图片车辆识别

根据文章搭建好环境后开始进行做项目linkimport 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)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_())