--- /dev/null
+import numpy as np\r
+import cv2, cv\r
+from common import anorm\r
+\r
+help_message = '''SURF image match \r
+\r
+USAGE: findobj.py [ <image1> <image2> ]\r
+'''\r
+\r
+\r
+def match(desc1, desc2, r_threshold = 0.75):\r
+ res = []\r
+ for i in xrange(len(desc1)):\r
+ dist = anorm( desc2 - desc1[i] )\r
+ n1, n2 = dist.argsort()[:2]\r
+ r = dist[n1] / dist[n2]\r
+ if r < r_threshold:\r
+ res.append((i, n1))\r
+ return np.array(res)\r
+\r
+def draw_match(img1, img2, p1, p2, status = None, H = None):\r
+ h1, w1 = img1.shape[:2]\r
+ h2, w2 = img2.shape[:2]\r
+ vis = np.zeros((max(h1, h2), w1+w2), np.uint8)\r
+ vis[:h1, :w1] = img1\r
+ vis[:h2, w1:w1+w2] = img2\r
+ vis = cv2.cvtColor(vis, cv.CV_GRAY2BGR)\r
+\r
+ if H is not None:\r
+ corners = np.float32([[0, 0], [w1, 0], [w1, h1], [0, h1]])\r
+ corners = np.int32( cv2.perspectiveTransform(corners.reshape(1, -1, 2), H).reshape(-1, 2) + (w1, 0) )\r
+ cv2.polylines(vis, [corners], True, (255, 255, 255))\r
+ \r
+ if status is None:\r
+ status = np.ones(len(p1), np.bool_)\r
+ green = (0, 255, 0)\r
+ red = (0, 0, 255)\r
+ for (x1, y1), (x2, y2), inlier in zip(np.int32(p1), np.int32(p2), status):\r
+ col = [red, green][inlier]\r
+ if not inlier:\r
+ cv2.line(vis, (x1, y1), (x2+w1, y2), col)\r
+ cv2.circle(vis, (x1, y1), 2, col, -1)\r
+ cv2.circle(vis, (x2+w1, y2), 2, col, -1)\r
+ return vis\r
+\r
+if __name__ == '__main__':\r
+ import sys\r
+ try: fn1, fn2 = sys.argv[1:3]\r
+ except:\r
+ fn1 = '../c/box.png'\r
+ fn2 = '../c/box_in_scene.png'\r
+ print help_message\r
+\r
+ img1 = cv2.imread(fn1, 0)\r
+ img2 = cv2.imread(fn2, 0)\r
+\r
+ surf = cv2.SURF(1000)\r
+ kp1, desc1 = surf.detect(img1, None, False)\r
+ kp2, desc2 = surf.detect(img2, None, False)\r
+ desc1.shape = (-1, surf.descriptorSize())\r
+ desc2.shape = (-1, surf.descriptorSize())\r
+ print 'img1 - %d features, img2 - %d features' % (len(kp1), len(kp2))\r
+\r
+ m = match(desc1, desc2)\r
+ matched_p1 = np.array([kp1[i].pt for i, j in m])\r
+ matched_p2 = np.array([kp2[j].pt for i, j in m])\r
+ H, status = cv2.findHomography(matched_p1, matched_p2, cv2.RANSAC, 10.0)\r
+ print '%d / %d inliers/matched' % (np.sum(status), len(status))\r
+\r
+ vis = draw_match(img1, img2, matched_p1, matched_p2, status, H)\r
+ cv2.imshow('find_obj SURF', vis)\r
+ cv2.waitKey()
\ No newline at end of file