我想根据视频中不断增加的size.To来检测障碍物。首先,我对灰度图像应用SIFT,以获得当前帧的特征点。接下来,为了比较当前帧和前一帧的特征点,我想应用Brute-Force算法。为此,我想在前一帧中获得特征点。如何在opencv python中访问上一帧?当当前帧是视频的第一帧时,如何避免访问前一帧?
下面是用python编写的代码,用于获取当前帧的特征点。
import cv2
import numpy as np
cap = cv2.VideoCapture('video3.mov')
while(cap.isOpened()):
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#detect key feature points
sift = cv2.xfeatures2d.SIFT_create()
kp, des = sift.detectAndCompute(gray, None)
#draw key points detected
img=cv2.drawKeypoints(gray,kp,gray,flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imshow("grayframe",img)
if cv2.waitKey(100) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
发布于 2017-12-30 01:29:55
OpenCV中没有特定的函数来访问上一帧。您的问题可以通过在进入while循环之前调用一次cap.read()
来解决。在读取新帧之前,使用变量prev_frame
存储前一帧。最后,作为一种良好的实践,在对帧进行计算之前,您应该验证帧是否被正确读取。您的代码可能如下所示:
import cv2
import numpy as np
cap = cv2.VideoCapture('video3.mov')
ret, frame = cap.read()
while(cap.isOpened()):
prev_frame=frame[:]
ret, frame = cap.read()
if ret:
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#detect key feature points
sift = cv2.xfeatures2d.SIFT_create()
kp, des = sift.detectAndCompute(gray, None)
#some magic with prev_frame
#draw key points detected
img=cv2.drawKeypoints(gray,kp,gray, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imshow("grayframe",img)
else:
print('Could not read frame')
if cv2.waitKey(100) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
发布于 2018-06-08 05:38:55
您还可以获取/设置从零开始的帧索引(CAP_PROP_POS_FRAMES),如果您希望灵活地后退到多个帧、与特定帧进行比较等,这可能会很有用。请注意,这将重置下一个read()的位置,因此如果您真的只想要前一帧,则根据其他答案将其存储在变量中可能更好。
next_frame = cap.get(cv2.CAP_PROP_POS_FRAMES)
current_frame = next_frame - 1
previous_frame = current_frame - 1
if previous_frame >= 0:
cap.set(cv2.CAP_PROP_POS_FRAMES, previous_frame)
ret, frame = cap.read()
发布于 2017-12-30 00:53:57
只需将当前帧保存为下一次迭代中的前一帧。如果您需要1个以上的列表,请使用列表。
import cv2
import numpy as np
cap = cv2.VideoCapture('video3.mov')
previousFrame=None
while(cap.isOpened()):
ret, frame = cap.read()
if previousFrame is not None:
#use previous frame here
pass
#save current frame
previousFrame=frame
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#detect key feature points
sift = cv2.xfeatures2d.SIFT_create()
kp, des = sift.detectAndCompute(gray, None)
#draw key points detected
img=cv2.drawKeypoints(gray,kp,gray,flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imshow("grayframe",img)
if cv2.waitKey(100) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
https://stackoverflow.com/questions/48025689
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