! 簡易パノラマを OPENCV とpython です

 # matching features of two images
 import cv2
 import sys
 import scipy as sp
 import numpy as np
 
 if len(sys.argv) < 3:
    print 'usage: %s img1 img2' % sys.argv[0]
    sys.exit(1)
 
 img1_path = sys.argv[1]
 img2_path = sys.argv[2]
 
 img1 = cv2.imread(img1_path, cv2.IMREAD_GRAYSCALE)
 img2 = cv2.imread(img2_path, cv2.IMREAD_GRAYSCALE)
 
 # detector = cv2.ORB_create()
 detector = cv2.AKAZE_create()
 
 kp1, des1 = detector.detectAndCompute(img1, None)
 kp2, des2 = detector.detectAndCompute(img2, None)
 
 print '#keypoints in image1: %d, image2: %d' % (len(kp1), len(kp2))
 
 # # descriptors
 
 # match the keypoints
 matcher = cv2.BFMatcher(cv2.NORM_HAMMING)
 matches = matcher.match(des1, des2)
 
 # visualize the matches
 print '#matches:', len(matches)
 dist = [m.distance for m in matches]
 
 print 'distance: min: %.3f' % min(dist)
 print 'distance: mean: %.3f' % (sum(dist) / len(dist))
 print 'distance: max: %.3f' % max(dist)
 
 # threshold: half the mean
 thres_dist = (sum(dist) / len(dist)) * 0.5
 
 # keep only the reasonable matches
 sel_matches = [m for m in matches if m.distance < thres_dist]
 
 print '#selected matches:', len(sel_matches)
 
 # #####################################
 # visualization
 h1, w1 = img1.shape[:2]
 h2, w2 = img2.shape[:2]
 #
 
 view = sp.zeros((max(h1, h2), (w1 + w2), 3), sp.uint8)
 # view = sp.zeros((max(int(h1*1.2), int(h2*1.2)), int((w1 + w2)*1.5), 3), sp.uint8)
 # view = sp.zeros(((h1+ h2), w1 + w2, 3), sp.uint8)
   
 ## src_pts = np.float32([ kp1[m.queryIdx].pt for m in good ]).reshape(-1,1,2)
 ## dst_pts = np.float32([ kp2[m.trainIdx].pt for m in good ]).reshape(-1,1,2)
 src_pts = np.float32([ kp1[m.queryIdx].pt for m in sel_matches ]).reshape(-1,1,2)
 dst_pts = np.float32([ kp2[m.trainIdx].pt for m in sel_matches ]).reshape(-1,1,2)
 
 ## M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,5.0)
 M, mask = cv2.findHomography(src_pts, dst_pts)
 # matchesMask = mask.ravel().tolist()
 
 ## dst = cv2.warpPerspective(img1,mask,(h1*1.5,w1*1.1))
 ### dst = cv2.warpPerspective(img1,M,((h1*1.5).integer(),(w1*1.1).integer()))
 
 # src1 = cv2.warpPerspective(img1,M,(w1,h1))
 # dst2 = cv2.warpPerspective(img2,M,(w2,h2))
 #
 # src1 = cv2.warpPerspective(img1,M,(int(w1*1.5),int(h1*1.1)))
 # dst2 = cv2.warpPerspective(img2,M,(int(w2*1.5),int(h2*1.1)))
 
 src1 = cv2.warpPerspective(img1,M,(int(w1*1.5),int(h1*1.1)))
 
 for yy in range(w2):
    for xx in range(h2):
	src1[xx,yy] = img2[xx,yy]
 
 ## cv2.imshow("view", view)
 cv2.imshow("view", src1)
 ## cv2.imshow("img1", img1)
 ## cv2.imshow("img2", img2)
 
 ## cv2.imshow("dest1", src1)
 ## cv2.imshow("dest2", dst2)
 #
 cv2.waitKey()