---
task_categories:
- image-classification
tags:
- waste
- classification
pretty_name: waste-cl
---

# Dataset Card for waste classifier 

This dataset contains waste images in different categories:
- cardboard
- compost
- glass
- metal
- paper
- plastic
- trash


### Dataset Description
- **Curated by:** Rootstrap
- **License:** MIT

### Dataset Sources 
Data is a combination of [Trashnet](https://github.com/garythung/trashnet) dataset plus more images obtained by internet search. 
Paper: [Classification of Trash for Recyclability Status](https://cs229.stanford.edu/proj2016/report/ThungYang-ClassificationOfTrashForRecyclabilityStatus-report.pdf)

## Uses
The dataset can be used for waste classification or other type of project. 

### Direct Use
This dataset is used to build a waste classifier for categorizing different types of waste, being able to correctly throw the trash in the corresponding trash can at our office.

{{ direct_use | default("[More Information Needed]", true)}}

## Dataset Structure
The data is already split in train and test folders. 
Inside each folder contains one folder for each class. 

## Dataset Creation

### Curation Rationale

at Rootstrap, our Machine Learning Engineers are committed to creating awareness of correct waste classification to help the environment. 
Their determination to make an impact led to the creation of 'RootTrash', an internal AI-powered app to help us recycle correctly.


#### Data Collection and Processing
Some of the images were obtained using Bing searcher using the api HTTP. 
You can find the code used to download the images at this [Google Colab](https://colab.research.google.com/drive/1JvAYFx1DIEi1MMyI-tuCfE2eHMSKisKT?usp=sharing). 

#### Who are the source data producers?
Thung, G., & Yang, M. (2016). Classification of Trash for Recyclability Status.



## Bias, Risks, and Limitations
Current model has been trained mostly with internet images and most of them has white background. This might be an issue when testing with real images.
In the future, the dataset will be extended with the photos taken through the app. 

### Recommendations
Integrate this model with a detection model such as [rootstrap-org/waste-detector](https://huggingface.co/rootstrap-org/waste-detector)