Smart Waste Classifier

Overview

The Smart Waste Classifier is a Convolutional Neural Network (CNN) designed to classify waste into three categories: organic, recyclable, and trash. This project processes over 30,000 images to enhance waste identification efficiency using advanced preprocessing and machine learning techniques.

Features

• Three Categories: Organic, recyclable, and trash.
• Preprocessing: Images are converted to grayscale, resized to 128x128 pixels, and normalized.
• CNN Architecture: Incorporates convolutional layers, max-pooling, dropout, and a softmax output layer.
• Metrics: Reports accuracy and a detailed classification report.

Dataset

Ensure your dataset is organized as follows:

Project/ ├── organic/ │ ├── image1.jpg │ ├── image2.jpg │ └── ... ├── recyclable/ │ ├── image1.jpg │ ├── image2.jpg │ └── ... ├── trash/ │ ├── image1.jpg │ ├── image2.jpg

Installation and Setup

Prerequisites

• Python 3.7 or higher
• Required Libraries:
  • TensorFlow
  • NumPy
  • scikit-learn
  • Pillow