def __init__(self):
self.model = pr.LPR("model/cascade.xml", "model/model12.h5", "model/ocr_plate_all_gru.h5")
print('init')
pass
self.__nicknames[user_id] = None
f.close()
if has_receive == filesize:
print('\n[Server] successfully received!')
connection.sendall(
json.dumps('[Server] successfuly received the file!').encode(
'utf-8'))
# start processing file, send the processing time to client
proc_results, proc_time = SpeedTest(
os.path.join(RECV_FOLDER, filename))
proc_result_info = {
'proc_results': proc_results,
'proc_time': proc_time
}
connection.sendall(json.dumps(proc_result_info).encode("utf-8"))
# 处理完关闭当前连接
# self.__connections[user_id].close()
# del self.__connections[user_id]
# del self.__nicknames[user_id]
if __name__ == '__main__':
# 打开图像处理模型，并一直开着
model = pr.LPR("model/cascade.xml", "model/model12.h5",
"model/ocr_plate_all_gru.h5")
server = Server()
server.start()
def init():
global model
print('目录:', BASE_PATH)
model = pr.LPR(os.path.join(BASE_PATH, "model", "cascade.xml"),
os.path.join(BASE_PATH, "model", "model12.h5"),
os.path.join(BASE_PATH, "model", "ocr_plate_all_gru.h5"))
parser.add_argument('--cascade_model_path',
action='store',
default='model/cascade.xml')
parser.add_argument('--mapping_vertical_model_path',
action='store',
default='model/model12.h5')
parser.add_argument('--ocr_plate_model_path',
action='store',
default='model/ocr_plate_all_gru.h5')
parser.add_argument('--save_result_flag', action='store', default='True')
parser.add_argument('--plot_result_flag', action='store', default='True')
parser.add_argument('--save_path', action='store', default=None)
args = parser.parse_args()
model = pr.LPR(args.cascade_model_path, args.mapping_vertical_model_path,
args.ocr_plate_model_path)
for filename in os.listdir(args.detect_parent_path):
path = os.path.join(args.detect_parent_path, filename)
if path.endswith(".jpg") or path.endswith(".png"):
grr = cv2.imread(path)
t0 = time.time()
image = grr
for pstr, confidence, rect in model.SimpleRecognizePlateByE2E(grr):
if confidence > 0.7:
image = drawRectBox(image, rect,
pstr + " " + str(round(confidence, 3)))
print("plate_str:")
print(pstr)
print("plate_confidence")
print(confidence)
addText, (255, 255, 255),
font=fontC)
imagex = np.array(img)
return imagex
import HyperLPRLite as pr
import cv2
import numpy as np
SpeedTest("images_rec/2_resized.jpg")
img = Image.open("images_rec/1_resized.jpg")
model = pr.LPR("export_graph/edgetpu_models/detection_model_edgetpu.tflite",
"export_graph/model12.h5",
"export_graph/edgetpu_models/ocr_model_edgetpu.tflite",
cnn=True,
tpu=True)
for pstr, confidence, rect in model.SimpleRecognizePlateByE2E(img):
#if confidence>0.1:
image = drawRectBox(cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR), rect,
pstr + " " + str(round(confidence, 3)))
print("plate_str:")
print(pstr)
print("plate_confidence")
print(confidence)
cv2.imshow("image", image)
cv2.waitKey(0)
cv2.destroyAllWindows()
(int(rect[0] + rect[2]), int(rect[1] + rect[3])),
(0, 0, 255), 2, cv2.LINE_AA)
cv2.rectangle(image, (int(rect[0] - 1), int(rect[1]) - 16),
(int(rect[0] + 115), int(rect[1])), (0, 0, 255), -1,
cv2.LINE_AA)
img = Image.fromarray(image)
draw = ImageDraw.Draw(img)
draw.text((int(rect[0] + 1), int(rect[1] - 16)),
addText, (255, 255, 255),
font=fontC)
imagex = np.array(img)
return imagex
model = pr.LPR(os.path.join(BASE_PATH, "model/cascade.xml"),
os.path.join(BASE_PATH, "model/model12.h5"),
os.path.join(BASE_PATH, "model/ocr_plate_all_gru.h5"))
# SpeedTest("images_rec/2.jpg")
def demo():
grr = cv2.imread(os.path.join(BASE_PATH, "images_rec/1.jpg"))
for pstr, confidence, rect in model.SimpleRecognizePlateByE2E(grr):
if confidence > 0.7:
# image = drawRectBox(grr, rect, pstr+" " +
# str(round(confidence, 3)))
print("plate_str:")
print(pstr)
print("plate_confidence")
print(confidence)
cv2.LINE_AA)
img = Image.fromarray(image)
draw = ImageDraw.Draw(img)
draw.text((int(rect[0]+1), int(rect[1]-16)), addText.decode("utf-8"), (255, 255, 255), font=fontC)
imagex = np.array(img)
return imagex
import HyperLPRLite as pr
import cv2
import numpy as np
grr = cv2.imread("images_rec/21jk.jpg")
model = pr.LPR("model/cascade_lbp.xml","model/model12.h5","model/model.h5")
for pstr,confidence,rect in model.SimpleRecognizePlateByE2E(grr):
if confidence>0.7:
image = drawRectBox(grr, rect, pstr+" "+str(round(confidence,3)))
print ("plate_str:")
print (pstr)
print ("plate_confidence")
print (confidence)
print ("plate_borders:")
print (rect)
cv2.imshow("image",image)
cv2.waitKey(0)