Waste Classifier: Organic vs Recyclable Using Deep Learning

Introduction

Waste management is a crucial challenge in today's world, and proper classification of waste can significantly improve recycling efficiency. To address this issue, I have developed an Organic vs Recyclable Waste Classifier using Convolutional Neural Networks (CNNs). The model is deployed using Flask, with a user-friendly HTML and CSS interface.

Project Overview

This project aims to automatically classify waste into two categories:

• Organic Waste – Biodegradable waste such as food scraps, vegetable peels, and garden waste.
• Recyclable Waste – Non-biodegradable materials like plastic bottles, glass, metal, and paper.

Technology Stack

• Deep Learning Framework: TensorFlow/Keras (CNN-based model)
• Backend: Flask (Python-based web framework)
• Frontend: HTML & CSS
• Data Processing: NumPy, Pandas, OpenCV
• Visualization: Matplotlib, Seaborn

Model Development

1. Dataset Collection: The model is trained on an image dataset containing organic and recyclable waste categories.
2. Preprocessing: Images are resized, normalized, and augmented to improve model generalization.
3. CNN Architecture:
   • Multiple convolutional layers with ReLU activation
   • MaxPooling layers to reduce spatial dimensions
   • Fully connected layers for classification
   • Softmax activation for final categorization
4. Training & Evaluation:
   • The model is trained using categorical cross-entropy loss and Adam optimizer.
   • Achieved high accuracy by fine-tuning hyperparameters.

Deployment with Flask

A Flask API is created to serve the trained model. Users can upload an image of waste, and the model predicts whether it is organic or recyclable. The UI is built with HTML and CSS, making the classification process simple and intuitive.

Features

• Real-time waste classification
• Simple and interactive web interface
• Fast and efficient predictions
• Can be integrated with IoT devices for smart waste management

Future Scope

• Enhancing the dataset with more diverse waste categories.
• Deploying the model as a mobile application.
• Integrating with smart waste bins for automated classification and disposal.
• Implementing object detection for detecting multiple waste items in a single image.

Conclusion

This Organic vs Recyclable Waste Classifier is a step towards smart waste management. By leveraging deep learning and Flask, this project provides an efficient and accurate way to classify waste, helping in environmental conservation and sustainable waste management.

Feel free to reach out with feedback or suggestions. Let's work together towards a cleaner and greener planet! 🌍

You can check out the full project on my GitHub or view a live demo below:

View Demo