def match(self):
input_stamp, input_img = self.img_sub.stamp, self.img_sub.img
input_features = self.query_features
reference_img = self.reference_sub.img
reference_features = imgsift_client(reference_img)
matches = self.find_match(input_features.descriptors,
reference_features.descriptors)
rospy.loginfo('matches: {}'.format(len(matches)))
# prepare output img
matched_img = drawMatches(input_img, input_features.positions,
reference_img, reference_features.positions,
matches)
cv2.putText(matched_img, 'matches: {}'.format(len(matches)),
(5, 25), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255))
self.publish_img(stamp=input_stamp, img=matched_img)
def match(self):
input_stamp, input_img = self.img_sub.stamp, self.img_sub.img
input_features = self.query_features
reference_img = self.reference_sub.img
reference_features = imgsift_client(reference_img)
matches = self.find_match(input_features.descriptors,
reference_features.descriptors)
rospy.loginfo('matches: {}'.format(len(matches)))
# prepare output img
matched_img = drawMatches(input_img, input_features.positions,
reference_img, reference_features.positions,
matches)
cv2.putText(matched_img, 'matches: {}'.format(len(matches)), (5, 25),
cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255))
self.publish_img(stamp=input_stamp, img=matched_img)
def extract_sift(obj_name):
"""Extract sift data from object images"""
positions = []
descriptors = []
data_dir = rospy.get_param('~train_data', None)
only_appropriate = rospy.get_param('~only_appropriate', True)
with_mask = rospy.get_param('~with_mask', True)
train_imgs = get_train_imgs(obj_name=obj_name,
data_dir=data_dir,
only_appropriate=only_appropriate,
with_mask=with_mask)
for train_img in train_imgs:
train_features = imgsift_client(train_img)
train_pos = np.array(train_features.positions)
train_des = np.array(train_features.descriptors)
positions.append(train_pos)
descriptors.append(train_des)
if len(positions) == 0 or len(descriptors) == 0:
rospy.logerr('no images found: {0}'.format(obj_name))
return
positions, descriptors = map(np.array, [positions, descriptors])
siftdata = dict(positions=positions, descriptors=descriptors)
# save sift data
save_siftdata(obj_name, siftdata)
