Somehow feed it to different pipes and make ffmpeg read from them.So, our conclusion is that we're getting bottlenecked by stdin and hence are looking for ways to pass input through multiple sources or somehow help ffmpeg to parallelize this effort - a few options that we're thinking of: Earlier when we were taking input as -pattern_type glob -i images/*.png we were getting around 1x-1.2x for this on a single core. The current speed of this process is ~0.135x which is a huge bottleneck for us. # put the frame in stdin so that it gets ready Here is a sample example of passing the image to FFMPEG proc stdin as: # wait for the next frame to get readyįrame = cv2.imread(frame_path, cv2.IMREAD_UNCHANGED) Proc = subprocess.Popen(args, stdin=subprocess.PIPE) # /usr/bin/ffmpeg -hide_banner -y -loglevel info -f rawvideo -pix_fmt bgra -s 1573x900 -framerate 30 -i -i audio.wav -c:v libvpx -b:v 0 -crf 30 -tile-columns 2 -quality good -speed 4 -threads 16 -auto-alt-ref 0 -g 300000 -map 0:v:0 -map 1:a:0 -shortest video.webm This is the current command, in python syntax: But we now want to pipeline these images to FFmpeg to encode into the WebM video simultaneously as the images are being spewed out so that we don't wait for ffmpeg to encode all the images afterwards. Right now, we're waiting for all the images and then encoding them with ffmpeg into a webm video file with vp8 ( libvpx encoder).
We've a system that spews out 4-channel png images frame-by-frame (we control the output format of these images as well, so we can use something else as long as it supports transparency).
0 kommentar(er)
