在Python OpenCV中创建流程图

Question

更新问题:

有没有人能给我指出任何可以帮助我用python绘制光流图的材料的方向?理想情况下，我想找到的东西，提供了一个类似的输出视频显示在这里:http://study.marearts.com/2014/04/opencv-study-calcopticalflowfarneback.html。或者具有类似功能输出的东西

我已经实现了密集光流算法(cv2.calcOpticalFlowFarneback)。由此，我可以对图像中指定点的亮度进行采样。正在输入的视频馈送是640x480，我设置了采样点在垂直和水平上每5个像素。

import cv2
import numpy as np
import matplotlib.pyplot as plt
cap = cv2.VideoCapture("T5.avi")
ret, frame1 = cap.read()
prvs = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[..., 1] = 255
[R,C]=prvs.shape
count=0
while (1):
    ret, frame2 = cap.read()
    next = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
    flow = cv2.calcOpticalFlowFarneback(prvs, next, None, 0.5, 3, 15, 2, 5, 1.2, 0)
    mag, ang = cv2.cartToPolar(flow[..., 0], flow[..., 1])
    RV=np.arange(5,480,5)
    CV=np.arange(5,640,5)
    # These give arrays of points to sample at increments of 5
    if count==0:
        count =1 #so that the following creation is only done once
        [Y,X]=np.meshgrid(CV,RV)
        # makes an x and y array of the points specified at sample increments
    temp =mag[np.ix_(RV,CV)]
    # this makes a temp array that stores the magnitude of flow at each of the sample points
    motionvectors=np.array((Y[:],X[:],Y[:]+temp.real[:],X[:]+temp.imag[:]))
    Ydist=motionvectors[0,:,:]- motionvectors[2,:,:]
    Xdist=motionvectors[1,:,:]- motionvectors[3,:,:]
    Xoriginal=X-Xdist
    Yoriginal=Y-Ydist

    plot2 = plt.figure()
    plt.quiver(Xoriginal, Yoriginal, X, Y,
               color='Teal',
               headlength=7)
    plt.title('Quiver Plot, Single Colour')
    plt.show(plot2)

    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)
    cv2.imshow('frame2', bgr)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
    prvs = next
cap.release()
cv2.destroyAllWindows()

我想我已经计算了像素的原始和最终X,Y位置以及移动的距离，并将这些放入matplotlib颤抖图中。

我得到的结果与密集光流的hsv图不一致(我知道这是正确的，因为它是从OpenCV教程中获取的)，而颤抖图一次也只显示一帧，并且必须在下一个显示之前退出。

有人能看到我在哪里出了问题在我的计算和我如何能使情节更新自动与每一帧?

Answer 1

我不知道如何改变matplotlib颤抖图的行为，但我确信这是可能的。

另一种方法是创建一个函数，根据计算出的光流，在原始图像的顶部绘制线条。下面的代码应该实现这一点:

def dispOpticalFlow( Image,Flow,Divisor,name ):
"Display image with a visualisation of a flow over the top. A divisor controls the density of the quiver plot."
PictureShape = np.shape(Image)
#determine number of quiver points there will be
Imax = int(PictureShape[0]/Divisor)
Jmax = int(PictureShape[1]/Divisor)
#create a blank mask, on which lines will be drawn.
mask = np.zeros_like(Image)
for i in range(1, Imax):
  for j in range(1, Jmax):
     X1 = (i)*Divisor
     Y1 = (j)*Divisor
     X2 = int(X1 + Flow[X1,Y1,1])
     Y2 = int(Y1 + Flow[X1,Y1,0])
     X2 = np.clip(X2, 0, PictureShape[0])
     Y2 = np.clip(Y2, 0, PictureShape[1])
     #add all the lines to the mask
     mask = cv2.line(mask, (Y1,X1),(Y2,X2), [255, 255, 255], 1)
#superpose lines onto image
img = cv2.add(Image,mask)
#print image
cv2.imshow(name,img)
return []

这段代码只创建行而不是箭头，但是稍加修改可以显示箭头。