def __init__(self):
print("------- Initial E2E")
self.image = np.empty((28, 28, 1))
self.detectLP = detectNumberPlate()
print("------- Loaded detectNumberPlate model")
self.detect_vehicle = DetectVehicle(threshold=0.5)
# self.recogChar = CNN_Model(trainable=False).model
# self.recogChar.load_weights('./weights/original_weight.h5')
# print ("------- Loaded recogChar model")
self.candidates = []
self.prev_candidates = dict()
# print("------- Before load VehicleDetection")
# self.vehicle_detection = VehicleDetection()
# print("------- After load VehicleDetection")
print("------- Before load LicensePlateDetection")
self.license_plate_detection = LicensePlateDetection()
print("------- After load LicensePlateDetection")
print("------- Before load OCR")
self.ocr = OCR(ocr_threshold=0.1)
print("------- After load OCR")
print("------- Before load GenOutput")
self.gen_output = GenOutput()
print("------- After load GenOutput")
def __init__(self):
self.image = np.empty((28, 28, 1))
self.detectLP = detectNumberPlate()
self.recogChar = CNN_Model(trainable=False).model
self.recogChar.load_weights('./weights/weight.h5')
self.candidates = []
self.preLpCnt = None
def save_a_img(link_img, output):
model = detectNumberPlate()
file_name = os.path.basename(link_img)
img = cv2.imread(link_img)
coordinates = model.detect(img)
for coordinate in coordinates:
pts = order_points(coordinate)
ls_region = perspective.four_point_transform(img, pts)
cv2.imwrite(os.path.join(output, file_name), ls_region)
return ls_region
def save_img(data_dir, output_dir):
model = detectNumberPlate() #initizial class to detect image
list_file = glob.glob(data_dir + "/*.jpg") #take list file
for file in list_file: #take each file in list file
file_name = os.path.basename(file) #name file match with list file original
img = cv2.imread(file) #read file
coordinates = model.detect(img) #detect file
for coordinate in coordinates: # detect license plate by yolov3
# candidates = []
# convert (x_min, y_min, width, height) to coordinate(top left, top right, bottom left, bottom right)
pts = order_points(coordinate)
# crop number plate used by bird's eyes view transformation
lp_region = perspective.four_point_transform(img, pts)
cv2.imwrite(os.path.join(output_dir, file_name), lp_region)