Question

我正在为我的实验室做一个项目，使用光流来计算物体的数量。有人能让我知道如何将我的光流输出视频写入存储在我计算机上的新视频吗？谢谢！

import numpy as np
import cv2

cap = cv2.VideoCapture('crab2.mp4')

# params for ShiTomasi corner detection
feature_params = dict( maxCorners = 100,
                       qualityLevel = 0.3,
                        minDistance = 7,
                        blockSize = 7 )
# Parameters for lucas kanade optical flow
lk_params = dict( winSize  = (15,15),
                   maxLevel = 2,
                   criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03)) 
 # Create some random colors
color = np.random.randint(0,255,(100,3))
# Take first frame and find corners in it
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
p0 = cv2.goodFeaturesToTrack(old_gray, mask = None, **feature_params)

# Create a mask image for drawing purposes
mask = np.zeros_like(old_frame)

while(1):
     ret,frame = cap.read()
     frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) 
    # calculate optical flow
     p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)

     # Select good points
     good_new = p1[st==1]
     good_old = p0[st==1]

     # draw the tracks
     for i,(new,old) in enumerate(zip(good_new,good_old)):
         a,b = new.ravel()
         c,d = old.ravel()
         mask = cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2)
         frame = cv2.circle(frame,(a,b),5,color[i].tolist(),-1)
     img = cv2.add(frame,mask)

     cv2.imshow('frame',img)
     k = cv2.waitKey(30) & 0xff
     if k == 27:
         break

     # Now update the previous frame and previous points
     old_gray = frame_gray.copy()
     p0 = good_new.reshape(-1,1,2)


cv2.destroyAllWindows()
cap.release()

Answer 1

这样可行：

import numpy as np
import cv2

cap = cv2.VideoCapture('crab2.mp4')
output_file = "./crab2_track.mp4"
fourcc = cv2.VideoWriter_fourcc(*'DIVX')

# params for ShiTomasi corner detection
feature_params = dict( maxCorners = 100,
                       qualityLevel = 0.3,
                        minDistance = 7,
                        blockSize = 7 )
# Parameters for lucas kanade optical flow
lk_params = dict( winSize  = (15,15),
                   maxLevel = 2,
                   criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03)) 
 # Create some random colors
color = np.random.randint(0,255,(100,3))
# Take first frame and find corners in it
ret, old_frame = cap.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
p0 = cv2.goodFeaturesToTrack(old_gray, mask = None, **feature_params)

# Create a mask image for drawing purposes
mask = np.zeros_like(old_frame)
is_begin = True

while(1):
     ret,frame = cap.read()
     if frame is None:
         break
     processed = frame

     if is_begin:
         h, w, _ = processed.shape
         out = cv2.VideoWriter(output_file, fourcc, 30, (w, h), True)
         is_begin = False

     frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) 
    # calculate optical flow
     p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)

     # Select good points
     good_new = p1[st==1]
     good_old = p0[st==1]

     # draw the tracks
     for i,(new,old) in enumerate(zip(good_new,good_old)):
         a,b = new.ravel()
         c,d = old.ravel()
         mask = cv2.line(mask, (a,b),(c,d), color[i].tolist(), 2)
         frame = cv2.circle(frame,(a,b),5,color[i].tolist(),-1)
     img = cv2.add(frame,mask)

     out.write(img)
     cv2.imshow('frame',img)
     k = cv2.waitKey(30) & 0xff
     if k == 27:
         break

     # Now update the previous frame and previous points
     old_gray = frame_gray.copy()
     p0 = good_new.reshape(-1,1,2)


cv2.destroyAllWindows()
cap.release()

它将使用跟踪线保存文件。

如何在python opencv中保存光流输出？

1 个答案: