# 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](https://huggingface.co/spaces/HMWCS/Gemma3n-challenge-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](https://www.kaggle.com/code/yichuanhuang/gemma3n-challenge)**

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## 🛠️ Getting Started

### Prerequisites

  * Python 3.9+
  * Pip
  * Cuda (optional)

### Installation

1.  Clone the repository:
    ```bash
    git clone https://github.com/yichuan-huang/gemma3n-challenge
    ```
2.  Navigate to the project directory:
    ```bash
    cd gemma3n-challenge
    ```
3.  Install the required dependencies:
    ```bash
    pip install -r requirements.txt
    ```

### Running the application

To start the application, run the following command:

```bash
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.