mv

Live video ML pipeline toolbox.

To install: pip install mv

Make it easy to build components for live video processing, to compute video features, run ML models, and display results.

Examples

Record video from camera

from mv.util import record_video_from_camera

# To record and save to a file (auto-named if not given):
record_video_from_camera()  # Press ESC or Ctrl+C to stop

# Or specify a filename:
record_video_from_camera("my_recording.mp4")

Reverse video

import mv.wip.video_transforms as vt

reversed_video_path = vt.reverse_video_w_moviepy("input.mp4", "output.mp4")

or, with only builtins (but you need ffmpeg installed on your system)

import mv.wip.video_transforms as vt

reversed_video_path = vt.reverse_video_w_ffmpeg("input.mp4", "output.mp4")

OverlayManager: Manages persistent overlays on video frames.

To see examples of use, run mv.wip.live_qr_codes.run_example_with_qr_detector(...) or from terminal, python ...path_to__live_qr_codes__module

More examples (for images)

Make qr code

>>> qr_img = create_qr_code("https://www.example.com")  # doctest: +SKIP
>>> qr_img.size  # doctest: +SKIP
(410, 410)

grid_image: Create a grid of images from a list of images.

>>> from PIL import Image
>>> img1 = Image.new('RGB', (100, 100), color='red')
>>> img2 = Image.new('RGB', (100, 100), color='blue')
>>> img3 = Image.new('RGB', (100, 100), color='green')
>>> img4 = Image.new('RGB', (100, 100), color='yellow')
>>> imgs = [img1, img2, img3, img4]
>>> grid = grid_image(imgs, n_rows=2, n_cols=2, v_padding=10, h_padding=10)
>>> grid.size  # Check the size of the resulting grid image
(220, 220)