def match_images(self):
"""
Match images
"""
im = match.ImageMatcher(self.params)
self.matches, self.num_matches, self.interest_points, self.descriptors = im.match_images(
self.images)
def __init__(self,
image_queue,
output_queue,
image_db,
engine_id,
log_flag=True):
super(ApertureServer, self).__init__(image_queue, output_queue,
engine_id)
self.log_flag = log_flag
self.table = image_db
self.matcher = match.ImageMatcher(self.table)
self.prev_match = None
# initialize database (if any)
path = os.path.abspath('db/')
if not os.path.exists(path):
os.makedirs(path)
surf = cv2.xfeatures2d.SURF_create()
db_filelist = [
os.path.join(path, f) for f in os.listdir(path)
if f.lower().endswith("jpeg")
]
for filename in db_filelist:
img = cv2.resize(cv2.imread(filename, 0),
(config.IM_HEIGHT, config.IM_WIDTH))
annotation_img = cv2.resize(
cv2.imread(filename.replace('jpeg', 'png'), -1),
(config.IM_HEIGHT, config.IM_WIDTH))
# Choose betwen color hist and grayscale hist
hist = cv2.calcHist([img], [0], None, [256], [0, 256]) # Grayscale
#hist = cv2.calcHist([img], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256]) # Color
kp, des = surf.detectAndCompute(img, None)
# Store the keypoints, descriptors, hist, image name, and cv image in database
self.table.add_annotation(filename,
kp,
des,
hist,
img,
annotation_img=annotation_img)
def match_images(self): """ Match images """ im=match.ImageMatcher(self.params) self.matches, self.num_matches = im.match_images(self.images)