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• avcodec/libjxl.h : include version.h

  23 janvier 2024, par Leo Izen

  avcodec/libjxl.h : include version.h
  This file has been exported since our minimum required version (0.7.0),
  
  but it wasn't documented. Instead it was transitively included by
  
  <jxl/decode.h> (but not jxl/encode.h), which ffmpeg relied on.
  libjxl broke its API in libjxl/libjxl@66b959239355aef5255 by removing
  
  the transitive include of version.h, and they do not plan on adding
  
  it back. Instead they are choosing to leave the API backwards-
  
  incompatible with downstream callers written for some fairly recent
  
  versions of their API.
  As a result, we include <jxl/version.h> to continue to build against
  
  more recent versions of libjxl. The version macros removed are also
  
  present in that file, so we no longer need to redefine them.
  Signed-off-by : Leo Izen <leo.izen@gmail.com>
  

  • [DH] libavcodec/libjxl.h

• How to read frames of a video and write them on another video output using FFMPEG and nodejs

  29 décembre 2023, par Aviato

  I am working on a project where I need to process video frames one at a time in Node.js. I aim to avoid storing all frames in memory or the filesystem due to resource constraints. I plan to use the ffmpeg from child processes for video processing.
I tried reading a video file and then output frames of it in the filesystem first for testing purposes :-

  


  const ffmpegProcess = spawn('ffmpeg', [
  '-i', videoFile,
  'testfolder/%04d.png' // Output frames to stdout
]);


  


  and the above code works fine, it saves the video frames as png files in the filesystem. Now instead of saving them in the file system, I want to read the frames on at a time and use a image manipulation library and than write the final edited frames to another video as output

  


  I tried this :-

  


  const ffmpegProcess = spawn('ffmpeg', [
  '-i', videoFile,
  'pipe:1' // Output frames to stdout
]);

const ffmpegOutputProcess = spawn('ffmpeg', [
  '-i', '-',
  'outputFileName.mp4'
  ]);

ffmpegProcess.stdout.on('data', (data) => {
  // Process the frame data as needed
  console.log('Received frame data:');
  ffmpegOutputProcess.stdin.write(data)
});

ffmpegProcess.on('close', (code) => {
  if (code !== 0) {
    console.error(`ffmpeg process exited with code ${code}`);
  } else {
    console.log('ffmpeg process successfully completed');
    
  }
});

// Handle errors
ffmpegProcess.on('error', (err) => {
  console.error('Error while spawning ffmpeg:', err);
});


  


  But when I tried above code and also some other modifications in the input and output suffix in the command I got problems as below :-

  


  

  1. ffmpeg process exited with code 1

  


  2. The final output video was corrupted when trying to initializing the filters for commands :-

  


  


  
const ffmpegProcess = spawn('ffmpeg', [
 '-i', videoFile,
 '-f', 'rawvideo',
 '-pix_fmt', 'rgb24',
 'pipe:1' // Output frames to stdout
]);

const ffmpegOutputCommand = [
 '-f', 'rawvideo',
 '-pix_fmt', 'rgb24',
 '-s', '1920x1080',
 '-r', '30',
 '-i', '-',
 '-c:v', 'libx264',
 '-pix_fmt', 'yuv420p',
 outputFileName
];


  


  Thank you so much in advance :)

  


• 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 !