Video Stitcher

A Python application for creating ultra-high-resolution images from video captures.

Project Overview

This tool processes multiple video captures of a scene and stitches them together to create a single ultra-high-resolution image. The application implements several computer vision techniques including:

• Video frame extraction
• Feature detection and matching
• Image alignment and transformation
• Seamless image blending
• Interactive image viewer with zoom capabilities

Prerequisites

• Python 3.8 or higher
• Git (for cloning the repository)
• pip (Python package installer)

Project Setup

1. Clone the Repository

git clone https://github.com/yourusername/video-stitcher.git
cd video-stitcher

2. Create a Virtual Environment

We use Python's built-in venv module to create an isolated environment:

On Windows:

python -m venv venv
venv\Scripts\activate

On macOS/Linux:

python -m venv venv
source venv/bin/activate

You'll see (venv) appear at the beginning of your command prompt, indicating the environment is active.

3. Install Dependencies

With the virtual environment activated, install the required packages:

pip install -r requirements.txt
pip install -e .

The -e flag installs the package in development mode, allowing you to modify the code without reinstalling.

4. VS Code Configuration

If you're using VS Code (recommended):

1. Open the project folder in VS Code
2. Press Ctrl+Shift+P (Windows/Linux) or Cmd+Shift+P (Mac)
3. Type "Python: Select Interpreter" and select that option
4. Choose the interpreter from your virtual environment (it should show something like 'venv':venv)

VS Code will now use the correct Python interpreter with all installed dependencies.

Project Structure

video-stitcher/
├── requirements.txt     # Project dependencies
├── setup.py            # Package configuration
├── README.md           # This file
├── src/                # Source code
│   └── video_stitcher/ # Main package
│       └── __init__.py # Package initialization
└── tests/              # Unit tests
    └── __init__.py     # Test package initialization

Development Workflow

1. Ensure your virtual environment is activated before working on the project
2. Run tests with pytest from the project root
3. Install any new dependencies with pip install <package> and then add them to requirements.txt

Deactivating the Environment

When you're done working on the project, you can deactivate the virtual environment:

deactivate

License

MIT