if (inversion)
{
//flip
Core.bitwise_not(toneMat, toneMat);
}
if (resize)
{
Imgproc.resize(toneMat, toneMat, new Size((int)Math.Round(resizeRatio * toneMat.width()), (int)Math.Round(resizeRatio * toneMat.height())));
}
//
if (toneThreshold)
{
Imgproc.threshold(toneMat, toneMat, thresholdValue, 255, Imgproc.THRESH_BINARY);
}
if (blobs)
{
blobDetector.detect(toneMat, keypoints);
Features2d.drawKeypoints(toneMat, keypoints, toneMat);
}
if (blur)
{
Imgproc.blur(toneMat, toneMat, new Size(blurSize, blurSize));
}
if (centerPoint)
{
moments.Add(Imgproc.moments(toneMat, true));
WeightedCentroid.Add(new Point((int)Math.Round(moments[0].m10 / moments[0].m00), (int)Math.Round(moments[0].m01 / moments[0].m00)));
Debug.Log("center: " + WeightedCentroid[0].x + ", " + WeightedCentroid[0].y);
}
if (edge)
{
Imgproc.Canny(toneMat, toneMat, thresholdValue * 0.5, thresholdValue);
//Imgproc.findContours (toneMat, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE );
//
// foreach(MatOfPoint i in contours){
// Debug.Log ("contour " + i + ": " + i.ToString());
// }
//Debug.Log ("contours count: " + contours.Count);
moments.Add(Imgproc.moments(toneMat, true));
if (WeightedCentroid.Count == 0)
{
moments.Add(Imgproc.moments(toneMat, true));
WeightedCentroid.Add(new Point(0, 0));
}
WeightedCentroid.Add(new Point((int)Math.Round(moments[1].m10 / moments[1].m00), (int)Math.Round(moments[1].m01 / moments[1].m00)));
if (thresholdValue >= thresholdValueCap && edgeCenterPoint == true)
{
Imgproc.ellipse(toneMat, WeightedCentroid [1], new Size(20, 20), 1, 0.1, 360, new Scalar(180), 10);
Imgproc.putText(toneMat, " Edge center point", WeightedCentroid [1], 0, 1.5, new Scalar(180), 5);
}
}
//draw center
if (centerPoint)
{
Imgproc.ellipse(toneMat, WeightedCentroid [0], new Size(20, 20), 1, 0.1, 360, new Scalar(180), 10);
Imgproc.putText(toneMat, " Tone center point", WeightedCentroid [0], 0, 1.5, new Scalar(180), 5);
}
if (resize)
{
Imgproc.resize(toneMat, toneMat, new Size((int)Math.Round((1 / resizeRatio) * toneMat.width()), (int)Math.Round((1 / resizeRatio) * toneMat.height())));
}
//assign to display
if (showProcessing)
{
rgbaMat = toneMat;
}
else
{
rgbaMat = cloneMat;
}
WeightedCentroid.Clear();
moments.Clear();
contours.Clear();
framesDropCount = 0;
}
private void Update()
{
inputMat = webCamTextureToMatHelper.GetMat();
MatOfKeyPoint camKeyPoints = new MatOfKeyPoint();
Mat camDescriptors = new Mat();
Imgproc.cvtColor(inputMat, grayMat, Imgproc.COLOR_BGR2GRAY);
detector.detect(grayMat, camKeyPoints);
extractor.compute(grayMat, camKeyPoints, camDescriptors);
if (camKeyPoints.toList().Count < 1)
{
return;
}
List <MatOfDMatch> matches = new List <MatOfDMatch>();
matcher.knnMatch(makerDescriptors, camDescriptors, matches, 2);
//-- Filter matches using the Lowe's ratio test
float ratioThresh = 0.75f;
List <DMatch> listOfGoodMatches = new List <DMatch>();
for (int i = 0; i < matches.Count; i++)
{
if (matches[i].rows() > 1)
{
DMatch[] dMatches = matches[i].toArray();
if (dMatches[0].distance < ratioThresh * dMatches[1].distance)
{
listOfGoodMatches.Add(dMatches[0]);
}
}
}
MatOfDMatch goodMatches = new MatOfDMatch();
goodMatches.fromList(listOfGoodMatches);
//-- Draw matches
Mat resultImg = new Mat();
Features2d.drawMatches(makerMat, makerKeyPoints, grayMat, camKeyPoints, goodMatches, resultImg);
//listOfGoodMatches = goodMatches.toList();
////-- Localize the object
//List<Point> obj = new List<Point>();
//List<Point> scene = new List<Point>();
//List<KeyPoint> listOfKeypointsObject = makerKeyPoints.toList();
//List<KeyPoint> listOfKeypointsScene = camKeyPoints.toList();
//for (int i = 0; i < listOfGoodMatches.Count(); i++)
//{
// //-- Get the keypoints from the good matches
// obj.Add(listOfKeypointsObject[listOfGoodMatches[i].queryIdx].pt);
// scene.Add(listOfKeypointsScene[listOfGoodMatches[i].trainIdx].pt);
//}
//MatOfPoint2f objMat = new MatOfPoint2f();
//MatOfPoint2f sceneMat = new MatOfPoint2f();
//objMat.fromList(obj);
//sceneMat.fromList(scene);
//double ransacReprojThreshold = 3.0;
//Mat H = Calib3d.findHomography(objMat, sceneMat, Calib3d.RANSAC, ransacReprojThreshold);
////-- Get the corners from the image_1 ( the object to be "detected" )
//Mat objCorners = new Mat(4, 1, CvType.CV_32FC2);
//Mat sceneCorners = new Mat();
//float[] objCornersData = new float[(int)(objCorners.total() * objCorners.channels())];
//objCorners.get(0, 0, objCornersData);
//objCornersData[0] = 0;
//objCornersData[1] = 0;
//objCornersData[2] = makerMat.cols();
//objCornersData[3] = 0;
//objCornersData[4] = makerMat.cols();
//objCornersData[5] = makerMat.rows();
//objCornersData[6] = 0;
//objCornersData[7] = makerMat.rows();
//objCorners.put(0, 0, objCornersData);
//Core.perspectiveTransform(objCorners, sceneCorners, H);
//byte[] sceneCornersData = new byte[(int)(sceneCorners.total() * sceneCorners.channels())];
//sceneCorners.get(0, 0, sceneCornersData);
////-- Draw lines between the corners (the mapped object in the scene - image_2 )
//Imgproc.line(resultImg, new Point(sceneCornersData[0] + makerMat.cols(), sceneCornersData[1]),
// new Point(sceneCornersData[2] + makerMat.cols(), sceneCornersData[3]), new Scalar(0, 255, 0), 4);
//Imgproc.line(resultImg, new Point(sceneCornersData[2] + makerMat.cols(), sceneCornersData[3]),
// new Point(sceneCornersData[4] + makerMat.cols(), sceneCornersData[5]), new Scalar(0, 255, 0), 4);
//Imgproc.line(resultImg, new Point(sceneCornersData[4] + makerMat.cols(), sceneCornersData[5]),
// new Point(sceneCornersData[6] + makerMat.cols(), sceneCornersData[7]), new Scalar(0, 255, 0), 4);
//Imgproc.line(resultImg, new Point(sceneCornersData[6] + makerMat.cols(), sceneCornersData[7]),
// new Point(sceneCornersData[0] + makerMat.cols(), sceneCornersData[1]), new Scalar(0, 255, 0), 4);
if (!first)
{
texture = new Texture2D(resultImg.cols(), resultImg.rows(), TextureFormat.RGBA32, false);
dstQuad.GetComponent <Renderer>().material.mainTexture = texture;
first = true;
}
Utils.matToTexture2D(resultImg, texture);
}
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;
}
