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This package allows handling of .cine files created by Vision Research Phantom® cameras.

Project description

pycine

PyPI version GitHub license Code style: black Codacy Badge

Reading Vision Research .cine files with python

Installation

Release Version

With pip

If you have Python 3 installed you can just use pip:

pip3 install -U pycine

Development version

pip install git+https://github.com/ottomatic-io/pycine.git

Example usage

Changing the playback and timecode framerates

pfs_meta set --playback-fps 60/1.001 --timecode_fps 60/1.001 A001C001_190302_16001.cine

You can also set metadata for multiple clips at once:

pfs_meta set --playback-fps 24/1.001 --timecode_fps 24/1.001 *.cine

Help

Every command has its own help output. Just append --help:

$ pfs_meta --help
Usage: pfs_meta [OPTIONS] COMMAND [ARGS]...

  This tool allows .cine file metadata manipulation. Use COMMAND --help for
  more info.

Options:
  --help  Show this message and exit.

Commands:
  copy  Copy metadata from a source clip
  set   Set metadata
  show  Show metadata
$ pfs_meta set --help
Usage: pfs_meta set [OPTIONS] [DESTINATIONS]...

  Set metadata

Options:
  --temp FLOAT          Set color temperature.
  --cc FLOAT            Set color correction.
  --record-fps INTEGER  Set record FPS.
  --playback-fps TEXT   Set playback FPS. Use 60 or 60/1.001 but not 59.94
  --timecode-fps TEXT   Set timecode FPS. Use 60 or 60/1.001 but not 59.94
  --tone TEXT           Set tone curve in the form of "[LABEL] x1 y1 x2 y2".
                        You can set up to 32 xy points.
  --help                Show this message and exit.
$ pfs_raw --help
Usage: pfs_raw [OPTIONS] CINE_FILE [OUT_PATH]

Options:
  --file-format [.png|.jpg|.tif]
  --start-frame INTEGER
  --count INTEGER
  --version                       Show the version and exit.
  --help                          Show this message and exit.

Jupyter notebook

Check out an example on how to use the library from a jupyter notebook: notebooks/Display frames.ipynb

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