def find_contours(cls, image, threshold=THRESHOLD):
image_gray = utils.BGR_to_gray(image)
ret, thresh = cv2.threshold(image_gray, threshold, 255, 0)
base_contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
# base_contours = [utils.approx_contour(cnt) for cnt in base_contours]
contours = []
for contour in base_contours:
area = cv2.contourArea(contour)
mask = utils.mask_from_contour_points(image, contour)
color = cv2.mean(image, mask=mask)
perimeter = cv2.arcLength(contour, True)
M = cv2.moments(contour)
try:
centroid_x = int(M['m10']/M['m00'])
centroid_y = int(M['m01']/M['m00'])
contours.append(Contour(contour, color, centroid_x, centroid_y, area, perimeter))
except ZeroDivisionError:
pass
return contours
def mask_image(self, image):
mask = utils.mask_from_contour_points(image, self.points)
return utils.apply_mask(image, mask)
