OpenCV项目1-图像识别之车辆统计

1.视频加载

import cv2
import numpy as np
cap = cv2.VideoCapture('./video.mp4')

2.背景减除对象

mog = cv2.bgsegm.createBackgroundSubtractorMOG() # 创建mog对象

3.形态学卷积核

kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5)) # 矩形卷积核用于形态学操作

4.外接矩形中心点

min_w = 90
min_h = 90
line_high = 600
offset = 7 # 偏移量
cars = []
carno = 0
def center(x, y, w, h): # cx, cy：计算外接矩形的中心点
    x1 = int(w / 2)
    y1 = int(h / 2)
    cx = int(x) + x1
    cy = int(y) + y1
    return cx, cy

5.视频帧循环读取

while True: 
    ret, frame = cap.read()
    if ret == True:
    
# 5.1 色彩空间
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # COLOR_BGR2GRAY:把原始帧进行灰度化
        
# 5.2 滤波器 
        blur = cv2.GaussianBlur(gray, (3, 3), 5) # GaussianBlur:去噪
        
# 5.3 背景减除
        mask = mog.apply(blur) # 背景减除
        
# 5.4 形态学
        erode = cv2.erode(mask, kernel) # erode：腐蚀
        dialte = cv2.dilate(erode, kernel, iterations=2) # dilate：膨胀即把图像还原回来
        close = cv2.morphologyEx(dialte, cv2.MORPH_CLOSE, kernel) # MORPH_CLOSE：消除内部的小块即闭运算
        
# 5.5 轮廓查找
        contours, h = cv2.findContours(close, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) 
        
# 5.6 检测线
        cv2.line(frame, (10, line_high), (1200, line_high), (255, 255, 0), 3) 
        
# 5.7 轮廓绘制
        for contour in contours: 
            (x, y, w, h) = cv2.boundingRect(contour) # boundingRect：最大外接矩形
            is_valid = (w >= min_w) and (h >= min_h) # 通过外接矩形的宽高大小来过滤掉小矩形.
            if not is_valid:
                continue # continue：跳过  能走到这里来的都是符合要求的矩形即正常的车
            cv2.rectangle(frame, (int(x), int(y)), (int(x + w), int(y + h)), (0, 0, 255), 2) #  要求坐标点都是整数
            cpoint = center(x, y, w, h) # 把车抽象为一点即外接矩形的中心点 要通过外接矩形计算矩形的中心点
            cars.append(cpoint)
            cv2.circle(frame, (cpoint), 5, (0, 0, 255), -1)
            
# 5.8 检测线及计数
            for (x, y) in cars: # 判断汽车是否过检测线
                if y > (line_high - offset) and y < (line_high + offset):
                    carno += 1 # 落入有效区间 计数加1
                    cars.remove((x, y))
                    print(carno)         # 画线 计数

# 5.9 窗口显示
        cv2.putText(frame, 'Vehicle Count:' + str(carno), (500, 60), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 0, 255), 5)    
        cv2.imshow('frame', frame)
        
# 5.10 窗口退出
    key = cv2.waitKey(1)
    if key == 27: # 用户按esc退出
        break

6.释放资源

cap.release() 

7.摧毁窗口

cv2.destroyAllWindows()
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