主要代码参考https://blog.csdn.net/wzh191920/article/details/79589506
GitHub：https://github.com/yinghualuowu
答辩通过了，补完~
这里主要是用两种方法进行定位识别
# -*- coding: utf-8 -*- __author__ = '樱花落舞' import tkinter as tk from tkinter.filedialog import * from tkinter import ttk import img_function as predict import cv2 from PIL import Image, ImageTk import threading import time import img_math import traceback import debug import config from threading import Thread class ThreadWithReturnValue(Thread): def __init__(self, group=None, target=None, name=None, args=(), kwargs=None, *, daemon=None): Thread.__init__(self, group, target, name, args, kwargs, daemon=daemon) self._return1 = None self._return2 = None self._return3 = None def run(self): if self._target is not None: self._return1,self._return2,self._return3 = self._target(*self._args, **self._kwargs) def join(self): Thread.join(self) return self._return1,self._return2,self._return3 class Surface(ttk.Frame): pic_path = "" viewhigh = 600 viewwide = 600 update_time = 0 thread = None thread_run = False camera = None color_transform = {"green": ("绿牌", "#55FF55"), "yello": ("黄牌", "#FFFF00"), "blue": ("蓝牌", "#6666FF")} def __init__(self, win): ttk.Frame.__init__(self, win) frame_left = ttk.Frame(self) frame_right1 = ttk.Frame(self) frame_right2 = ttk.Frame(self) win.title("车牌识别") win.state("zoomed") self.pack(fill=tk.BOTH, expand=tk.YES, padx="10", pady="10") frame_left.pack(side=LEFT, expand=1, fill=BOTH) frame_right1.pack(side=TOP, expand=1, fill=tk.Y) frame_right2.pack(side=RIGHT, expand=0) ttk.Label(frame_left, text='原图：').pack(anchor="nw") ttk.Label(frame_right1, text='形状定位车牌位置：').grid(column=0, row=0, sticky=tk.W) from_pic_ctl = ttk.Button(frame_right2, text="来自图片", width=20, command=self.from_pic) from_vedio_ctl = ttk.Button(frame_right2, text="来自摄像头", width=20, command=self.from_vedio) from_img_pre = ttk.Button(frame_right2, text="查看形状预处理图像", width=20,command = self.show_img_pre) self.image_ctl = ttk.Label(frame_left) self.image_ctl.pack(anchor="nw") self.roi_ctl = ttk.Label(frame_right1) self.roi_ctl.grid(column=0, row=1, sticky=tk.W) ttk.Label(frame_right1, text='形状定位识别结果：').grid(column=0, row=2, sticky=tk.W) self.r_ctl = ttk.Label(frame_right1, text="",font=('Times','20')) self.r_ctl.grid(column=0, row=3, sticky=tk.W) self.color_ctl = ttk.Label(frame_right1, text="", width="20") self.color_ctl.grid(column=0, row=4, sticky=tk.W) from_vedio_ctl.pack(anchor="se", pady="5") from_pic_ctl.pack(anchor="se", pady="5") from_img_pre.pack(anchor="se", pady="5") ttk.Label(frame_right1, text='颜色定位车牌位置：').grid(column=0, row=5, sticky=tk.W) self.roi_ct2 = ttk.Label(frame_right1) self.roi_ct2.grid(column=0, row=6, sticky=tk.W) ttk.Label(frame_right1, text='颜色定位识别结果：').grid(column=0, row=7, sticky=tk.W) self.r_ct2 = ttk.Label(frame_right1, text="",font=('Times','20')) self.r_ct2.grid(column=0, row=8, sticky=tk.W) self.color_ct2 = ttk.Label(frame_right1, text="", width="20") self.color_ct2.grid(column=0, row=9, sticky=tk.W) self.predictor = predict.CardPredictor() self.predictor.train_svm() def get_imgtk(self, img_bgr): img = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB) im = Image.fromarray(img) imgtk = ImageTk.PhotoImage(image=im) wide = imgtk.width() high = imgtk.height() if wide > self.viewwide or high > self.viewhigh: wide_factor = self.viewwide / wide high_factor = self.viewhigh / high factor = min(wide_factor, high_factor) wide = int(wide * factor) if wide <= 0: wide = 1 high = int(high * factor) if high <= 0: high = 1 im = im.resize((wide, high), Image.ANTIALIAS) imgtk = ImageTk.PhotoImage(image=im) return imgtk def show_roi1(self, r, roi, color): if r: roi = cv2.cvtColor(roi, cv2.COLOR_BGR2RGB) roi = Image.fromarray(roi) self.imgtk_roi = ImageTk.PhotoImage(image=roi) self.roi_ctl.configure(image=self.imgtk_roi, state='enable') self.r_ctl.configure(text=str(r)) self.update_time = time.time() try: c = self.color_transform[color] self.color_ctl.configure(text=c[0], background=c[1], state='enable') except: self.color_ctl.configure(state='disabled') elif self.update_time + 8 < time.time(): self.roi_ctl.configure(state='disabled') self.r_ctl.configure(text="") self.color_ctl.configure(state='disabled') def show_roi2(self, r, roi, color): if r: roi = cv2.cvtColor(roi, cv2.COLOR_BGR2RGB) roi = Image.fromarray(roi) self.imgtk_roi = ImageTk.PhotoImage(image=roi) self.roi_ct2.configure(image=self.imgtk_roi, state='enable') self.r_ct2.configure(text=str(r)) self.update_time = time.time() try: c = self.color_transform[color] self.color_ct2.configure(text=c[0], background=c[1], state='enable') except: self.color_ct2.configure(state='disabled') elif self.update_time + 8 < time.time(): self.roi_ct2.configure(state='disabled') self.r_ct2.configure(text="") self.color_ct2.configure(state='disabled') def show_img_pre(self): filename = config.get_name() if filename.any() == True: debug.img_show(filename) def from_vedio(self): if self.thread_run: return if self.camera is None: self.camera = cv2.VideoCapture(0) if not self.camera.isOpened(): mBox.showwarning('警告', '摄像头打开失败！') self.camera = None return self.thread = threading.Thread(target=self.vedio_thread, args=(self,)) self.thread.setDaemon(True) self.thread.start() self.thread_run = True def from_pic(self): self.thread_run = False 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 = img_math.img_read(self.pic_path) first_img, oldimg = self.predictor.img_first_pre(img_bgr) self.imgtk = self.get_imgtk(img_bgr) self.image_ctl.configure(image=self.imgtk) th1 = ThreadWithReturnValue(target=self.predictor.img_color_contours,args=(first_img,oldimg)) th2 = ThreadWithReturnValue(target=self.predictor.img_only_color,args=(oldimg,oldimg,first_img)) th1.start() th2.start() r_c, roi_c, color_c = th1.join() r_color,roi_color,color_color = th2.join() print(r_c,r_color) self.show_roi2(r_color, roi_color, color_color) self.show_roi1(r_c, roi_c, color_c) @staticmethod 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(img_bgr) self.show_roi(r, roi, color) predict_time = time.time() print("run end") def close_window(): print("destroy") if surface.thread_run: surface.thread_run = False surface.thread.join(2.0) win.destroy() if __name__ == '__main__': win = tk.Tk() surface = Surface(win) # close,退出输出destroy win.protocol('WM_DELETE_WINDOW', close_window) # 进入消息循环 win.mainloop()
