I want to detect obstacles from a video based on their increasing size.To do that first I applied SIFT on gray image to get feature points of current frame. Next to compare the feature points of current frame with the previous frame I want to apply Brute-Force algorithm. For that I want to get feature points in previous frame. How can I access previous frame in opencv python ? and how to avoid accessing previous frame when the current frame is the first frame of the video?
below is the code written in python to get feature points of current frame.
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()
You could also get/set the zero-based frame index (CAP_PROP_POS_FRAMES), which might be useful if you wanted flexibility to step back through more than one frame, compare to a specific frame, etc. Note though that this would reset the position for the next read(), so if you really only ever want the previous frame, storing it in a variable per the other answers is probably better.
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()
There is no specific function in OpenCV to access the previous frame. Your problem can be solved by calling cap.read()
once before entering the while loop. Use a variable prev_frame
to store the previous frame just before reading the new frame. Finally, as a good practice, you should verify that the frame was properly read, before doing computations on it. Your code could look something like:
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()
Simply save the current frame to be the previous frame in the next iteration. Use a list, if you need more than 1.
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()
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