def run(self):
try:
matcher = DescriptorMatcher(self.__descriptor_set1, self.__descriptor_set2)
matcher.match()
self.__feature_matches = matcher.get_feature_matches()
except Exception as error:
logger.exception(error)
def align_images(img1, img2, threshold):
descriptors1 = SURFDetector.extract_features(img1, threshold)
descriptors2 = SURFDetector.extract_features(img2, threshold)
matcher = DescriptorMatcher(descriptors1, descriptors2)
matcher.match()
estimator = RansacHomographyEstimator.create_for_matches(matcher.get_feature_matches())
estimator.estimate()
homography = estimator.homography
print homography
np.save('D:\\test\\test2\\ololo.txt', homography)
def run(self):
try:
matcher = DescriptorMatcher(self.__descriptor_set1, self.__descriptor_set2)
matcher.match()
estimator = RansacHomographyEstimator.create_for_matcher(matcher)
estimator.estimate()
self.__homography = estimator.homography
self.__inliers = estimator.inliers
except Exception as error:
logger.exception(error)
def stitch(img1, img2):
descriptors1 = SURFDetector.extract_features(img1)
descriptors2 = SURFDetector.extract_features(img2)
matcher = DescriptorMatcher(descriptors1, descriptors2)
matcher.match()
estimator = RansacHomographyEstimator.create_for_matches(matcher.get_feature_matches())
estimator.estimate()
homography = estimator.homography
h1, w1 = img1.shape[0], img1.shape[1]
w2 = img2.shape[1]
dsize = (w1 + w2, h1)
inv_homography = np.linalg.inv(homography)
warped_img2 = cv2.warpPerspective(img2, inv_homography, dsize)
panorama = blending.pyramid_blending(img1, warped_img2, 5)
return imgtools.crop_panorama(panorama)
