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="5", pady="5")
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='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)
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='识别结果：').grid(column=0, row=2, sticky=tk.W)
self.r_ctl = ttk.Label(frame_right1, text="")
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_pic_ctl.pack(anchor="se", pady="5")
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("License Plate Recognition")
win.state("zoomed")
self.pack(fill=tk.BOTH, expand=tk.YES, padx="5", pady="5")
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='Orjgin Image:').pack(anchor="nw")
ttk.Label(frame_right1, text='Plate Position:').grid(column=0,
row=0,
sticky=tk.W)
from_pic_ctl = ttk.Button(frame_right2,
text="Choose Image",
width=20,
command=self.from_pic)
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='Results:').grid(column=0,
row=2,
sticky=tk.W)
self.r_ctl = ttk.Label(frame_right1, text="")
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_pic_ctl.pack(anchor="se", pady="5")
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
def __init__(self, win):
ttk.Frame.__init__(self, win)
#界面名称
win.title("车牌识别")
win.state("normal")
self.pack(fill=tk.BOTH, expand=tk.YES, padx="5", pady="5")
#创建3块矩形区域，作为容器来布局图形界面
############################################frame_left主要用来显示待识别的图像##################################################
frame_left = ttk.Frame(self)
frame_left.pack(side=LEFT, expand=1, fill=BOTH)
ttk.Label(frame_left, text='input picture：',
font=('Arial', 20)).pack(anchor="nw", padx=30)
self.image_ctl = ttk.Label(frame_left)
self.image_ctl.pack(anchor="nw")
############################################################################################################################
############################################frame_right1主要用来显示识别结果##################################################
frame_right1 = ttk.Frame(self)
frame_right1.pack(side=TOP, expand=1, fill=tk.Y)
ttk.Label(frame_right1,
text='license plate segmentation：',
font=('Arial', 20)).grid(column=0, row=0, sticky=tk.W)
self.roi_ctl = ttk.Label(frame_right1, font=('Arial', 20))
self.roi_ctl.grid(column=0, row=1)
ttk.Label(frame_right1, text='recognition result：',
font=('Arial', 20)).grid(column=0, row=10, sticky=tk.SW)
self.r_ctl = ttk.Label(frame_right1, text="", font=('Arial', 20))
self.r_ctl.grid(column=0, row=11)
# self.color_ctl = ttk.Label(frame_right1, text = "", font = ('Arial', 20), width = "20")
# self.color_ctl.grid(column = 0, row = 12, sticky = tk.SW)
############################################################################################################################
############################################frame_right2主要用来选择倒入图片的方式##################################################
frame_right2 = ttk.Frame(self)
frame_right2.pack(side=RIGHT, expand=0)
ttk.Style().configure('TButton', font=('Arial', 20))
#创建一个button，用于从文件路径中读取待识别图片，回调函数为from_folder
from_folder_ctl = ttk.Button(frame_right2,
text="chose picture from folder",
width=30,
command=self.from_folder)
from_folder_ctl.pack(anchor="se", pady="5")
############################################################################################################################
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
def Get_Plate(self):
# get the license plate, the color one need to recognize color
photopro = PhotoPro(self.image_path)
color_plate = photopro.Get_Image()
# create a object from predict which can recognize plate
cpd = predict.CardPredictor()
cpd.train_svm()
# write plate
cv2.imwrite('test.jpg', color_plate)
return cv2.imread('./test.jpg')
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("数字表识别")
w, h = win.maxsize()
win.geometry("{}x{}".format(w, h))
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='表盘位置：').grid(column=0,
row=0,
sticky=tk.W)
from_pic_ctl = ttk.Button(frame_right2,
text="打开相册",
width=20,
command=self.from_pic)
from_vedio_ctl = ttk.Button(frame_right2,
text="打开摄像头",
width=20,
command=self.from_vedio)
start_ctl = ttk.Button(frame_right2,
text="拍照",
width=20,
command=self.start_vedio)
send_ctl = ttk.Button(frame_right2,
text="上传",
width=20,
command=self.send)
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='识别结果：').grid(column=0,
row=2,
sticky=tk.W)
self.r_ctl = ttk.Label(frame_right1, text="")
self.r_ctl.grid(column=0, row=3, sticky=tk.W)
from_pic_ctl.pack(anchor="se", pady="10")
from_vedio_ctl.pack(anchor="se", pady="10")
start_ctl.pack(anchor="se", pady="10")
send_ctl.pack(anchor="se", pady="10")
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")
win.maxsize(1000, 800)
win.minsize(600, 600)
self.pack(fill=tk.BOTH, expand=tk.YES, padx="5", pady="5")
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='车牌位置：').grid(column=0, row=0, sticky=tk.W)
ttk.Label(frame_right1, text='是否是库内车辆：').grid(column=0, row=2, sticky=tk.W)
ttk.Label(frame_right1, text='进入时间：').grid(column=0, row=4, sticky=tk.W)
ttk.Label(frame_right1, text='出来时间：').grid(column=0, row=6, 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)
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)
self.positon = ttk.Label(frame_right1)
self.positon.grid(column=0, row=3, sticky=tk.W)
self.first_time = ttk.Label(frame_right1)
self.first_time.grid(column=0, row=5, sticky=tk.W)
self.final_time = ttk.Label(frame_right1)
self.final_time.grid(column=0, row=7, sticky=tk.W)
ttk.Label(frame_right1, text='识别结果：').grid(column=0, row=8, sticky=tk.W)
self.r_ctl = ttk.Label(frame_right1, text="")
self.r_ctl.grid(column=0, row=9, sticky=tk.W)
self.color_ctl = ttk.Label(frame_right1, text="", width="20")
self.color_ctl.grid(column=0, row=10, sticky=tk.W)
from_vedio_ctl.pack(anchor="se", pady="5")
from_pic_ctl.pack(anchor="se", pady="5")
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
def __init_gui(self):
# self.currentBroadValue = '123'
self.window = tk.Tk()
self.window.wm_title('AIOT智能交通综合案例')
# books = ('颜色检测', '物体识别 ', 'd', \
# '涂鸦检测','结束检测')
self.window.config(background='#FFFFFF')
self.canvas = ICanvas(self.window, width=320, height=240)
self.canvas.grid(row=0, column=0)
self.fm_control = tk.Frame(self.window,
width=200,
height=240,
background='#FFFFFF')
self.fm_control.grid(row=0, column=1, padx=10, pady=2)
# self.fm_status = tk.Frame(self.window, width=320, height=120, background='#FFFFFF')
# self.fm_status.grid(row=1, column=0, padx=0, pady=2)
self.lbStatus = tk.Label(self.fm_control,
text='提示：没有需要识别的...',
bg='Yellow',
justify='left',
anchor='w')
self.lbStatus.place(x=0, y=10, width=320, height=30)
self.lbValue = tk.Label(self.fm_control,
text='等待识别中... ',
bg='Green',
justify='left',
anchor='w')
self.lbValue.place(x=0, y=70, width=320, height=30)
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
# self.fm_title = tk.Frame(self.window, width=200, height=120, background='#FFFFFF')
# self.fm_title.grid(row=1, column=1, padx=0, pady=2)
# self.lbCue = tk.Label(self.fm_title, text='提示：点击上方按钮，选择需要识别的... ', bg='Blue', fg='White',justify='left', anchor='w')
# self.lbCue.place(x=0, y=30, width=200, height=50)
self.__action_read_frame()
def __init__(self):
# 设置不显示警告
global ser
global c
GPIO.setwarnings(False)
# 设置读取面板针脚模式
# 将引脚设置为输入模式
GPIO.setmode(GPIO.BCM)
# 设置读取针脚标号
GPIO.setup(4, GPIO.IN)
# GPIO.setup(2, GPIO.OUT)
# 串口初始化
ser = serial.Serial("/dev/ttyAMA0", 9600, timeout=0)
time.sleep(1)
c = predict.CardPredictor()
c.train_svm()
print('init ok!')
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_center = ttk.Frame(self)
win.title("车牌识别")
win.state("zoomed")
self.pack(fill=tk.BOTH, expand=tk.YES, padx="5", pady="5")
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)
frame_center.pack(side=LEFT, expand=1, fill=BOTH)
Label(frame_center,
text="==\n|欢|\n|迎|\n|使|\n|用|\n|车|\n|牌|\n|识|\n|别|\n|系|\n|统|\n==",
fg="red",
font='Helvetica -49 bold').pack(anchor="nw")
Label(frame_left, text='原图：',
font='Helvetica -27 bold').pack(anchor="nw")
Label(frame_right1, text='车牌位置：',
font='Helvetica -27 bold').grid(column=0, row=0, sticky=tk.W)
from_pic_ctl = Button(frame_right2,
text="来自图片",
font='Helvetica -29 bold',
bg="grey",
fg="yellow",
width=20,
command=self.from_pic)
from_vedio_ctl = Button(frame_right2,
text="来自摄像头",
font='Helvetica -29 bold',
bg="grey",
fg="yellow",
width=20,
command=self.from_vedio)
button3 = Button(frame_right2,
text="api再识别",
font='Helvetica -29 bold',
bg="grey",
fg="yellow",
width=20,
command=self.api)
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)
Label(frame_right1, text='识别结果：',
font='Helvetica -29 bold').grid(column=0, row=2, sticky=tk.W)
self.r_ctl = ttk.Label(frame_right1, text="")
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")
button3.pack(anchor="se", pady="5")
self.predictor = predict.CardPredictor()
self.predictor.train_svm()
def detect_carnumber(img_bgr, box): #r1, r2, r3, r4
predictor = predict.CardPredictor()
img_bgr = img_bgr[box[0]:box[1], box[2]:box[3]]
r = predictor.predict(img_bgr)
return r
def main():
try:
# 1-设备与环境初始化
picdir = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'lib_E-ink/pic') # 设置路径
libdir = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'lib_E-ink/lib')
if os.path.exists(libdir):
sys.path.append(libdir)
logging.basicConfig(level=logging.DEBUG)
# 摄像头
camera = cv2.VideoCapture(0) # 定义摄像头对象，参数0表示第一个摄像头，默认640x480
# camera.set(cv2.CAP_PROP_FRAME_WIDTH, 960) # 重设获取图像分辨率(predict.py设定了最大1000)
# camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 540) # 图像越大处理速度越慢，树莓派不开超频时会卡
if camera is None: # 摄像头打开失败
print(u'检测摄像头是否连接正常!')
exit()
fps = 24 # 帧率
# 水墨屏
epd = epd1in54_V2.EPD()
logging.info("E-ink Init & Clear")
epd.init()
epd.Clear(0xFF)
image = Image.open(os.path.join(picdir, 'USST.bmp')) # read bmp file
epd.display(epd.getbuffer(image)) # 欢迎界面
time.sleep(2)
# 绘制的图像界面
image = Image.open(os.path.join(picdir, '1in54.bmp'))
draw = ImageDraw.Draw(image) # 相当于清屏，得到当前图像对象句柄
font20 = ImageFont.truetype(os.path.join(picdir, 'Font.ttc'),
20) # 字体，高20个像素
font24 = ImageFont.truetype(os.path.join(picdir, 'Font.ttc'),
24) # 字体，高24个像素
font30 = ImageFont.truetype(os.path.join(picdir, 'Font.ttc'), 30)
draw.text((0, 89), u' 界面初始化 ', font=font30,
fill=0) # PIL库还提供很多绘制函数，十分方便
draw.text((5, 165), u'CPU: °C GPU: °C', font=font20, fill=0)
draw.rectangle((70, 4, 180, 30), fill=255)
draw.text((70, 4), time.strftime('%m/%d/%Y'), font=font24, fill=0)
epd.display(epd.getbuffer(image))
# 向量机图像学习分类训练
predictor = predict.CardPredictor()
predictor.train_svm()
logging.info(u'SVM学习训练完毕')
refershsign = 0 # 刷新墨水屏的标记；0不刷新，1刷新
lastrefreshtime = 0 # 记录墨水屏上次刷新的时间
lastcarchar = None
while True:
start = time.time()
res, cur_frame = camera.read() # 读取视频流
if res != True:
break
end = time.time()
seconds = end - start
if seconds < 1.0 / fps: # 按帧速处理，这里其实可以可以除掉了，因为这里视频输出帧率已经无法保证
time.sleep(1.0 / fps - seconds)
# 若检测按下ESC键，则退出程序
key = cv2.waitKey(10) & 0xff
if key == 27:
break
# 车牌识别
carchar, roi, color = predictor.predict(
cur_frame) # 返回识别到的字符，定位的车牌图像，车牌颜色
if carchar is not None:
print(u'识别结果:{0:s}\n'.format(
carchar.decode('utf-8'))) # Python2对中文字符不直接支持的问题
if carchar != lastcarchar: # 说明与上次识别的结果不一致，需要刷新下墨水屏
refershsign = 1
lastcarchar = carchar
else:
lastcarchar = None
continue
# 当有新的识别结果，且满足刷新频率时（2s/次），更新墨水屏显示
if (time.time() - lastrefreshtime) > 2 and refershsign == 1:
draw.rectangle((10, 75, 190, 150), fill=255)
draw.text((10, 75), u' 识别成功！ ', font=font24, fill=0)
draw.text((35, 110),
carchar.decode('utf-8'),
font=font30,
fill=0)
draw.rectangle((70, 38, 180, 65), fill=255)
draw.text((70, 38),
time.strftime(' %H:%M:%S'),
font=font24,
fill=0)
draw.rectangle((50, 165, 70, 198), fill=255)
draw.text((50, 165),
str(int(get_cpu_temp())),
font=font20,
fill=0)
draw.rectangle((145, 165, 168, 198), fill=255)
draw.text((145, 165),
str(int(get_gpu_temp())),
font=font20,
fill=0)
epd.displayPart(epd.getbuffer(image)) # 局部刷新显示
lastrefreshtime = time.time()
refershsign = 0
camera.release() # 释放摄像头
cv2.destroyAllWindows() # 关闭所有图像窗口
logging.info("E-Ink Clear...") # 墨水屏清屏
epd.init()
epd.Clear(0xFF)
epd.sleep()
# 异常处理
except IOError as e:
logging.info(e)
except KeyboardInterrupt:
logging.info("ctrl + c:")
epd1in54_V2.epdconfig.module_exit()
exit()
