Read/write/show images and videos in an IPython/Jupyter notebook.

Examples:

Images:

    !pip install -q mediapy
    import mediapy as media
    import numpy as np

    image = media.read_image('https://github.com/hhoppe/data/raw/main/image.png')
    print(image.shape, image.dtype)  # It is a numpy array.
    media.show_image(image)

    checkerboard = np.kron([[0, 1] * 16, [1, 0] * 16] * 16, np.ones((4, 4)))
    media.show_image(checkerboard)

    media.show_image(media.color_ramp((128, 128)), height=48, title='ramp')

    images = {
        'original': image,
        'brightened': media.to_float01(image) * 1.5,
    }
    media.show_images(images)

    media.write_image('/tmp/checkerboard.png', checkerboard)

Videos:

    url = 'https://github.com/hhoppe/data/raw/main/video.mp4'
    video = media.read_video(url)
    print(video.shape, video.dtype)  # It is a numpy array.
    print(video.metadata.fps)  # The 'metadata' attribute includes framerate.
    media.show_video(video)  # Play the video using the retrieved framerate.

    media.show_images(video, height=80, columns=4)  # Show frames side-by-side.

    video = media.moving_circle((128, 128), num_images=10)
    media.show_video(video, fps=10)

    media.write_video('/tmp/video.mp4', video, fps=60)

    # Darken a video frame-by-frame:
    filename_in = '/tmp/video.mp4'
    filename_out = '/tmp/out.mp4'
    with media.VideoReader(filename_in) as r:
      print(f'shape={r.shape} fps={r.fps} bps={r.bps}')
      darken_image = lambda image: media.to_float01(image) * 0.5
      with media.VideoWriter(
          filename_out, shape=r.shape, fps=r.fps, bps=r.bps) as w:
        for image in r:
          w.add_image(darken_image(image))
    media.show_video(media.read_video(filename_out), fps=60)

Setup:

    apt install ffmpeg

    !command -v ffmpeg >/dev/null || (apt update && apt install -y ffmpeg)