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="", pady="")
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',''))
self.r_ctl.grid(column=0, row=3, sticky=tk.W)
self.color_ctl = ttk.Label(frame_right1, text="", width="")
self.color_ctl.grid(column=0, row=4, sticky=tk.W)
from_vedio_ctl.pack(anchor="se", pady="")
from_pic_ctl.pack(anchor="se", pady="")
from_img_pre.pack(anchor="se", pady="") 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',''))
self.r_ct2.grid(column=0, row=8, sticky=tk.W)
self.color_ct2 = ttk.Label(frame_right1, text="", width="")
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()