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Computer Vision Explorer

Streamlit App

A simple computer vision application that allows users to apply various image processing techniques and face detection to uploaded images.

App Screenshot

Features

  • Image Processing Techniques
    • Grayscale conversion
    • Gaussian blur with adjustable kernel size
    • Edge detection with adjustable thresholds
  • Face Detection
    • Detects faces in images using Haar Cascade classifier
    • Highlights detected faces with blue rectangles

Getting Started

Prerequisites

  • Python 3.7+
  • pip

Installation

  1. Clone the repository

    git clone https://github.com/yourusername/computer-vision-project.git
cd computer-vision-project

  2. Create and activate a virtual environment

    python -m venv venv

    On Windows:

    venv\Scripts\activate

    On macOS/Linux:

    source venv/bin/activate

  3. Install dependencies

    pip install -r requirements.txt

Usage

Running the Basic Image Processing Script

python image_processing.py

Running the Face Detection Script

python face_detection.py

Running the Streamlit App Locally

streamlit run app.py

Project Structure

computer-vision-project/
├── app.py                  # Streamlit web application
├── image_processing.py     # Basic image processing script
├── face_detection.py       # Face detection script
├── requirements.txt        # Project dependencies
├── assets/                 # Screenshots and images
├── README.md               # This file
└── .gitignore              # Git ignore file

Technologies Used

  • OpenCV - Open Source Computer Vision Library
  • NumPy - Numerical computing library
  • Matplotlib - Visualization library
  • Streamlit - Web application framework

Blog Post

For a detailed walkthrough of how this project was built, check out my blog post: Make Your First Computer Vision Project: A Step-by-Step Guide

Future Enhancements

  • Add more image processing techniques
  • Implement object detection
  • Create a real-time webcam version
  • Add image classification capabilities

License

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

Acknowledgments