README.md

Waste Classification Application

This project is a web-based application that classifies waste materials from user-uploaded images. It identifies the type of waste (e.g., cardboard, glass, metal) and provides information on how to properly dispose of it.

🚀 Live Demo

Try the application live on Hugging Face Spaces!

➡️ Waste Classification Demo

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✨ Features

• Image-based classification: Upload an image of a waste item to have it automatically classified.
• Multiple waste categories: The application can identify a variety of waste materials.
• Disposal information: After classification, the app provides guidance on how to dispose of the identified waste material.
• Web interface: A user-friendly web interface built with Gradio makes the application easy to use.

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💡 How it works

The application uses a pre-trained Gemma3n (E2B) model to perform the image classification. The model has been fine-tuned on a dataset of waste images to accurately identify different materials. The disposal information is retrieved from a knowledge base within the application.

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📓 Kaggle Notebook

Explore the model fine-tuning process and the underlying code in our detailed Kaggle Notebook.

➡️ Gemma3n Challenge Notebook

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🛠️ Getting Started

Prerequisites

• Python 3.9+
• Pip
• Cuda (optional)

Installation

1. Clone the repository:

   git clone https://github.com/yichuan-huang/gemma3n-challenge
   

2. Navigate to the project directory:

   cd gemma3n-challenge
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

Running the application

To start the application, run the following command:

python app.py

This will launch a Gradio web server. You can access the application by opening the provided URL in your web browser.

📂 Project Structure

• app.py: The main application file, containing the Gradio interface and the classification logic.
• classifier.py: Handles the image classification using the pre-trained model.
• config.py: Contains configuration settings for the application, such as the model name and labels.
• knowledge_base.py: A simple knowledge base containing disposal information for different waste materials.
• requirements.txt: A list of the Python dependencies required to run the application.
• test_images/: A directory containing sample images for testing the application.