def main(args):
assert isinstance(args, argparse.Namespace), 'args must be of type argparse.Namespace not {0}'.format(type(args))
sift = cv2.SIFT()
flann = cv2.FlannBasedMatcher({'algorithm': 0, 'trees': 5}, {'checks': 50})
result, result_gry = None, None
for path in args.paths:
try:
assert os.path.exists(path), '{0} is not a valid path'.format(path)
logger.info('processing {0}'.format(path))
cam = cv2.VideoCapture(path)
logger.debug('opened video')
count = 0
while True:
logger.debug('reading frame {0}'.format(count))
ret, frame = cam.read()
logger.debug('cropping frame to minimise distortions')
#todo: Crop frame!
if ret:
logger.debug('frame read correctly')
count += 1
if result is not None and result_gry is not None:
frame_gry = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
logger.debug('computing sift features')
keypoints0, descriptors0 = sift.detectAndCompute(result_gry, None)
keypoints1, descriptors1 = sift.detectAndCompute(frame_gry, None)
logger.debug('finding correspondence')
matches = flann.knnMatch(descriptors0, descriptors1, k=args.knn)
positive = []
for match0, match1 in matches:
if match0.distance < args.lowe*match1.distance:
positive.append(match0)
if len(positive) > args.min_correspondence:
src_pts = numpy.array([keypoints0[good_match.queryIdx].pt for good_match in positive], dtype=numpy.float32)
src_pts = src_pts.reshape((-1, 1, 2))
dst_pts = numpy.array([keypoints1[good_match.trainIdx].pt for good_match in positive], dtype=numpy.float32)
dst_pts = dst_pts.reshape((-1, 1, 2))
M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
result = combine.combine_images(frame, result, M)
if args.display and not args.quiet:
scripts.display('result', result)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
else:
logger.warning('too few correspondence points')
else:
result = frame
result_gry = cv2.cvtColor(result, cv2.COLOR_RGB2GRAY)
else:
break
logger.debug('{0} is completed'.format(path))
cam.release()
cv2.destroyAllWindows()
if args.save:
scripts.save_image(path, result)
except Exception as error:
logger.warning('Failed to process {0}'.format(path))
logger.debug('Error msg: {0}'.format(error))
return result
def main():
create_temp_dir()
if len(sys.argv) != 6:
print "usage: python %s lat1 lon1 lat2 lon2 save_image_name" % sys.argv[0]
sys.exit(1)
centers, size = get_centers(*map(float, sys.argv[1:-1]))
logging.info('%d centers generated' % len(centers))
process(centers)
img = combine_images(size)
cv2.imwrite(sys.argv[-1], img)