def __init__(self, image_folder, filterchain):
self.image_folder = ImageFolder()
self.image_folder.return_file_name = True
self.image_folder.read_folder(image_folder)
self.chain = chain.read(filterchain)
self.precisions = {}
self.noises = {}
class LineTest:
def __init__(self, image_folder, filterchain):
self.image_folder = ImageFolder()
self.image_folder.return_file_name = True
self.image_folder.read_folder(image_folder)
self.chain = chain.read(filterchain)
self.precisions = {}
self.noises = {}
def launch(self):
for file_name, image in self.image_folder:
if os.path.exists(file_name + '.map'):
filtered = self.chain.execute(image)
filtered = self.make_binary_array(filtered)
map = np.fromfile(file_name + '.map', dtype=np.uint8)
map = map.reshape(filtered.shape)
self.precisions[file_name] = self.find_precision(filtered, map)
self.noises[file_name] = self.find_noise(filtered, map)
def make_binary_array(self, filtered):
gray = cv2.cvtColor(filtered, cv.CV_BGR2GRAY)
bin = np.zeros(gray.shape, dtype=np.uint8)
bin[gray > 0] = 255
return bin
def find_precision(self, filtered, map):
undetected = (filtered & np.invert(map))
sum_map = np.count_nonzero(map)
sum_undetected = np.count_nonzero(undetected)
return (sum_map - sum_undetected) / float(sum_map)
def remove_line(self, filtered, map):
detected = (filtered & map)
return (filtered & np.invert(detected))
def find_noise(self, filtered, map):
filtered = self.remove_line(filtered, map)
cnt_filtered, _ = cv2.findContours(filtered,
cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
cnt_map, _ = cv2.findContours(map,
cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
noise = 0
for cf in cnt_filtered:
dist = abs(self.find_dist_between_blob_and_line(cf, cnt_map))
area = np.abs(cv2.contourArea(cf))
noise += dist * area
return noise / self.max_noise(cnt_map, filtered.shape)
def max_noise(self, cnt_map, image_size):
max_dist = math.sqrt(image_size[0]**2 + image_size[1]**2) / 4.0
max_noise = 0
for cm in cnt_map:
area = np.abs(cv2.contourArea(cm)) / 2.0
max_noise += area * max_dist
return max_noise
def find_dist_between_blob_and_line(self, cf, cnt_map):
moment = cv2.moments(cf)
m00 = moment['m00']
if m00 <> 0:
x = int(moment['m10'] / m00)
y = int(moment['m01'] / m00)
else:
x = cf[0][0][0]
y = cf[0][0][1]
min_dist = sys.maxint
for cm in cnt_map:
dist = cv2.pointPolygonTest(cm, (x, y), True)
if dist < min_dist:
min_dist = dist
return min_dist
def total_images(self):
count = 0
for f in self.image_folder.file_names:
map = f + '.map'
if os.path.exists(map):
count += 1
return count
def avg_noise(self):
c = len(self.noises.values())
s = sum(self.noises.values())
return s / c
def avg_precision(self):
c = len(self.precisions.values())
s = sum(self.precisions.values())
return s / c