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垃圾桶主程序.py
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垃圾桶主程序.py
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# 基本原理：垃圾被丢进垃圾桶，触发红外模块，触发程序，系统调用训练好的模型对图像进行分类
# 根据模型预测的结果，通过串口发送指令给下位机，控制垃圾桶进行分类操作
# 同时有反馈步骤 + 保存每次预测的图像 （具体原理和步骤详见报告书）
# 路径结构,文件夹名称表示图片的类别
#||imagePath
#|----plastic
# |----image1
# |----image2
# ............
#|----metal
# |----image1
# |----image2
# ............
#|----paper
# |----image1
# |----image2
# ............
#|----other
# |----image1
# |----image1
#
from tkinter import *
from PIL import Image,ImageTk
import tkinter.messagebox
import tkinter as tk
import time
import pyautogui
from keras.models import load_model
from keras.preprocessing import image
from keras.applications.imagenet_utils import preprocess_input
from keras.preprocessing.image import img_to_array
import numpy as np
import time
import os
from PIL import Image
import cv2
from multiprocess import Process,Queue
import os,time,random
import RPi.GPIO as GPIO
import serial
# 界面显示的logo图标
logo_path = "/home/pi/Desktop/smart_trash/photo/fly_hero.jpg"
imagePath = "/home/pi/Desktop/Images/" #图片储存的路径（注意路径中不能有中文名）
labels = ["金属","塑料","废纸","其他"]
time_ok = time.time()
time_yesno = time.time()
time_init = time.time()
sign_yesno = 0
sign_ok = 0
sign_init = 0
#初始化IO口，分别是红外出发端口和LED补光控制端口
GPIO.setmode(GPIO.BCM)
GPIO.setup(21,GPIO.IN)
GPIO.setup(20,GPIO.OUT,initial=GPIO.LOW)
GPIO.setwarnings(False)
#初始化串口，串口连接下位机
ser = serial.Serial("/dev/ttyUSB0",9600,timeout =1)
# 加载已经训练好的模型
happyModel = load_model("/home/pi/Desktop/Models/MobileNet_trash.h5")
#拍照
def capture(count):
os.system("fswebcam --no-banner -r 640x480 -d /dev/video"+str(count)+" /home/pi/Desktop/Images/test"+str(count)+".jpg")
#图像预处理
def image_preprocess(imagePath):
image = cv2.imread(imagePath)
image = cv2.resize(image,(128,128))
image = image.astype("float")/255.0
image = img_to_array(image)
image = np.expand_dims(image,axis=0)
return image
#压缩图像
def compressed_image(imagePath,weight,height):
sImag = Image.open(imagePath)
print(weight,height)
dImg = sImag.resize((weight,height),Image.ANTIALIAS)
dImg.save(imagePath)
def Tk_photo(photoPath,weight,height):
sImag = Image.open(photoPath)
dImg = sImag.resize((weight,height),Image.ANTIALIAS)
dImg.save(photoPath.split(".")[0]+"_show."+photoPath.split(".")[1]) #重命名显示的图片
photo = ImageTk.PhotoImage(dImg)
return photo
class Popup(tk.Toplevel):
def __init__(self,parent):
super().__init__()
self.title("请给垃圾进行标记～")
self.parent = parent
self.geometry("480x360")
Label(self,text = "请选择您刚才扔的垃圾的类型",font = "Monaco 16",fg="green").place(x=80,y=30)
Button_capture1 = Button(self,text="塑料",font = "Monaco 12",width=8,height=5,command=lambda:self.move_file("plastic"))
Button_capture2 = Button(self,text="金属",font = "Monaco 12",width=8,height=5,command=lambda:self.move_file("metal"))
Button_capture3 = Button(self,text="废纸",font = "Monaco 12",width=8,height=5,command=lambda:self.move_file("paper"))
Button_capture4 = Button(self,text="其他",font = "Monaco 12",width=8,height=5,command=lambda:self.move_file("other"))
Button_capture1.place(x = 10,y = 100)
Button_capture2.place(x = 125,y = 100)
Button_capture3.place(x = 240,y = 100)
Button_capture4.place(x = 355,y = 100)
def message_show(self):
global time_ok,sign_ok,time_init,sign_init
self.destroy()
time_ok = time.time()
sign_ok = 1
a = tkinter.messagebox.showinfo("谢谢","谢谢您的反馈！\n你的反馈让我变得更智能！")
time_init = time.time()
sign_init = 1
# 将每次判断的图像保存到文件夹当中，以增加数据集
def move_file(self,trash_type):
os.system("mv /home/pi/Desktop/Images/test0.jpg /home/pi/Desktop/Images/user_label_image/"+trash_type+"/"+str(int(time.time()))+"0"+".jpg")
os.system("mv /home/pi/Desktop/Images/test1.jpg /home/pi/Desktop/Images/user_label_image/"+trash_type+"/"+str(int(time.time()))+"1"+".jpg")
if trash_type == "plastic":
ser.write("1".encode(encoding="utf-8"))
elif trash_type == "paper":
ser.write("2".encode(encoding="utf-8"))
elif trash_type == "metal":
ser.write("3".encode(encoding="utf-8"))
elif trash_type == "other":
ser.write("4".encode(encoding="utf-8"))
if trash_type == "plastic":
a = "塑料"
elif trash_type == "paper":
a = "废纸"
elif trash_type == "metal":
a = "金属"
elif trash_type == "other":
a = "其他"
self.parent.label_decision.config(text="垃圾种类："+a,font = "Monaco 18",fg="blue")
self.parent.update()
self.message_show()
class MyApp(tk.Tk):
def __init__(self):
super().__init__()
self.title("人工智能图像识别垃圾桶 电协小飞侠队")
self.geometry("480x360")
self.begin()
def begin(self):
a = Tk_photo(logo_path,100,100)
self.photo_show1 = Label(self,image = a)
self.photo_show1.image = a
self.label1 = Label(self,text = "摄像头1：")
b = Tk_photo(logo_path,100,100)
self.photo_show2 = Label(self,image = b)
self.photo_show2.image = b
self.label2 = Label(self,text = "摄像头2：")
self.label1.place(x=20,y=10)
self.photo_show1.place(x=20,y=30)
self.label2.place(x=20,y=145)
self.photo_show2.place(x=20,y=165)
self.label_state = Label(self,text="状态：空闲",font = "Monaco 15",fg="green")
self.label_decision = Label(self,text="垃圾种类：无",font = "Monaco 18",fg="red")
self.label_result1 = Label(self,text="等待结果",font = "Monaco 12")
self.label_result2 = Label(self,text="等待结果1",font = "Monaco 12")
self.label_result3 = Label(self,text="等待结果2",font = "Monaco 12")
self.label_result4 = Label(self,text="等待结果3",font = "Monaco 12")
Label(self,text="置信度：",font = "Monaco 15").place(x = 160,y= 130)
self.label_state.place(x=160,y=30)
self.label_decision.place(x=160,y=60)
self.label_result1.place(x = 160,y= 160)
self.label_result2.place(x = 160,y= 190)
self.label_result3.place(x = 160,y= 220)
self.label_result4.place(x = 160,y= 250)
Button_capture1 = Button(self,text="点击",font = "Monaco 10",width=8,height=5,command=self.on_click)
Button_capture1.place(x = 475,y = 130)
def init(self):
global sign_init,sign_yesno,sign_ok
sign_init = 0
sign_yesno = 0
sign_ok = 0
a = Tk_photo(logo_path,100,100)
self.photo_show1 = Label(self,image = a)
self.photo_show1.image = a
self.photo_show1.place(x=20,y=30)
b = Tk_photo(logo_path,100,100)
self.photo_show2 = Label(self,image = b)
self.photo_show2.image = b
self.photo_show2.place(x=20,y=165)
self.label_decision.config(text="垃圾种类：无",font = "Monaco 18",fg="red")
self.label_result1.config(text="等待垃圾",font = "Monaco 12")
self.label_result2.config(text="等待垃圾",font = "Monaco 12")
self.label_result3.config(text="等待垃圾",font = "Monaco 12")
self.label_result4.config(text="等待垃圾",font = "Monaco 12")
a = Tk_photo(logo_path,100,100)
self.photo_show1 = Label(self,image = a)
self.photo_show1.image = a
self.label1 = Label(self,text = "摄像头1：")
b = Tk_photo(logo_path,100,100)
self.photo_show2 = Label(self,image = b)
self.photo_show2.image = b
self.label2 = Label(self,text = "摄像头2：")
# 促发系统
def on_click(self):
global time_yesno,sign_yesno,time_ok,sign_ok,time_init,sign_init
#拍照+识别
self.init()
result = {}
self.label_state.config(text="状态：正在拍照",font = "Monaco 15",fg="blue")
self.update()
GPIO.output(20,1) #开灯拍照
time.sleep(1)
capture(0)
capture(1)
GPIO.output(20,0) #关灯
self.label_state.config(text="状态：正在识别",font = "Monaco 15",fg="blue")
self.update()
image1 = image_preprocess("/home/pi/Desktop/Images/test0.jpg")
image2 = image_preprocess("/home/pi/Desktop/Images/test1.jpg")
#预测图像，对两个摄像头采集的图像进行预测
pred1 = happyModel.predict(image1)
pred2 = happyModel.predict(image2)
print(pred1)
print(pred2)
# 平均两个预测结果
for i in range(4):
result[labels[i]] = float(pred1[0][i] + pred2[0][i])
result[labels[i]] = round(result[labels[i]]*100/2,2)
sorted_r = sorted(result.items(),key=lambda result:result[1])
a = Tk_photo("/home/pi/Desktop/Images/test0.jpg",100,100)
self.photo_show1 = Label(self,image = a)
self.photo_show1.image = a
self.photo_show1.place(x=20,y=30)
b = Tk_photo("/home/pi/Desktop/Images/test1.jpg",100,100)
self.photo_show2 = Label(self,image = b)
self.photo_show2.image = b
self.photo_show2.place(x=20,y=165)
self.label_decision.config(text="垃圾种类："+str(sorted_r[-1][0]),font = "Monaco 18",fg="blue")
self.label_result1.config(text="1."+sorted_r[-1][0]+":"+str(sorted_r[-1][1])+"%",fg="green")
self.label_result2.config(text="2."+sorted_r[-2][0]+":"+str(sorted_r[-2][1])+"%")
self.label_result3.config(text="3."+sorted_r[-3][0]+":"+str(sorted_r[-3][1])+"%")
self.label_result4.config(text="4."+sorted_r[-4][0]+":"+str(sorted_r[-4][1])+"%")
time_yesno = time.time()
sign_yesno = 1
YN = tkinter.messagebox.askyesno(title="请问",message="识别结果是:\n\n"+" "+sorted_r[-1][0]+"\n\n请问正确吗？")
self.label_state.config(text="状态：空闲",font = "Monaco 15",fg="green")
self.update()
if YN == False:
sign_yesno = 0
pw = Popup(self)
self.wait_window(pw)
else:
if sorted_r[-1][0] == "塑料":
trash_type = "plastic"
elif sorted_r[-1][0] == "金属":
trash_type = "metal"
elif sorted_r[-1][0] == "其他":
trash_type = "other"
elif sorted_r[-1][0] == "废纸":
trash_type = "paper"
if sorted_r[-1][0] == "塑料":
ser.write("1".encode(encoding="utf-8"))
elif sorted_r[-1][0] == "废纸":
ser.write("2".encode(encoding="utf-8"))
elif sorted_r[-1][0] == "金属":
ser.write("3".encode(encoding="utf-8"))
elif sorted_r[-1][0] == "其他":
ser.write("4".encode(encoding="utf-8"))
os.system("mv /home/pi/Desktop/Images/test0.jpg /home/pi/Desktop/Images/user_label_image/"+trash_type+"/"+str(int(time.time()))+"0"+".jpg")
os.system("mv /home/pi/Desktop/Images/test1.jpg /home/pi/Desktop/Images/user_label_image/"+trash_type+"/"+str(int(time.time()))+"1"+".jpg")
time_ok = time.time()
sign_ok = 1
tkinter.messagebox.showinfo("谢谢","谢谢您的反馈！\n你的反馈让我变得更加智能！")
time_init = time.time()
sign_init = 1
def main():
global time_yesno,time_ok,time_init,sign_yesno,sign_ok,sign_init
if GPIO.input(21)==0:
time.sleep(0.15)
if GPIO.input(21)==0:
pyautogui.click(x = 495,y = 215)
print("4")
pyautogui.click(x = 480,y = 320)
if ((time.time()-time_yesno) >5) and (sign_yesno == 1):
sign_yesno = 0
pyautogui.press("enter")
print("1")
if ((time.time()-time_ok) >2) and (sign_ok == 1):
sign_ok = 0
pyautogui.press("enter")
print("2")
if ((time.time()-time_init) >8) and (sign_init == 1):
sign_init = 0
app.init()
print("3")
app.after(1,main)
if __name__ == '__main__':
app = MyApp()
app.after(1,main)
app.mainloop()