Computer Vision Scripts

This repository contains Python scripts demonstrating various computer vision techniques using OpenCV, NumPy, and Matplotlib.

Requirements

• Python 3.9
• OpenCV 4 (at least version 3)
• NumPy
• Matplotlib

Installation

1. Clone this repository:

   git clone https://github.com/yourusername/Computer-Vision-Scripts.git
   cd Computer-Vision-Scripts
   

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
   

3. Install the required dependencies:

   pip install opencv-python numpy matplotlib
   

Usage

Run each script independently:

python script_name.py

Notable Experiments

1. Color Histogram Computation from ROI

Computes color histograms from a Region of Interest in a webcam feed.

Key Features:

• Real-time processing with user-selectable ROI
• Multiple color space support (BGR, HSV, YCrCb)

2. Color-based Object Tracking

Tracks objects based on color using dynamic thresholding.

Key Features:

• Real-time tracking with color-based segmentation
• Morphological filtering for improved detection

3. Invisibility Cloak

Creates an "invisibility cloak" effect inspired by Harry Potter.

Key Features:

• Background subtraction and color-based segmentation
• Real-time invisibility effect

4. Histogram Equalization for BGR Images

Enhances contrast in color images using histogram equalization.

Key Features:

• Supports BGR color images
• Before and after comparison visualization

5. Vertical Pattern Segmentation

Segments vertical patterns in images using advanced filtering techniques.

Key Features:

• Combines Gabor filters, Otsu thresholding, and morphological operations
• Specialized for vertical pattern extraction