https://github.com/toolshive/forensi-frame
Video Frame Extraction Too
https://github.com/toolshive/forensi-frame
Last synced: 2 months ago
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Video Frame Extraction Too
- Host: GitHub
- URL: https://github.com/toolshive/forensi-frame
- Owner: ToolsHive
- License: mit
- Created: 2025-03-08T04:06:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-10T01:34:02.000Z (over 1 year ago)
- Last Synced: 2025-12-25T18:58:41.672Z (6 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 1.59 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Video Frame Extractor 🎥
A high-performance Python tool for extracting frames from video files with multi-threading support and rich visualization features.
## 📑 Table of Contents
- [Features](#-features)
- [Process Flow](#-process-flow)
- [Prerequisites](#-prerequisites)
- [Virtual Environment Setup](#-virtual-environment-setup)
- [Installation](#-installation)
- [Usage](#-usage)
- [Command Line Interface](#command-line-interface)
- [Arguments](#arguments)
- [Jupyter Notebook](#jupyter-notebook)
- [Output](#-output)
- [Contributing](#-contributing)
- [License](#-license)
- [Acknowledgments](#-acknowledgments)
## 🚀 Features
- Multi-threaded frame extraction for optimal performance
- Real-time progress tracking with Rich console
- Detailed video metadata display
- Cross-platform compatibility
- Configurable thread count
- Robust error handling
- Jupyter Notebook integration support
## 🔄 Process Flow
## 📋 Prerequisites
- Python 3.6 or higher
- Required packages for CLI:
```bash
pip install opencv-python rich
```
- Additional packages for Jupyter Notebook:
```bash
pip install numpy matplotlib jupyter ipython
```
## 🔮 Virtual Environment Setup
1. Create a virtual environment:
```bash
python -m venv venv
```
2. Activate the virtual environment:
Windows:
```bash
.\venv\Scripts\activate
```
Linux/Mac:
```bash
source venv/bin/activate
```
3. Verify activation (you should see (venv) in your terminal):
```bash
python --version
```
## 💻 Installation
1. Clone or download this repository
```bash
git clone https://github.com/ToolsHive/Forensi-Frame.git
```
2. Install all dependencies:
```bash
pip install -r requirements.txt
```
## 🔧 Usage
### Command Line Interface
```bash
python script.py [--threads N]
```
### Example:
```bash
python script.py sample.mp4 frames --threads 8
```
### Arguments
- `video_path`: Path to the input video file
- `output_directory`: Directory where extracted frames will be saved
- `--threads`: Number of threads to use (default: 4)
### Jupyter Notebook
You can also use the provided Jupyter notebook `Video_Frame_Extractor.ipynb` for an interactive experience with additional visualization features.
## 📊 Output
- Frames are saved as sequential JPEG images
- Naming format: `frame_XXXX.jpg`
- Video metadata is displayed in a formatted table
- Progress bar shows extraction status
## 👥 Contributing
1. Fork the repository
2. Create feature branch (`git checkout -b feature/name`)
3. Commit changes (`git commit -am 'Add feature'`)
4. Push branch (`git push origin feature/name`)
5. Create Pull Request
## 📜 License
This project is licensed under the MIT License - see the LICENSE file for details.
## 🙏 Acknowledgments
- OpenCV for video processing capabilities
- Rich library for terminal visualization
- Python's concurrent.futures for multi-threading support