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| #!/usr/bin/env python | |
| ''' | |
| Uses SURF to match two images. | |
| Based on the sample code from opencv: | |
| samples/python2/find_obj.py | |
| USAGE | |
| find_obj.py <image1> <image2> | |
| ''' | |
| import numpy | |
| import cv2 | |
| import sys | |
| ############################################################################### | |
| # Image Matching | |
| ############################################################################### | |
| def match_images(img1, img2): | |
| """Given two images, returns the matches""" | |
| detector = cv2.SURF(400, 5, 5) | |
| matcher = cv2.BFMatcher(cv2.NORM_L2) | |
| kp1, desc1 = detector.detectAndCompute(img1, None) | |
| kp2, desc2 = detector.detectAndCompute(img2, None) | |
| #print 'img1 - %d features, img2 - %d features' % (len(kp1), len(kp2)) | |
| raw_matches = matcher.knnMatch(desc1, trainDescriptors = desc2, k = 2) #2 | |
| kp_pairs = filter_matches(kp1, kp2, raw_matches) | |
| return kp_pairs | |
| def filter_matches(kp1, kp2, matches, ratio = 0.75): | |
| mkp1, mkp2 = [], [] | |
| for m in matches: | |
| if len(m) == 2 and m[0].distance < m[1].distance * ratio: | |
| m = m[0] | |
| mkp1.append( kp1[m.queryIdx] ) | |
| mkp2.append( kp2[m.trainIdx] ) | |
| kp_pairs = zip(mkp1, mkp2) | |
| return kp_pairs | |
| ############################################################################### | |
| # Match Diplaying | |
| ############################################################################### | |
| def explore_match(win, img1, img2, kp_pairs, status = None, H = None): | |
| h1, w1 = img1.shape[:2] | |
| h2, w2 = img2.shape[:2] | |
| vis = numpy.zeros((max(h1, h2), w1+w2), numpy.uint8) | |
| vis[:h1, :w1] = img1 | |
| vis[:h2, w1:w1+w2] = img2 | |
| vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR) | |
| if H is not None: | |
| corners = numpy.float32([[0, 0], [w1, 0], [w1, h1], [0, h1]]) | |
| corners = numpy.int32( cv2.perspectiveTransform(corners.reshape(1, -1, 2), H).reshape(-1, 2) + (w1, 0) ) | |
| cv2.polylines(vis, [corners], True, (255, 255, 255)) | |
| if status is None: | |
| status = numpy.ones(len(kp_pairs), numpy.bool_) | |
| p1 = numpy.int32([kpp[0].pt for kpp in kp_pairs]) | |
| p2 = numpy.int32([kpp[1].pt for kpp in kp_pairs]) + (w1, 0) | |
| green = (0, 255, 0) | |
| red = (0, 0, 255) | |
| white = (255, 255, 255) | |
| kp_color = (51, 103, 236) | |
| for (x1, y1), (x2, y2), inlier in zip(p1, p2, status): | |
| if inlier: | |
| col = green | |
| cv2.circle(vis, (x1, y1), 2, col, -1) | |
| cv2.circle(vis, (x2, y2), 2, col, -1) | |
| else: | |
| col = red | |
| r = 2 | |
| thickness = 3 | |
| cv2.line(vis, (x1-r, y1-r), (x1+r, y1+r), col, thickness) | |
| cv2.line(vis, (x1-r, y1+r), (x1+r, y1-r), col, thickness) | |
| cv2.line(vis, (x2-r, y2-r), (x2+r, y2+r), col, thickness) | |
| cv2.line(vis, (x2-r, y2+r), (x2+r, y2-r), col, thickness) | |
| vis0 = vis.copy() | |
| for (x1, y1), (x2, y2), inlier in zip(p1, p2, status): | |
| if inlier: | |
| cv2.line(vis, (x1, y1), (x2, y2), green) | |
| cv2.imshow(win, vis) | |
| def draw_matches(window_name, kp_pairs, img1, img2): | |
| """Draws the matches for """ | |
| mkp1, mkp2 = zip(*kp_pairs) | |
| p1 = numpy.float32([kp.pt for kp in mkp1]) | |
| p2 = numpy.float32([kp.pt for kp in mkp2]) | |
| if len(kp_pairs) >= 4: | |
| H, status = cv2.findHomography(p1, p2, cv2.RANSAC, 5.0) | |
| #print '%d / %d inliers/matched' % (numpy.sum(status), len(status)) | |
| else: | |
| H, status = None, None | |
| #print '%d matches found, not enough for homography estimation' % len(p1) | |
| if len(p1): | |
| explore_match(window_name, img1, img2, kp_pairs, status, H) | |
| ############################################################################### | |
| # Test Main | |
| ############################################################################### | |
| if __name__ == '__main__': | |
| """Test code: Uses the two specified""" | |
| if len(sys.argv) < 3: | |
| print "No filenames specified" | |
| print "USAGE: find_obj.py <image1> <image2>" | |
| sys.exit(1) | |
| fn1 = sys.argv[1] | |
| fn2 = sys.argv[2] | |
| img1 = cv2.imread(fn1, 0) | |
| img2 = cv2.imread(fn2, 0) | |
| if img1 is None: | |
| print 'Failed to load fn1:', fn1 | |
| sys.exit(1) | |
| if img2 is None: | |
| print 'Failed to load fn2:', fn2 | |
| sys.exit(1) | |
| kp_pairs = match_images(img1, img2) | |
| if kp_pairs: | |
| draw_matches('find_obj', kp_pairs, img1, img2) | |
| cv2.waitKey() | |
| cv2.destroyAllWindows() | |
| else: | |
| print "No matches found" | |
Yes this does work..
Which OpenCV version you have used? Mine is 3.1.0 and it does not have SURF() method
Hey,
Yes, it works with version 3 of OpenCV, but you need to modify line 34:
cv2.xfeatures2d.SURF_create(400, 5, 5)
Because in OpenCV 3 that SURF module and others are not in the project by default anymore. You need to install or compile the opencv_contrib package https://github.com/Itseez/opencv_contrib
If you need it for Raspberry Pi 2 raspbian i compiled and made a package for them http://soc.ninja/downloads
Following your advice, @ivaniclixx, This line:
"raw_matches = matcher.knnMatch(desc1, trainDescriptors=desc2, k=2) # 2"
Gives this error:
"error: (-215) _queryDescriptors.type() == trainDescType in function knnMatchImpl"
Any ideas what might be wrong? This error message isn't very descriptive...
how to import two image?
Does this work?