https://github.com/dpbm/extract_frames

extract frames from videos
https://github.com/dpbm/extract_frames

frames frames-extract linux numpy opencv pip pipenv py python python-opencv python3 simple-program study terminal tool video videos

Last synced: 14 days ago
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extract frames from videos

• Host: GitHub
• URL: https://github.com/dpbm/extract_frames
• Owner: Dpbm
• Created: 2020-12-06T22:59:09.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2023-12-21T22:50:59.000Z (about 1 year ago)
• Last Synced: 2024-11-18T21:43:48.864Z (3 months ago)
• Topics: frames, frames-extract, linux, numpy, opencv, pip, pipenv, py, python, python-opencv, python3, simple-program, study, terminal, tool, video, videos
• Language: Python
• Homepage: https://dpbm.github.io/extract_frames/
• Size: 9.77 KB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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README

        
# extract frames from a mp4 video

https://github.com/Dpbm/extract_frames/assets/75098594/789637b4-6ba7-488a-95d2-07de1737251a

This is an old project of mine, using python, to extract frames from videos.

The idea here is an automate this process, and learning something about [Pillow](https://pillow.readthedocs.io/en/stable/) and [OpencvPython](https://pypi.org/project/opencv-python/).

## Requirements

To run that you need to have installed in your machine:

* python3 (3.8)

* pip

* git

Using [Pipenv](https://pipenv.pypa.io/en/latest/) or [conda](https://www.anaconda.com/) is optional here, but recommended.

## Installation

To install this project:

1. clone this repo

```bash

git clone https://github.com/Dpbm/extract_frames.git

cd extract_frames

```

3. install dependencies

```bash

# using pip

pip install -r requirements.txt

# using conda

conda env create -f enviroment.yml

conda activate extract_frames

# using pipenv

pipenv install

pipenv shell

```

## Using

In the project directory run:

```bash

python3 main.py

```

Then provide the `folder path` where the videos are and the `salt number`, this number provides how much time you need to wait before getting a frame.

The resulting images are put inside the directory `./frames`

`Note: this scripts run over a folder, not a single file!` 

--- 

For sure, this is a too simple project, and all this could be done so much better using [ffmpeg](https://ffmpeg.org/) or similar. However, this project I've made a couple of year ago, and I don't intend to update it for now.

If you want to update this project by yourself, I'll be pleasured to accept your pull request :)