def get_plate(wpod_net,image, Dmax=650, Dmin=270):
vehicle = image
ratio = float(max(vehicle.shape[:2])) / min(vehicle.shape[:2])
side = int(ratio * Dmin)
bound_dim = min(side, Dmax)
_ , LpImg, _, cor = detect_lp(wpod_net, vehicle, bound_dim, lp_threshold=0.5)
return vehicle,LpImg, cor
def get_plate(image_path, Dmax=608, Dmin = 608):
vehicle = preprocess_image(image_path)
ratio = float(max(vehicle.shape[:2])) / min(vehicle.shape[:2])
side = int(ratio * Dmin)
bound_dim = min(side, Dmax)
_ , LpImg, _, cor = detect_lp(wpod_net, vehicle, bound_dim, lp_threshold=0.5)
return vehicle, LpImg, cor
def __getPlate(self, image, Dmax=608, Dmin=608):
with self.graph.as_default():
set_session(self.sess)
car = self.__changeImage(image)
ratio = float(max(car.shape[:2])) / min(car.shape[:2])
side = int(ratio * Dmin)
bound_dim = min(side, Dmax)
_, LpImg, _, cor = detect_lp(self.model,
car,
bound_dim,
lp_threshold=0.5)
return car, LpImg, cor
try:
vid = cv2.VideoCapture(int(video_path))
except:
vid = cv2.VideoCapture(video_path)
while True:
return_value, frame = vid.read()
if return_value:
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
vehicle = frame / 255
ratio = float(max(vehicle.shape[:2])) / min(vehicle.shape[:2])
side = int(ratio * Dmin)
bound_dim = min(side, Dmax)
_, LpImg, _, cor = detect_lp(wpod_net,
vehicle,
bound_dim,
lp_threshold=0.5)
plate_image = cv2.convertScaleAbs(LpImg[0], alpha=(255.0))
# conver to grayscale
gray = cv2.cvtColor(plate_image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (7, 7), 0)
#Applied inversed thresh_binary where the pixel value less than threshold will be converted to 255 and vice versa
binary = cv2.threshold(blur, 180, 255,
cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
## Applied dilation
kernel3 = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
thre_mor = cv2.morphologyEx(binary, cv2.MORPH_DILATE, kernel3)
