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, QRegExpValidatorclass 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

    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3flags =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 = Nonecv2.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 = Nonecv2.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:breakelse: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_())

图像识别效果（想要效果好些 需要自己去琢磨调参数）

视频车辆识别效果

文章内容都为个人笔记，侵权必究！！！
源码下载：link