I am currently working on keyframe extraction from videos.
Code :
while success:
success, currentFrame = vidcap.read()
isDuplicate = False
limit = count if count <= 10 else (count - 10)
for img in xrange(limit, count):
previusFrame = cv2.imread("%sframe-%d.png" % (outputDir, img))
try:
difference = cv2.subtract(currentFrame, previusFrame)
except:
pass
This gives me huge amounts of frames. Expected ouput: Calculate pixel difference between frames and then compare it with a threshold value and store unique keyframes.
Working on videos for the first time. please guide on how to proceed to achieve the expected output
Here is a script to extract I-frames with ffprobe and OpenCV:
import os
import cv2
import subprocess
filename = '/home/andriy/Downloads/video.mp4'
def get_frame_types(video_fn):
command = 'ffprobe -v error -show_entries frame=pict_type -of default=noprint_wrappers=1'.split()
out = subprocess.check_output(command + [video_fn]).decode()
frame_types = out.replace('pict_type=','').split()
return zip(range(len(frame_types)), frame_types)
def save_i_keyframes(video_fn):
frame_types = get_frame_types(video_fn)
i_frames = [x[0] for x in frame_types if x[1]=='I']
if i_frames:
basename = os.path.splitext(os.path.basename(video_fn))[0]
cap = cv2.VideoCapture(video_fn)
for frame_no in i_frames:
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_no)
ret, frame = cap.read()
outname = basename+'_i_frame_'+str(frame_no)+'.jpg'
cv2.imwrite(outname, frame)
print ('Saved: '+outname)
cap.release()
else:
print ('No I-frames in '+video_fn)
if __name__ == '__main__':
save_i_keyframes(filename)
You can change 'I'
to 'P'
if you need to extract P-frames.
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