Opencv python之车辆识别项目

图片车辆识别

根据文章搭建好环境后开始进行做项目link

import sys
import cv2
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
from PyQt5.QtGui import QIcon, QPalette, QPixmap, QBrush, QRegExpValidator




class mainWin(QWidget):
    def __init__(self):
        """
        构造函数
        """
        super().__init__()
        self.initUI()
        self.openBtn.clicked.connect(self.openFile)  # 信号和槽
        self.grayBtn.clicked.connect(self.imgGray)  # 信号和槽
        self.carCheckBtn.clicked.connect(self.carCheck)

    def initUI(self):
        # 设置窗口得大小
        self.setFixedSize(860, 600)
        # 图标和背景
        self.setWindowTitle("车辆检测")
        self.setWindowIcon(QIcon("img/icon.jpg"))  # 图标

        # 标签
        self.leftLab = QLabel("原图:", self)
        self.leftLab.setGeometry(10, 50, 400, 400)  # 设置绝对位置
        self.leftLab.setStyleSheet("background:white")

        self.newLab = QLabel("新图:", self)
        self.newLab.setGeometry(420, 50, 400, 400)  # 设置绝对位置
        self.newLab.setStyleSheet("background-color:white")

        # 按钮
        self.openBtn = QPushButton(" 打开文件", self)
        self.openBtn.setGeometry(10, 10, 80, 30)


        self.grayBtn = QPushButton(" 灰度处理", self)
        self.grayBtn.setGeometry(100, 10, 80, 30)

        self.carCheckBtn = QPushButton(" 视频检测", self)
        self.carCheckBtn.setGeometry(200, 10, 80, 30)

打开文件方法

 def openFile(self):
        """
        打开文件的处理函数
        :return;
        :return:
        """

        print("打开图片")

        self.img,imgType = QFileDialog.getOpenFileName(self, "打开图片", "", "*.jpg;;*.png;;ALL FILES(*)")
        print(self.img)

        #jpg = QPixmap(self.img)
        self.leftLab.setPixmap(QPixmap(self.img))
        self.leftLab.setScaledContents(True)

图像变灰度并车辆识别方法
外汇专业术语https://www.fx61.com/definitions

    def imgGray(self):
        print("灰度")
        img1 = cv2.imread(self.img)
        #1. 灰度化处理
        img_gray = cv2.cvtColor(img1, cv2.COLOR_RGB2GRAY)
        # BGR = cv2.cvtColor(module,cv2.COLOR_BGR2RGB)# 转化为RGB格式
        # ret,thresh = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)#二值化


        #2. 加载级联分类器
        car_detector = cv2.CascadeClassifier("./cars.xml")

        """
        image--图片像素数据
        scaleFactor=None,缩放比例
        minNeighbors=None,2  写2就是3
        flags =None, 标志位 用什么来进行检测
        minSize=None,最小的尺寸
        maxSize=None,最大的尺寸
        self, image, scaleFactor=None, minNeighbors=None, flags=None, minSize=None, maxSize=None
        """
        #3. 检测车辆  多尺度检测,得到车辆的坐标定位
        cars = car_detector.detectMultiScale(img_gray, 1.05, 2, cv2.CASCADE_SCALE_IMAGE, (20,20), (100,100))
        print(cars)
        #(274  46  28  28) --(x,y,w,h)

        #4. 在车的定位上画图
        for(x, y, w, h) in cars:
            print(x, y, w, h)
            #img, pt1, pt2, color, thickness = None, lineType = None, shift = None
            cv2.rectangle(img1,(x,y), (x+w, y+h), (255, 255, 255), 1, cv2.LINE_AA)

        # 保存图片
        img_gray_name = "3.png"  # 文件名
        cv2.imwrite(img_gray_name, img1)  # 保存

        # 显示再控件上面
        self.newLab.setPixmap(QPixmap(img_gray_name))
        self.newLab.setScaledContents(True)

视频车辆识别

视频打开且识别方法

    def carCheck(self):
        print("车流检测")
        # parent: QWidget = None, caption: str = '', directory: str = '', filter:
        #1. 选择视频
        video, videoType = QFileDialog.getOpenFileName(self, "打开视频", "", "*.mp4")
        print(video, videoType)

        # video --打开的视频filename
        #2. 读取加载视频
        cap = cv2.VideoCapture(video)

        #3.读取一帧图片
        while True:
            status,img = cap.read()
            if status:
                # 灰度
                gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
                # 2. 加载级联分类器
                car_detector = cv2.CascadeClassifier("./cars.xml")

                cars = car_detector.detectMultiScale(gray, 1.2, 2, cv2.CASCADE_SCALE_IMAGE, (25, 25), (200, 200))
                # 画框框
                for (x, y, w, h) in cars:
                    print(x, y, w, h)
                    # img, pt1, pt2, color, thickness = None, lineType = None, shift = None
                    cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 255), 1, cv2.LINE_AA)

                print("实时车流量", len(cars))
                text = 'car number: '+str(len(cars))
                # 添加文字
                cv2.putText(img, text, (350, 100), cv2.FONT_HERSHEY_SIMPLEX, 1.2, (255, 255, 0), 2)
                cv2.imshow("opencv", img)
                key = cv2.waitKey(10)  # 延时并且监听按键
                if key == 27:
                    break
            else:
                break

        # 释放资源
        cap.release()
        cv2.destroyAllWindows()

主函数

if __name__ == "__main__":
    app = QApplication(sys.argv)  #创建一个应用程序
    win = mainWin()  #实例化对象
    win.show()  #显示窗口
    sys.exit(app.exec_())
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