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---
license: cc-by-4.0
task_categories:
- image-classification
language:
- en
tags:
- waste
- recycling
- trash
- garbage
- environment
pretty_name: Trash Optimizer Dataset
size_categories:
- 1K<n<10K
---
# Trash Optimizer Dataset
Assembled waste classification dataset covering **18 categories**, used to train the
[cpoisson/trash-optimizer-models](https://huggingface.co/cpoisson/trash-optimizer-models) series.
Built with a custom pipeline that normalises, filters and balances images from three sources:
| Source | Categories contributed | License |
|---|---|---|
| [RealWaste](https://archive.ics.uci.edu/dataset/908/realwaste) (UCI / Kaggle) | cardboard, food_organics, glass, metal, miscellaneous_trash, paper, plastic, textile_trash, vegetation | CC BY 4.0 |
| [RHWC](https://www.kaggle.com/datasets/alistairking/recyclable-and-household-waste-classification) (Kaggle) | cardboard, food_organics, glass, metal, paper, plastic, textile_trash | CC BY-SA 4.0 |
| Custom (web-scraped) | battery, car_battery, light_bulb, mirror, neon, pharmacy, printer_cartridge, tire, wood | ⚠️ Mixed — images sourced from the public web, licenses vary |
> **Note**: The custom category images were collected from publicly accessible web sources.
> Their individual licenses may vary. Use for research and non-commercial purposes.
## Structure
```
dataset/
battery/ 277 images
car_battery/ 260 images
cardboard/ 500 images
food_organics/ 500 images
glass/ 500 images
light_bulb/ 157 images
metal/ 500 images
mirror/ 194 images
miscellaneous_trash/ 500 images
neon/ 190 images
paper/ 500 images
pharmacy/ 257 images
plastic/ 500 images
printer_cartridge/ 357 images
textile_trash/ 500 images
tire/ 353 images
vegetation/ 436 images
wood/ 245 images
```
**Total: 6,229 images across 18 categories**
Images are JPEG/PNG, minimum size 150×150px, maximum 500 images per category.
Filename prefix indicates source: `realwaste_*`, `rhwc_*`, `customdataset_*`.
## Dataset builder
The assembly pipeline is available in the
[trash-optimizer](https://github.com/cpoisson/trash-optimizer) repository
under `dataset/datasetbuilder.py`, configured via `trash-optimizer-datasetbuilder.toml`.
## Model trained on this dataset
→ [cpoisson/trash-optimizer-models](https://huggingface.co/cpoisson/trash-optimizer-models)
— EfficientNet-B0, 95.07% test accuracy across 18 categories.
## Citation
If you use the RealWaste portion, please cite:
```bibtex
@misc{realwaste,
author = {Majchrowska, Sylwia and others},
title = {RealWaste},
year = {2023},
publisher = {UCI Machine Learning Repository},
doi = {10.24432/C5SS4S}
}
```