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")