Video Frame Extractor

This repository contains a Python script that extracts still images from a given video file. The extracted images are placed in a subdirectory named "TrainingImages." The script is designed to generate an image every half second of the video, making it suitable for training a YOLOv8 object recognition model.

Table of Contents

• Prerequisites
• Installation
• Usage
• Contributing
• License

Prerequisites

• Python 3: The script is written in Python 3 and requires it to be installed on your system.
• ffmpeg: The script uses the ffmpeg command-line tool to process the video file. It must be installed on your system.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/videoframe-extractor.git

2. Navigate to the directory:

   cd videoframe-extractor

3. Install ffmpeg (if not already installed): On macOS, you can install ffmpeg using Homebrew:

   brew install ffmpeg

Usage

1. Make the script executable (optional):

   chmod +x extract_images.py

2. Run the script with the path to the video file:

   python extract_images.py path_to_video_file

   Replace path_to_video_file with the actual path to the video file you want to process.

3. Find the extracted images: The extracted images will be saved in the "TrainingImages" subdirectory within the current directory.

Contributing

Feel free to fork the repository, make changes, and submit pull requests. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

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