🧠 Product Image Classification System

This project is a deep learning-based image classification system that predicts the category of fashion products from images. Built with a user-friendly Flask web interface, it allows users to upload product images and get real-time predictions. The model is trained using PyTorch on a labeled fashion dataset.

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Demo

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🎯 Features

• Classifies images into multiple fashion product categories:

  • T-shirts
  • Dresses
  • Jeans
  • Shorts
  • Heels
  • Sandals

• Easy-to-use web interface (Flask)

• Real-time image classification

• Responsive UI for quick testing

• Easily extendable for more categories

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🧠 Model Info

• Deep Convolutional Neural Network (CNN) built with PyTorch
• Trained on a curated Fashion Product Image Dataset
• Optimized with data augmentation and dropout for better generalization
• Achieves high accuracy on validation set

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💻 Tech Stack

• Python 3.10+ – Core programming language
• PyTorch – Model creation, training, and inference
• TorchVision – Image transformations like resizing, normalization, etc.
• Flask – Web framework to build and run the user-facing web app
• Jinja2 – Templating engine used via Flask for rendering HTML
• Pillow (PIL) – Image loading and format conversion in the web app
• HTML / CSS – Basic frontend styling (in templates/ and static/)
• OS – Used for file system operations (creating directories, paths, etc.)

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🚀 How to Use

1. Launch the web app:

   python app.py

2. Open your browser and go to: http://127.0.0.1:5000/

3. Upload an image of a product

4. Click Classify

5. View the predicted product category instantly!

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🌐 Deployment

Live Demo: https://product-classifier-63lq.onrender.com

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📦 Installation (for Local Use)

1. Clone the repository:

   git clone https://github.com/yourusername/Product_Classifier.git
   cd Product_Classifier

2. Install the dependencies:

   pip install -r requirements.txt

3. Run the app:

   python app.py

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📁 Project Structure

Product_Classifier/
├── app.py                  # Flask web application
├── model.pth               # Trained PyTorch model
├── static/                 # CSS & uploaded images
├── templates/              # HTML templates
├── utils.py                # Image preprocessing and model prediction
├── requirements.txt        # Python dependencies
├── README.md               # Project overview

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👩‍💻 Author

Insiya Fakhruddin AI & Deep Learning Enthusiast GitHub

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📜 License

This project is licensed under the MIT License – feel free to use, modify, and distribute.

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🙏 Acknowledgements

• Dataset: Fashion Product Images (public dataset)
• PyTorch for deep learning framework
• Flask for seamless deployment