parallel-minterpolate

Parallelize video frame interpolation with FFmpeg.

Table of Contents

• Table of Contents
• Prerequisites
• Installation
• Description
• Options
• Examples
• Usage
• Contributing
• License

Prerequisites

• Windows only
• FFmpeg
• Python version 3.6+
• Installed opencv-python dependency:

  pip3 install opencv-python

• Only works with MP4 videos

Installation

Retrieve the Python script:

• by cloning the repository:

  git clone https://github.com/Bryght7/parallel-minterpolate.git

• or directly retrieving the parallel-minterpolate.py source file.

Description

parallel-minterpolate is a command-line program to help the user speed up the process of applying frame interpolation to longer videos, using the minterpolate filter from FFmpeg.

As that filter is only single threaded, a common practice is to split the videos into smaller chunks, process those in parallel, and join them back together. This tool generates and runs all the needed commands to do this, all at once.

py parallel-minterpolate.py inputVideo --split N [OPTIONS]

Options

positional arguments:
  inputVideo            an input video file

options:
  -h, --help            show this help message and exit
  --split N             number of tasks to generate equally
  -o, --outputDir NAME  name of the output directory, default='output'
  --fps N               target FPS, default=60
  --shutdown            shutdown computer after tasks are completed

Examples

py parallel-minterpolate.py input.mp4 --split 5

👆 Split the video input.mp4 into 5 roughly equal chunks, apply the minterpolate filter to them, and join them back together.

py parallel-minterpolate.py input.mp4 --split 5 --shutdown

👆 Same but the computer shuts down when it is done. Useful for overnight tasks.

Usage

After executing the Python script, with option --split 5 for example, you should see 5 different command-line windows open, those are the parallel frame interpolation tasks. Do not close any of them and let them work.

When it is finished, everything should auto close, and you should see the result as a final.mp4 file inside an newly created output directory (this can be changed using the -o option).

Contributing

This script was originally developed hastily and without any serious testing. Therefore it probably contains bugs, may not work under all circumstances, or lack many options/features. Any contributions you make to improve this script are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m '✨ Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.md for more information.