python-opencv图像处理基础练习2

最新推荐文章于 2024-02-16 20:54:50 发布

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最新推荐文章于 2024-02-16 20:54:50 发布

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本文链接：https://blog.youkuaiyun.com/qq_27689693/article/details/79062312

本文介绍了一种使用OpenCV库进行实时视频中运动目标检测的方法。该方法通过摄像头捕获实时视频帧，并利用背景减除技术来检测画面中的运动目标。通过对连续帧之间的差异进行分析并应用图像处理技术，如高斯模糊、轮廓检测等，实现对移动物体的有效识别。

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import cv2
import numpy as np


def fun():
    camera=cv2.VideoCapture(0)
    es = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(10,10))
    kernel =np.ones((5,5),np.uint8)
    background = None
    while True:
        ret,frame=camera.read()
        if background is None:
            background = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
            background = cv2.GaussianBlur(background,(21,21),0)
            continue
        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray_frame = cv2.GaussianBlur(gray_frame, (21, 21), 0)
        diff = cv2.absdiff(background, gray_frame)
        diff = cv2.threshold(diff, 25, 255, cv2.THRESH_BINARY)[1]
        diff = cv2.dilate(diff, es, iterations=2)
        cnts,hierarchy = cv2.findContours(diff.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        for c in cnts:
            if cv2.contourArea(c)<1500:
                continue
            (x,y,w,h) = cv2.boundingRect(c)
            cv2.rectangle(frame,(x,y),(x+w,y+h),(255,255,0),2)
        cv2.imshow("contours",frame)
        cv2.imshow("dif",diff)
        if cv2.waitKey(1000/12)&0xf ==ord("q"):
            break
    cv2.destroyAllWindows()
    camera.replease()


def showimg():
    img = cv2.imread("1.jpg")
    cv2.namedWindow("SHE")
    cv2.imshow("SHE", img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


if __name__ == "__main__":
    fun()