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• Is there a faster way to generate video from pixel arrays using python and ffmpeg ?

  8 mai 2019, par devneal17

  I’ve found a few sources which use python and ffmpeg to generate video from pixel arrays by passing the -f rawvideo flag 1 2. However, this is very slow for high-definition video since each individual pixel must be piped into ffmpeg.

  In fact this is provably wasteful, as I’ve found that 2.5Gb of pixel arrays generates about 80Kb of video. I’ve also chanced upon some examples where javascript can render high quality animations in near-real time 1, which makes me even more suspicious that I’m doing something wrong.

  Is there a way to do this more efficiently, perhaps by piping the differences between pixel arrays into ffmpeg rather than the pixels themselves ?

  (edit) This is the line I’m using. Most executions take the else path that follows.

• Processing video frame by frame in AWS Lambda with Node.js and FFmpeg [closed]

  29 décembre 2023, par Aviato

  I am working on a project where I need to process video frames one at a time in an AWS Lambda function using Node.js. My goal is to avoid storing all frames in memory or the filesystem due to resource constraints. I plan to use the fluent-ffmpeg library or ffmpeg from child processes for video processing.

  


  In the past, I used OpenCV to process videos and frames without writing the frames on the disk or storing all the frames at once on the memory itself. But now as I am using node js, its a little hard to set up the code using ffmpeg, etc.

  


  Here is a small snippet from what I did with opencv :-

  


  import cv2

cap = cv2.VideoCapture(video_file)

out = cv2.VideoWriter('output.mp4', fourcc, fps, (width, height))

def generate_frame():
        while cap.isOpened():
            code, frame = cap.read()
            if code:
                yield frame
            else:
                print("completed")
                break

for i, frame in enumerate(generate_frame()):
          # Now we can process the video frames directly and write them on the output opencv
          out.write(editing_frames)


  


  Additionally, I intend to leverage image processing libraries like Sharp and the Canvas API to edit individual frames before assembling the final video. I am looking for help in handling video frames efficiently within the constraints of AWS Lambda.

  


  Any insights, code snippets, or recommendations would be greatly appreciated. Thank you !

  


• How to get the last x seconds with high accuracy with FFmpeg ?

  16 novembre 2024, par rbarab

  I would like to batch process mp4 videos, getting the last x seconds of each and saving them to individual files.
I need to do this with a very high accuracy, preferably to 0.001 seconds or better.
Found a related question (FFmpeg : get the last 10 seconds) suggesting -sseof, which works great, but as the answer said it's not completely accurate with stream copy.

  


  I am trying to match video lengths to the length of a reference video.

  


  Would I need to re-encode ? Can sseof handle this accurate enough if I specify duration as 00:00:00.000000 (which I get from reference video ffprobe) ?

  


  Please see related ffprobe -i below, all videos to be processed have this same encoding.

  


     Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf57.83.100
  Duration: 00:00:58.67, start: 0.000000, bitrate: 639 kb/s
    Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p, 640x360, 499 kb/s, 29.97 fps, 29.97 tbr, 30k tbn, 59.94 tbc (default)
    Metadata:
      handler_name    : VideoHandler
    Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 131 kb/s (default)
    Metadata:
      handler_name    : SoundHandler
duration=58.673000


  


  Is there a better way to achieve frame-level accuracy ? As end goal I would need to overlay these videos with 25fps 'frame-level accuracy'.