import cv2 import numpy as np from matplotlib import pyplot as plt def drawlines(img1,img2,lines,pts1,pts2): ''' img1 - image on which we draw the epilines for the points in img2 lines - corresponding epilines ''' r,c = img1.shape[:2] img1 = cv2.cvtColor(img1,cv2.COLOR_GRAY2BGR) img2 = cv2.cvtColor(img2,cv2.COLOR_GRAY2BGR) for r,pt1,pt2 in zip(lines,pts1,pts2): color = tuple(np.random.randint(0,255,3).tolist()) x0,y0 = map(int, [0, -r[2]/r[1] ]) x1,y1 = map(int, [c, -(r[2]+r[0]*c)/r[1] ]) img1 = cv2.line(img1, (x0,y0), (x1,y1), color,1) img1 = cv2.circle(img1,tuple(pt1),5,color,-1) img2 = cv2.circle(img2,tuple(pt2),5,color,-1) return img1,img2 SOURCE_IMAGE1='../tea05.jpg' SOURCE_IMAGE2='../tea08.jpg' ## képek beolvasása img1 = cv2.imread(SOURCE_IMAGE1); img2 = cv2.imread(SOURCE_IMAGE2); ## a képet szürkeárnyalatossá konvertáljuk gray_img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY) gray_img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY) ## jellemzőpontok detektálása surf = cv2.xfeatures2d.SURF_create() keypoints1 = surf.detect(gray_img1, None) keypoints2 = surf.detect(gray_img2, None) ## kulcspont leírók számítása keypoints1, descriptors1 = surf.compute(gray_img1, keypoints1) keypoints2, descriptors2 = surf.compute(gray_img2, keypoints2) ## pontpárok keresése # FLANN parameterek FLANN_INDEX_KDTREE = 0 index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5) search_params = dict(checks=50) # or pass empty dictionary flann = cv2.FlannBasedMatcher(index_params,search_params) matches = flann.knnMatch(descriptors1,descriptors2,k=2) ## ez kNN-alapú, ## minden pontnak két lehetséges párja lehet # csak a jó párosításokat tároljuk el, amelyek átmentek a Lowe-teszten good = [] for m,n in matches: if m.distance < 0.7*n.distance: good.append(m) points1 = [] points2 = [] for m in good: points1.append(keypoints1[m.queryIdx].pt) points2.append(keypoints2[m.trainIdx].pt) points1, points2 = np.float32((points1, points2)) draw_params = dict(matchColor = (0,255,0), singlePointColor = (255,0,0), # matchesMask = matchesMask, flags = 0) matching_img = cv2.drawMatchesKnn(img1,keypoints1,img2,keypoints2,matches[:300],None) cv2.imwrite("matching_image.png", matching_img) ## A fundamentális mátrix meghatározása F, F_mask = cv2.findFundamentalMat(points1, points2, cv2.FM_8POINT) print("A fundamentális mátrix:") print(F) ## Az epipoláris egyenesek meghatározása lines1 = cv2.computeCorrespondEpilines(points2.reshape(-1,1,2), 2,F) lines1 = lines1.reshape(-1,3) img5,img6 = drawlines(gray_img1,gray_img2,lines1,points1,points2) cv2.imwrite('lines1.png', img5) lines2 = cv2.computeCorrespondEpilines(points1.reshape(-1,1,2), 1,F) lines2 = lines2.reshape(-1,3) img5,img6 = drawlines(gray_img2,gray_img1,lines2,points2,points1) cv2.imwrite('lines2.png', img5)