Make timelapses easily using FFmpeg

Note of support: ffmpeg supported many of the transcoding needs of my former employer back in 2007, being a "friendly" tool to the team. Yes it had/s issue. Being open source gave us a lifeline, to be able to fix our own stuff, and build up our video and audio live streaming and video watching white label service.

> The sortedness of glob.glob's output is platform-dependent.

https://bugs.python.org/issue33275#msg315254

https://pubs.acs.org/doi/10.1021/acs.orglett.9b03216

see https://trac.ffmpeg.org/wiki/Concatenate or https://shotstack.io/learn/use-ffmpeg-to-concatenate-video/

    ffmpeg -framerate 30 -pattern_type glob -i '*.jpg' -c:v libx264 -pix_fmt yuv420p out.mp4

Also as an FYI to everyone, FFmpeg does support nVidia GPU acceleration but it might not be enabled in your build. So check if you use it a lot.

Worth a try!

    ffmpeg -ss 00:01:00 -i input.avi -t 30 -vf "fps=1,scale=320:-1:flags=lanczos" output_%04d.jpg

brew install homebrew-ffmpeg/ffmpeg/ffmpeg $(brew options homebrew-ffmpeg/ffmpeg/ffmpeg --compact)

    $ ffmpeg-english "capture video from the camera every 1 second and write it to jpg files"
    $ ffmpeg-english "take all of the images ending with .jpg in this directory and make a 30fps timelapse of it"

    #!/usr/bin/env python3

    import openai
    import sys
    import os
    import time

    # Ensure you have set your OpenAI API key as an environment variable
    openai.api_key = os.getenv("OPENAI_API_KEY")
    client = openai.OpenAI()

    def get_ffmpeg_command(task_description):
        # Call the OpenAI API with the task description
        response = client.chat.completions.create(
            model="gpt-4",
            messages=[
                {"role":"system", "content":"You are an expert in FFmpeg commands. Given the following English description of a task, you respond with the correct FFmpeg command. Do not include any other information in your response except for the command only."},
                {"role":"user", "content":task_description},
            ],
            max_tokens=150,
            temperature=0.5
        )
        command = response.choices[0].message.content.strip()
        return command

    def main():
        if len(sys.argv) < 2:
            print("Usage: ffmpeg-english <task_description>", file=sys.stderr)
            sys.exit(1)

        task_description = " ".join(sys.argv[1:])
        ffmpeg_command = get_ffmpeg_command(task_description)

        # some basic guardrails
        assert(ffmpeg_command.startswith("ffmpeg"))
        assert(";" not in ffmpeg_command)
        assert("|" not in ffmpeg_command)

        print(f"Executing command: {ffmpeg_command} in 2 seconds (^C to cancel)")
        time.sleep(2)
        os.system(ffmpeg_command)

    if __name__ == "__main__":
        main()

Try encoding the video to AV1 with OPUS audio. You'll get ridiculous gainz!

My command is:

    $ffmpegPath -i $_.FullName -r 23.976 -vf scale=1280:720 -c:v libsvtav1 -pix_fmt yuv420p10le -crf 30 -preset 10 -g 300 -c:a libopus -b:a 96k -ac 2 -c:s copy -map 0 $destPath

Noise reduction, so you compress less useless noise: -vf hqdn3d

Turn up the Constant Rate Factor. This will make better visual tradeoffs than decreasing frame rate. 23 is a good starting point for h264, but keep increasing it until you don't like how the content looks: -crf 23

Throw more CPU at the problem: -preset veryslow

Ffmpeg can encode into ProRes, but it’s technically an unofficial implementation.

What issues do you run into with image sequences?

I press shift-s to take a snapshot, not sure if that's a default hotkey or I set it to that a long time ago.

In the preferences you choose where it will save to and what format.