def __init__(self, win):
ttk.Frame.__init__(self, win)
# win.title("车牌识别系统")
# win.geometry('+300+200')
# win.minsize(UI_main.width,UI_main.height)
# win.configure(relief=tk.RIDGE)
# win.update()
self.pack(fill=tk.BOTH)
frame_left = ttk.Frame(self)
frame_right_1 = ttk.Frame(self)
frame_right_2 = ttk.Frame(self)
frame_left.pack(side=tk.LEFT, expand=1, fill=tk.BOTH)
frame_right_1.pack(side=tk.TOP, expand=1, fill=tk.Y)
frame_right_2.pack()
#界面左边 --->车牌识别主界面大图片
self.image_ctl = ttk.Label(frame_left)
self.image_ctl.pack()
#界面右边 --->定位车牌位置、识别结果
# ttk.Label(frame_right_1, text='定位车牌：', font=('Times', '14')).grid(
# column=0, row=6, sticky=tk.NW)
self.roi_ct2 = ttk.Label(frame_right_1)
self.roi_ct2.grid(column=0, row=7, sticky=tk.W, pady=5)
# ttk.Label(frame_right_1, text='识别结果：', font=('Times', '14')).grid(
# column=0, row=8, sticky=tk.W,pady=5)
self.r_ct2 = ttk.Label(frame_right_1, text="", font=('Times', '20'))
# self.r_ct2.grid(column=0, row=9, sticky=tk.W,pady=5)
#车牌颜色
self.color_ct2 = ttk.Label(frame_right_1,
background=self.colorimg,
text="",
width="4",
font=('Times', '14'))
# self.color_ct2.grid(column=0, row=10, sticky=tk.W)
#界面右下角
from_pic_ctl = ttk.Button(frame_right_2,
text="车牌图片",
width=20,
command=self.from_pic)
from_pic_ctl.grid(column=0, row=1)
#
# #清除识别数据
# from_pic_chu = ttk.Button(
# frame_right_2, text="清除识别数据", width=20, command=self.clean)
# from_pic_chu.grid(column=0, row=2)
# #查看图像处理过程
# from_pic_chu = ttk.Button(
# frame_right_2, text="查看图像处理过程", width=20, command=self.pic_chuli)
# from_pic_chu.grid(column=0, row=3)
# self.clean()
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
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 __init__(self):
# 车牌颜色
self.color_ct2 = ttk.Label(background=self.colorimg,
text="",
width="4",
font=('Times', '14'))
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
def __init__(self, win):
ttk.Frame.__init__(self, win)
frame_left = ttk.Frame(self)
frame_right1 = ttk.Frame(self)
frame_right2 = ttk.Frame(self)
top = ttk.Frame(self)
win.title("车牌识别")
win.minsize(850, 700)
# win.wm_attributes('-topmost', 1)
self.center_window()
top.pack(side=TOP, expand=1, fill=tk.Y)
reset_ctl = ttk.Button(top, text="重置窗口", width=10, command=self.reset)
reset_ctl.pack(side=LEFT)
L1 = ttk.Label(top, text='网络地址:')
L1.pack(side=LEFT)
self.p1 = StringVar()
self.user_text = ttk.Entry(top, textvariable=self.p1, width=45)
self.user_text.pack(side=LEFT)
self.user_text.bind('<Key-Return>', self.url_pic2)
url_ctl = ttk.Button(top,
text="识别网络图片",
width=20,
command=self.url_pic)
url_ctl.pack(side=RIGHT)
self.pack(fill=tk.BOTH, expand=tk.YES, padx="10", pady="10")
frame_left.pack(side=LEFT, expand=1)
frame_right1.pack(side=TOP, expand=1, fill=tk.Y)
frame_right2.pack(side=RIGHT, expand=0)
#ttk.Label(frame_left, text='地址：').pack(anchor="nw")
self.image_ctl = ttk.Label(frame_left)
self.image_ctl.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="打开/关闭摄像头",
width=20,
command=self.from_vedio)
from_video_ctl = ttk.Button(frame_right2,
text="拍照并识别",
width=20,
command=self.video_pic)
from_img_pre = ttk.Button(frame_right2,
text="查看预处理图像",
width=20,
command=self.show_img_pre)
clean_ctrl = ttk.Button(frame_right2,
text="清除识别数据",
width=20,
command=self.clean)
exit_ctrl = ttk.Button(frame_right2,
text="api再次识别",
width=20,
command=self.api_ctl)
self.cut_ctrl = ttk.Button(frame_right2,
text="截图识别",
width=20,
command=self.cut_pic)
camera_ctrl = ttk.Button(frame_right2,
text="开关摄像头实时识别(测试)",
width=20,
command=self.camera_flag)
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)
self.cut_ctrl.pack(anchor="se", pady="5")
camera_ctrl.pack(anchor="se", pady="5")
from_vedio_ctl.pack(anchor="se", pady="5")
from_video_ctl.pack(anchor="se", pady="5")
from_pic_ctl.pack(anchor="se", pady="5")
from_img_pre.pack(anchor="se", pady="5")
clean_ctrl.pack(anchor="se", pady="5")
exit_ctrl.pack(anchor="se", pady="5")
ttk.Label(frame_right1,
text='-------------------------------').grid(column=0,
row=5,
sticky=tk.W)
ttk.Label(frame_right1, text='颜色定位车牌位置：').grid(column=0,
row=6,
sticky=tk.W)
self.roi_ct2 = ttk.Label(frame_right1)
self.roi_ct2.grid(column=0, row=7, sticky=tk.W)
ttk.Label(frame_right1, text='颜色定位识别结果：').grid(column=0,
row=8,
sticky=tk.W)
self.r_ct2 = ttk.Label(frame_right1, text="", font=('Times', '20'))
self.r_ct2.grid(column=0, row=9, sticky=tk.W)
self.color_ct2 = ttk.Label(frame_right1, text="", width="20")
self.color_ct2.grid(column=0, row=10, sticky=tk.W)
ttk.Label(frame_right1,
text='-------------------------------').grid(column=0,
row=11,
sticky=tk.W)
self.clean()
self.apistr = None
img_excel.create_excel()
img_sql.create_sql()
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
def __init__(self, win):
ttk.Frame.__init__(self, win)
frame_left = ttk.Frame(self)
frame_right1 = ttk.Frame(self)
frame_right2 = ttk.Frame(self)
# frame作为框架
win.title("车牌识别")
screenwidth = self.winfo_screenwidth()
screenheight = self.winfo_screenheight()
size = '%dx%d+%d+%d' % (950, 700, (screenwidth - 950) / 2, (screenheight - 700) / 2)
# 设置页面大小 居中显示
print(size)
win.geometry(size)
win.minsize(950,700)
self.pack(fill=tk.BOTH, expand=tk.YES, padx="10", pady="10")
# padx是上下对称 pady是左右对齐
# 摆放控件位置
frame_left.pack(side=LEFT, expand=1, fill=BOTH)
# fill是填充样式both是横向纵向都填充 expand 1/yes表示中心 0/no表示不能扩展
# 当side = "left"或side = "right"时，fill = "x"不起作用，只能填充y
# side =“top”, side = "bottom"时，fill = "y"不起作用，只能填充x
# side: 按扭停靠在窗口的哪个位置left: 左 top: 上 right: 右 botton: 下
# fill: 填充 x: 水平方向填充 y: 竖直方向填充 both: 水平和竖直方向填充 none: 不填充
# expand:yes: 扩展整个空白区 no: 不扩展
# anchor: N: 北 下 E: 东 右 S: 南 下 W: 西 左 CENTER: 中间
# padx: x方向的外边距 pady: y方向的外边距 ipadx: x方向的内边距 ipady：y方向的内边距
from_pic_ctl = ttk.Button(frame_right2, text="来自图片", width=20, command=self.from_pic)
from_img_pre = ttk.Button(frame_right2, text="查看形状预处理图像", width=20, command=self.show_img_pre)
from_pic_ctl.pack(anchor="se", pady="5")
from_img_pre.pack(anchor="se", pady="5")
# anchor 可以设置9各参数 表示方向
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")
self.image_ctl = ttk.Label(frame_left)
self.image_ctl.pack(anchor="nw")
# 图片展示
ttk.Label(frame_right1, text='轮廓定位车牌位置：').grid(column=0, row=0, sticky=tk.W)
self.roi_ctl = ttk.Label(frame_right1)
print("ct1", self.roi_ctl)
self.roi_ctl.grid(column=0, row=1, sticky=tk.W)
# grid 列 行 位置
ttk.Label(frame_right1, text='轮廓定位识别结果：').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")
ttk.Label(frame_right1, text='车牌颜色：').grid(column=0, row=4, sticky=tk.W)
self.color_ctl.grid(column=0, row=5, sticky=tk.W)
ttk.Label(frame_right1, text='颜色定位车牌位置：').grid(column=0, row=6, sticky=tk.W)
self.roi_ct2 = ttk.Label(frame_right1)
print("ct2",self.roi_ct2)
self.roi_ct2.grid(column=0, row=7, sticky=tk.W)
ttk.Label(frame_right1, text='颜色定位识别结果：').grid(column=0, row=8, sticky=tk.W)
self.r_ct2 = ttk.Label(frame_right1, text="",font=('Times', '20'))
self.r_ct2.grid(column=0, row=9, sticky=tk.W)
self.color_ct2 = ttk.Label(frame_right1, text="",width="20")
ttk.Label(frame_right1, text='车牌颜色：').grid(column=0, row=10, sticky=tk.W)
self.color_ct2.grid(column=0, row=11, sticky=tk.W)
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
def choose_pic(self):
self.path = getcwd()
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
self.car1 = "你"
self.car2 = "我"
self.car3 = "他"
#界面处理
fileName_choose, filetype = QFileDialog.getOpenFileName(
self.centralwidget,
"选取图片文件",
self.path, # 起始路径
"视频(*.mp4)") # 文件类型
print(fileName_choose)
self.textEdit_pic.setText(fileName_choose + '文件已选中')
self.label1.setText('正在启动识别系统...\n\nleading')
self.cap = cv2.VideoCapture(fileName_choose)
i = 0
while self.cap.isOpened():
flag, im_rd = self.cap.read()
frameClone = im_rd.copy() # 复制画面
self.key1 = cv2.resize(frameClone[200:800, 150:650], (600, 600))
cv2.rectangle(frameClone, (150, 200), (650, 800), (255, 255, 0), 2)
self.key2 = cv2.resize(frameClone[200:800, 700:1200], (800, 800))
cv2.rectangle(frameClone, (700, 200), (1200, 800), (0, 255, 0), 2)
self.key3 = cv2.resize(frameClone[200:800, 1300:1800], (800, 800))
cv2.rectangle(frameClone, (1300, 200), (1800, 800), (255, 0, 0), 2)
frameClone = cv2.resize(frameClone, (520, 410))
# 在Qt界面中显示人脸
show = cv2.cvtColor(frameClone, cv2.COLOR_BGR2RGB)
showImage = QtGui.QImage(show.data, show.shape[1], show.shape[0],
QtGui.QImage.Format_RGB888)
self.label1.setPixmap(QtGui.QPixmap.fromImage(showImage))
QtWidgets.QApplication.processEvents()
i = i + 1
if i == 400: # 50秒响应一次
i = 0
#print((self.key1).type)
#cv2.imshow("ok",self.key2)
#img_bgr = cv2.imdecode(self.key1, cv2.IMREAD_COLOR)
#img_bgr = img_math.img_read("C:/Users/Administrator/Desktop/carddete/img_data/1586768004.jpg")
# cv2.imshow("dsad",self.key1)
#第1个
first_img2, oldimg2 = self.predictor.img_first_pre(self.key1)
#r_color2, roi_color2, color_color2 = self.predictor.img_color_contours(first_img2, oldimg2) #字符，定位图像，车牌颜色
r_color2, roi_color2, color_color2 = self.predictor.img_only_color(
oldimg2, oldimg2, first_img2)
if len(r_color2) > 4:
self.label_5.setStyleSheet(
"background-image: url(:/newPrefix/images_test/red.png);"
)
img1 = cv2.resize(roi_color2, (100, 20))
#cv2.imshow("ok",img1)
showImage = QtGui.QImage(img1.data, img1.shape[1],
img1.shape[0],
QtGui.QImage.Format_RGB888)
self.label_result.setPixmap(
QtGui.QPixmap.fromImage(showImage))
self.label_result_2.setText(r_color2)
self.label_5.setText(r_color2)
self.car1 = r_color2
print(str(self.car1))
else:
self.label_5.setStyleSheet(
"background-image: url(:/newPrefix/images_test/green.png);"
)
self.label_5.setText("NULL")
#第三个
first_img, oldimg = self.predictor.img_first_pre(self.key3)
# r_c, roi_c, color_c = self.predictor.img_color_contours(first_img, oldimg) #字符，定位图像，车牌颜色
r_color, roi_color, color_color = self.predictor.img_only_color(
oldimg, oldimg, first_img)
# print( "|", color_c, r_c, "|", color_color, r_color, "| ")
# print(len(r_c))
if len(r_color) > 4:
self.label_7.setStyleSheet(
"background-image: url(:/newPrefix/images_test/red.png);"
)
img1 = cv2.resize(roi_color, (100, 20))
#cv2.imshow("ok",img1)
showImage = QtGui.QImage(img1.data, img1.shape[1],
img1.shape[0],
QtGui.QImage.Format_RGB888)
self.label_result_5.setPixmap(
QtGui.QPixmap.fromImage(showImage))
self.label_result_6.setText(r_color)
self.label_7.setText(r_color)
self.car3 = r_color
#continue
else:
self.label_7.setStyleSheet(
"background-image: url(:/newPrefix/images_test/green.png);"
)
self.label_7.setText("NULL")
#self.car3 = "0"
first_img1, oldimg1 = self.predictor.img_first_pre(self.key2)
r_color1, roi_color1, color_color1 = self.predictor.img_only_color(
oldimg1, oldimg1, first_img1)
if len(r_color1) > 4:
self.label_6.setStyleSheet(
"background-image: url(:/newPrefix/images_test/red.png);"
)
img1 = cv2.resize(roi_color1, (100, 20))
#cv2.imshow("ok",img1)
showImage = QtGui.QImage(img1.data, img1.shape[1],
img1.shape[0],
QtGui.QImage.Format_RGB888)
self.label_result_3.setPixmap(
QtGui.QPixmap.fromImage(showImage))
self.label_result_4.setText(r_color1)
self.label_6.setText(r_color1)
self.car2 = r_color1
print("ok")
print((self.car2))
else:
self.label_6.setStyleSheet(
"background-image: url(:/newPrefix/images_test/green.png);"
)
self.label_6.setText("NULL")
