def handle_image():
content = request.get_json(force=True)
time = content['time']
post_img = content['img'][0]
img_name = str(str(time) + str(random.randint(0, 65535)))
# img_name = '1'
img = open(locate + img_name + '.jpg', 'wb')
# img = open('q.jpg','wb')
img_temp = base64.b64decode(post_img)
img.write(img_temp)
address = content['address']
# plate = readImg.read_img()
import hyperlpr.pipline as pp
import cv2
read_img = cv2.imread(locate + img_name + '.jpg')
plate_temp = pp.SimpleRecognizePlate(read_img)
# print plate
plate = '识别失败'
if plate != None and plate != []:
plate = plate_temp[0]
user = User(img=img_name + '.jpg',
type=1,
time=time,
address=address,
plate=plate)
db.session.add(user)
db.session.commit()
search_res = User.query.filter_by(address=address, time=time).first()
id = search_res.id
address = search_res.address
img = "http://101.132.144.11/getImg/" + img_name
time = search_res.time
img.close()
#失败之后对图片进行删除
# count = search(plate)
if plate != '识别失败':
result = jsonify({
'res': 'success',
'address': address,
'time': time,
'plate': plate,
'id': id,
'img': img
})
else:
result = jsonify({
'res': 'fail',
'address': address,
'time': time,
'plate': plate,
'id': id,
'img': img
})
return result
def recognize(self):
self.timer.stop()
from hyperlpr import pipline as pp
cv2.imshow('i', self.frame_)
cv2.waitKey()
_, res = pp.SimpleRecognizePlate(self.frame_)
if not len(res):
res.append('无效的图片')
item = QStandardItem(res[0])
self.model_t.setItem(self.i, 0, item)
self.i += 1
def recognize_0(self):
_, res = pp.SimpleRecognizePlate(self.frame_)
if not len(res):
# res.append('无效的图片')
return
value = self.model_t.data(self.model_t.index(self.i - 1, 0))
if value == res[0]:
return
item = QStandardItem(res[0])
self.model_t.setItem(self.i, 0, item)
self.i += 1
def start_check(self, file):
image = cv2.imread(file)
image, res = pp.SimpleRecognizePlate(image)
try:
self.ui.label.setText(res[0])
except Exception as e:
self.ui.plainTextEdit.appendPlainText('抱歉，未检测到车牌...')
self.ui.plainTextEdit.appendPlainText('---------------------------')
return e
self.ui.label.adjustSize()
check_res = self.sql_tools.check_plate(res[0])
print(check_res)
if check_res[0]:
if check_res[1][4] == '0':
now_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
self.ui.plainTextEdit.appendPlainText('车牌号:{}\n进入时间:{}'.format(check_res[1][1], now_time))
self.sql_tools.update_intime_plate_info(now_time, check_res[1][0])
self.ui.plainTextEdit.appendPlainText('匹配成功，正在下发抬杆指令...')
self.open_the_door()
time.sleep(0.01)
self.ui.plainTextEdit.appendPlainText('下发成功，正在抬杆')
self.ui.plainTextEdit.appendPlainText('---------------------------')
elif check_res[1][4] == '1':
now_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
in_time = time.mktime(time.strptime(check_res[1][2], "%Y-%m-%d %H:%M:%S"))
out_time = time.mktime(time.strptime(now_time, "%Y-%m-%d %H:%M:%S"))
self.ui.plainTextEdit.appendPlainText('车牌号:{}\n进入时间:{}'.format(check_res[1][1], check_res[1][2]))
self.ui.plainTextEdit.appendPlainText('驶出时间:{}'.format(now_time))
stop_time = out_time - in_time
stop_time_day = int(stop_time / 86400)
stop_time_hour = int((stop_time % 86400) / 3600)
stop_time_min = int(((stop_time % 86400) % 3600) / 60)
str_stop_time = "已停车{}天{}时{}分，请缴费{}元".format(stop_time_day, stop_time_hour, stop_time_min, 2)
self.ui.plainTextEdit.appendPlainText(str_stop_time)
self.ui.plainTextEdit.appendPlainText('欢迎再次光临，正在下发抬杆指令...')
self.open_the_door()
time.sleep(0.01)
self.ui.plainTextEdit.appendPlainText('下发成功，正在抬杆')
self.ui.plainTextEdit.appendPlainText('---------------------------')
self.sql_tools.update_outime_plate_info(now_time, check_res[1][0])
else:
self.ui.plainTextEdit.appendPlainText('外来车辆，不予抬杆...')
self.ui.plainTextEdit.appendPlainText('---------------------------')
for filename in os.listdir(parent):
path = os.path.join(parent, filename)
print path
if path.endswith(".jpg") or path.endswith(".png"):
ics, name = os.path.split(path)
name, ext = name.split(".")
image = cv2.imread(path)
image = image[roi[1]:roi[1] + roi[3], roi[0]:roi[0] + roi[2]]
# cv2.imshow("test",image)
# cv2.waitKey(0)
info, dataset = pp.SimpleRecognizePlate(image)
ext = ext.strip()
name = name.strip()
if len(dataset) == 0:
count_undetected += 1
# cv2.imwrite("./cache/bad2/" + name + ".png", image)
for one in dataset:
# p = sm.StringMatcher(seq1=one.encode("utf-8"),seq2=name.encode("utf-8"))
A = one.encode("utf-8")
B = name.encode("utf-8")
print one.encode("utf-8"), "<->", name.encode(
"utf-8"), "编辑距离:", comparestring(A, B)
from hyperlpr import pipline
import cv2
# image1 = cv2.imread("./dataset/0.jpg")
# image2 = cv2.imread("./dataset/1.jpg")
# image3 = cv2.imread("./dataset/5.jpg")
# image4 = cv2.imread("./dataset/6.jpg")
image5 = cv2.imread("./dataset/3144391.png")
#
# pipline.SimpleRecognizePlate(image4)
# pipline.SimpleRecognizePlate(image3)
pipline.SimpleRecognizePlate(image5)
from hyperlpr import pipline as pp
import cv2
import h5py
image = cv2.imread("6.jpg")
image, res = pp.SimpleRecognizePlate(image)
