def from_pic(self):
self.thread_run = False
self.pic_path = askopenfilename(title="选择识别图片", filetypes=[("jpg图片", "*.jpg")])
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
r, roi, color = self.predictor.predict(img_bgr)
self.show_roi(r, roi, color)
def from_pic(self):
self.thread_run = False
self.pic_path = askopenfilename(title="选择识别图片",
filetypes=[("jpg图片", "*.jpg")])
if self.pic_path:
with open('pathpic.txt', 'w') as f:
f.write(str(self.pic_path))
img_bgr = predict.imreadex(self.pic_path)
self.imgtk1 = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk1)
def cutlicen(self):
print(self.pic_path)
os.system(
'python /Users/wangxin/PycharmProjects/ParkingPaymentSystem/recoginzer_licenseplate.py'
)
time.sleep(2)
picpath = '/Users/wangxin/PycharmProjects/ParkingPaymentSystem/test_images/cut.png'
if os.path.exists(picpath):
img_bgr = predict.imreadex(picpath)
self.imgtk2 = self.get_imgtk(img_bgr)
self.roi_ctl.configure(image=self.imgtk2)
def get_value(self):
global imgurl
print(imgurl)
self.thread_run = False
self.pic_path = imgurl
print(self.pic_path)
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
r, roi, color = self.predictor.predict(img_bgr)
# print(roi)
return roi
def from_pic(self):
self.thread_run = False
self.pic_path = tkFileDialog.askopenfilename(title="选择识别图片",
filetypes=[("jpg图片",
"*.jpg")])
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
r, roi, color = self.predictor.predict(img_bgr)
self.show_roi(
'{0[0]}{0[1]}{0[2]}{0[3]}{0[4]}{0[5]}{0[6]}'.format(r), roi,
color)
def from_pic(self):
try:
self.thread_run = False
self.pic_path = askopenfilename(title="选择识别图片",
filetypes=[("jpg图片", "*.jpg")])
print(self.pic_path)
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
r, roi, color = self.predictor.predict(img_bgr)
# print(roi)
self.show_roi(r, roi, color)
except ():
tk.messagebox.showwarning('错误', '图片无法识别！')
def from_pic(self):
self.thread_run = False
self.pic_path = askopenfilename(title="选择识别图片",
filetypes=[("jpg图片", "*.jpg")])
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
resize_rates = (1, 0.8, 0.6, 0.5, 0.4)
for resize_rate in resize_rates:
print("resize_rate:", resize_rate)
r, roi, color = self.predictor.predict(img_bgr, resize_rate)
if r:
break
#r, roi, color = self.predictor.predict(img_bgr, 1)
self.show_roi(r, roi, color)
def from_folder(self):
self.pic_path = askopenfilename(title="选择待识别图片",
filetypes=[("jpg图片", "*.jpg")])
#如果图片打开成功
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
#显示图片
self.image_ctl.configure(image=self.imgtk)
#对图片进行处理，得到
r, roi, color = self.predictor.predict(img_bgr)
#显示分割出来的车牌
self.show_roi(r, roi, color)
def from_pic(self):
self.thread_run = False
self.send_signn = 0
self.pic_path = askopenfilename(title="选择识别图片",
filetypes=[("jpg图片", "*.jpg"),
("png图片", "*.png")])
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
r, roi = self.predictor.predict(img_bgr)
total_port_num = 0
for singleline in r:
if (singleline.isdigit()):
slot_port_num = int(singleline)
total_port_num = total_port_num * 10 + slot_port_num
self.show_roi(total_port_num, roi)
def from_pic(self):
self.thread_run = False
self.pic_path = askopenfilename(title="选择识别图片",
filetypes=[("jpg图片", "*.jpg")])
if self.pic_path:
img_bgr = predict.imreadex(self.pic_path)
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
r, roi, color = self.predictor.predict(img_bgr)
self.show_roi(r, roi, color)
def vedio_thread(self):
self.thread_run = True
predict_time = time.time()
while self.thread_run:
_, img_bgr = self.camera.read()
self.imgtk = self.get_imgtk(img_bgr)
self.image_ctl.configure(image=self.imgtk)
if time.time() - predict_time > 2:
r, roi, color = self.predictor.predict(img_bgr)
self.show_roi(r, roi, color)
predict_time = time.time()
print("run end")
