# Garbage Classification System A machine learning system that classifies different types of waste materials into categories. It's built on TensorFlow and leverages the VGG16 model architecture for image classification. ![Sample Prediction](https://github.com/supriya811106/Garbage-Classification/assets/89856408/e85162e1-6e15-4409-8e43-9ddce1be3fb6) ## Table of Contents - [Features](#features) - [Installation](#installation) - [Usage](#usage) ## Features - **VGG16 Model Architecture**: The project utilizes the power of the pre-trained VGG16 model for image classification. - **12 Waste Categories**: Classify waste into 12 distinct categories including cardboard, metal, paper, and more. - **Image Augmentation**: Uses `ImageDataGenerator` for real-time data augmentation. - **Visual Predictions**: Provides a visual representation of predictions using Matplotlib. ## Installation 1. Clone the repository: ```bash git clone https://github.com/supriya811106/Garbage-Classification-System.git ``` 2. Navigate to the cloned repository: ```bash cd Garbage-Classification-System ``` 3. Install the required dependencies: ```bash pip install -r requirements.txt ``` ## Usage 1. **Running the Notebook**: - Ensure you have Jupyter Notebook or Jupyter Lab installed. If not, install it: ```bash pip install jupyterlab ``` - Launch Jupyter: ```bash jupyter lab ``` - Navigate to the project notebook and run the cells to either train the model or make predictions. 2. **Classifying Waste**: - Use the `waste_prediction` function within the notebook to classify waste by providing the path to your image. ## Model The trained model is saved as `predictWaste12.h5` and can be loaded using TensorFlow/Keras for further predictions or improvements.