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VisionAI: Image Blur & Sharpness Classifier

VisionAI is a modern, high-performance web application designed to detect image quality. Using advanced Machine Learning and Computer Vision techniques, it accurately classifies images as either Sharp or Blurred.


Key Features

  • Modern Dark UI: Iconic glassmorphism design with a seamless user experience.
  • MLP Classifier: Powered by a Multi-Layer Perceptron model trained on extracted image features.
  • Real-time Analysis: Instant feedback on image clarity with confidence scoring.
  • Responsive Design: Optimized for both desktop and mobile viewing.

Technology Stack

  • Frontend: HTML5, Tailwind CSS (Modern Glass UI)
  • Backend: Python, Flask
  • Machine Learning: Scikit-learn (MLP Classifier), Joblib
  • Computer Vision: OpenCV (Sobel, Tenengrad Feature Extraction)
  • Deployment: Vercel (Serverless Functions)

How it Works

The application uses Feature Engineering to analyze the input image:

  1. Sobel Variance: Measures the intensity of edges.
  2. Tenengrad Mean: Evaluates the focus level of the image.
  3. ML Prediction: These features are fed into a pre-trained MLP model to determine the final class.

Getting Started

Prerequisites

  • Python 3.9+
  • A Vercel account for deployment.

Installation

  1. Clone the repository:
    git clone https://github.com
  2. Install dependencies: pip install -r requirements.txt
  3. Run locally : python api/index.py

فيديو VisionNeural

If you find this project useful or like the UI, feel free to drop a ⭐ on this repository. It means a lot!


About

VisionAI: A high-performance Image Quality Classifier built with Python and Flask. Utilizing an MLP (Multi-Layer Perceptron) model to instantly detect and distinguish between blurred and sharp images with high precision

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