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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: label |
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dtype: |
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class_label: |
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names: |
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- Metal |
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- Glass |
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- Biological |
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- Paper |
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- Battery |
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- Trash |
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- Cardboard |
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- Shoes |
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- Clothes |
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- Plastic |
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splits: |
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- name: train |
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num_examples: 19762 |
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total_num_examples: 19762 |
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task_templates: |
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- task: image-classification |
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input_schema: image |
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label_schema: class_label |
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license: mit |
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tags: |
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- waste |
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- garbage |
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- waste-management |
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- cnn |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Garbage Classification Dataset |
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## Dataset Summary |
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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**. |
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It is ideal for building classification or object detection models, or developing **AI-powered solutions for sustainable waste disposal**. |
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- **Total Images:** 19,762 |
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- **Number of Classes:** 10 |
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### Class Distribution |
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- **Metal:** 1020 |
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- **Glass:** 3061 |
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- **Biological:** 997 |
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- **Paper:** 1680 |
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- **Battery:** 944 |
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- **Trash:** 947 |
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- **Cardboard:** 1825 |
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- **Shoes:** 1977 |
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- **Clothes:** 5327 |
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- **Plastic:** 1984 |
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--- |
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## Key Features |
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- **Diverse Categories:** Covers common household waste items for a wide range of applications. |
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- **Balanced Distribution:** Each class is sufficiently populated, ensuring robust model training. |
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- **High-Quality Images:** Clear and well-annotated images for better performance in computer vision tasks. |
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- **Real-World Applications:** Ideal for recycling solutions, waste segregation apps, and educational tools. |
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--- |
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## Academic Reference |
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This dataset was featured in the research paper: |
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**_"Managing Household Waste Through Transfer Learning"_** |
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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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--- |
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## 🔗 Parquet version |
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This dataset is automatically converted to [Apache Parquet](https://parquet.apache.org/) by the Hugging Face parquet-converter bot. |
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You can find the Parquet files here: |
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👉 [View Parquet files](https://huggingface.co/datasets/omasteam/waste-garbage-management-dataset/tree/refs%2Fconvert%2Fparquet) |
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Using the Parquet version is often faster for loading and querying metadata. |
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### Example usage |
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```python |
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from datasets import load_dataset |
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# Load metadata from the parquet-converted branch |
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dataset = load_dataset("omasteam/waste-garbage-management-dataset", split="train") |
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print(dataset[0]) |
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``` |
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--- |
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## Applications |
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- **AI for Sustainability:** Train AI models to classify garbage and promote automated waste management. |
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- **Recycling Programs:** Build systems to sort garbage into recyclable and non-recyclable materials. |
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- **Environmental Education:** Develop tools to teach kids and adults about proper waste disposal. |
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--- |
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## Feedback |
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Thank you for your interest in our waste dataset! |
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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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--- |
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## Citation |
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If you use this dataset, please cite the following: |
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**Author:** *Suman Kunwar* |
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**Company:** *D.Waste.app* |
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**App Link:** [Deep Waste - Play Store](https://play.google.com/store/apps/details?id=com.hai.deep_waste&hl=en) |
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--- |
