def preprocess(self, mode="Blue"):
gray = cv2.cvtColor(self.bgr, cv2.COLOR_BGR2GRAY)
if mode == "Blue":
self.mode = "Blue"
self.gray = gray #iicontrast(gray)#contrast(gray)#equalized_image = cv2.equalizeHist(self.gray)
else:
self.mode = "Yellow"
self.gray = 255 - gray
self.DoG = DoG(self.gray) #Difference of Gaussians
self.laplacian = Laplacian(self.gray, needcontrast=False)
self.thr = AdaptiveThreshold(self.laplacian)
self.thr = maskize(self.thr, self.DoG)
def preprocess(self, image):
self.bgr = image
gray = cv2.cvtColor(self.bgr, cv2.COLOR_BGR2GRAY)
self.gray = icontrast(255 - gray)
self.laplacian = Laplacian(gray)
#self.sobel = Sobel(gray)
#self.entropy = Entropy(gray)
#self.garbor = Garbor(gray)
self.DoG = DoG(gray)
self.lthr = AdaptiveThreshold(self.laplacian)
self.tophat = tophatmask(gray)
#tophatblackhat(gray)
masks = []
#masks.append(self.tophat)
masks.append(self.DoG)
self.compose = maskize(self.lthr, masks)
self.contour = np.zeros((self.compose.shape[:2]), np.uint8)