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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

Table of Contents

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:

    git clone https://github.com/supriya811106/Garbage-Classification-System.git

  2. Navigate to the cloned repository:

    cd Garbage-Classification-System

  3. Install the required dependencies:

    pip install -r requirements.txt

Usage

  1. Running the Notebook:

    • Ensure you have Jupyter Notebook or Jupyter Lab installed. If not, install it:

      pip install jupyterlab

    • Launch Jupyter:

      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.