omasteam/waste-garbage-management-dataset

Garbage Classification Dataset

Dataset Summary

This dataset contains images of garbage items categorized into 10 classes, designed for machine learning and computer vision projects focusing on recycling and waste management.

It is ideal for building classification or object detection models, or developing AI-powered solutions for sustainable waste disposal.

• Total Images: 19,762
• Number of Classes: 10

Class Distribution

• Metal: 1020
• Glass: 3061
• Biological: 997
• Paper: 1680
• Battery: 944
• Trash: 947
• Cardboard: 1825
• Shoes: 1977
• Clothes: 5327
• Plastic: 1984

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Key Features

• Diverse Categories: Covers common household waste items for a wide range of applications.
• Balanced Distribution: Each class is sufficiently populated, ensuring robust model training.
• High-Quality Images: Clear and well-annotated images for better performance in computer vision tasks.
• Real-World Applications: Ideal for recycling solutions, waste segregation apps, and educational tools.

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Academic Reference

This dataset was featured in the research paper:
"Managing Household Waste Through Transfer Learning"
It demonstrates the dataset’s utility in real-world waste management applications. Researchers and developers can replicate or extend the experiments for further studies.

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🔗 Parquet version

This dataset is automatically converted to Apache Parquet by the Hugging Face parquet-converter bot.
You can find the Parquet files here:

👉 View Parquet files

Using the Parquet version is often faster for loading and querying metadata.

Example usage

from datasets import load_dataset

# Load metadata from the parquet-converted branch
dataset = load_dataset("omasteam/waste-garbage-management-dataset", split="train")

print(dataset[0])

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Applications

• AI for Sustainability: Train AI models to classify garbage and promote automated waste management.
• Recycling Programs: Build systems to sort garbage into recyclable and non-recyclable materials.
• Environmental Education: Develop tools to teach kids and adults about proper waste disposal.

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Feedback

Thank you for your interest in our waste dataset!
Whether you have used the dataset or are considering its use, your feedback is crucial. Please share your thoughts and experiences to help us improve.

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Citation

If you use this dataset, please cite the following:

Author: Suman Kunwar
Company: D.Waste.app
App Link: Deep Waste - Play Store

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