OpenCV运动目标识别光流法

待我称王封你为后i 2023-01-11 09:13 149阅读 0赞

import cv2
    import numpy as np
    es = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(10,10))
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
    cap = cv2.VideoCapture("anew.flv")
    frame1 = cap.read()[1]
    prvs = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
    hsv = np.zeros_like(frame1)
    hsv[...,1] = 255
    out_fps =12.0
    fourcc = cv2.VideoWriter_fourcc('M','P','4','2')
    sizes = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
    out1 = cv2.VideoWriter('5.avi',fourcc,out_fps,sizes)
    out2 = cv2.VideoWriter('6.avi',fourcc,out_fps,sizes)
    while True:
        (ret,frame2) = cap.read()
        next = cv2.cvtColor(frame2,cv2.COLOR_BGR2GRAY)
        flow = cv2.calcOpticalFlowFarneback(prvs,next,None,0.5,3,15,3,5,1.2,0)
        print(flow[...,1])
        #得到梯度幅度和梯度角度阵列
        mag,ang = cv2.cartToPolar(flow[...,0],flow[...,1])
        hsv[...,0] = ang*180/np.pi/2
        hsv[...,2] = cv2.normalize(mag,None,0,255,cv2.NORM_MINMAX)
        bgr = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)
        draw = cv2.cvtColor(bgr,cv2.COLOR_BGR2GRAY)
        draw = cv2.morphologyEx(draw,cv2.MORPH_OPEN,kernel)
        draw = cv2.threshold(draw,25,255,cv2.THRESH_BINARY)[1]
        contours,hierarchy = cv2.findContours(draw.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
        for c in contours:
            if cv2.contourArea(c) < 300:
                continue
            (x,y,w,h) = cv2.boundingRect(c)
            cv2.rectangle(frame2,(x,y),(x+w,y+h),(255,255,0),2)
        cv2.imshow('frame2',bgr)
        cv2.imshow('draw',draw)
        cv2.imshow('frame1',frame2)
        out1.write(bgr)
        out2.write(frame2)
        k= cv2.waitKey(20) & 0xff
        if k==27 or k == ord('q'):
            break
        elif k == ord('s'):
            cv2.imwrite('opticalfb.png',frame2)
            cv2.imwrite('opticalhsv.png',bgr)
        prvs = next
    out1.release()
    out2.release()
    cap.release()
    cv2.destroyAllWindows()

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