BowerApp/bower-waste-annotations
Dataset Card for waste annotations made by the recycling solution Bower The data offered by Bower (Sugi Group AB) in collaboration with Google.org Dataset Summary The bower-waste-annotations dataset consists of 1440 images of waste and various consumer items taken by consumer phone cameras. The images are annotated with Material type and Object type classes, listed below. The images and annotations has been manually reviewed to ensure correctness. It is… See the full description on the dataset page: https://huggingface.co/datasets/BowerApp/bower-waste-annotations.
Dataset Card for waste annotations made by the recycling solution Bower
<div align="center"> <img width="500" alt="img.png" src="img.png"> </div>
<p align="center"> <b>The data offered by Bower (Sugi Group AB) in collaboration with Google.org </b> </p>
Table of Contents
- Dataset Summary
- Dataset Description
- Homepage
- Repository
- Point of Contact
- Number of Images
- Taxonomy and Description
- Object Type
- Material Type
- Languages
- Data Instances
- Data Splits
- Dataset Creation
- Annotations
- Annotation Process
- Considerations for Using the Data
- Social Impact of Dataset
- Discussion of Biases
- Other Known Limitations
- Additional Information
- Contributors
- Licensing Information
- Acknowledgments
Dataset Summary
The bower-waste-annotations dataset consists of 1440 images of waste and various consumer items taken by consumer phone cameras. The images are annotated with Material type and Object type classes, listed below. The images and annotations has been manually reviewed to ensure correctness. It is assumed to have high quality of both bounding box accuracy and material + object combination. The purpose of the dataset has been to validate models - therefor all images in this set is categorized as validation data. As quality of annotations is high, one can use this as ground truth for validating models. This data set was created in a collaboration with Google.org and Google employees as part of the Google Impact Challenge: Tech for social good support that Bower got H1 2024. Which had as goal to create impact in the area of sustainability and waste. Any use of this data that contributes to this purpose is highly appreciated! Let us know how you contribute.
Dataset Description
- Homepage: https://www.getbower.com
- Repository: https://github.com/PantaPasen/seegull
- Point of Contact: lucas@getbower.com
Number of Images
{'valid': 1440}Taxonomy and description
Object type
Material type
Languages
English
Data Instances
A sample from the validation set is provided below:
{
...
}Data Splits
Validation dataset only
Dataset Creation
Images collected from consumer phone cameras and annotated manually
Annotations
Annotation process
- Pre-labelling using Grounding-DINO model (bounding boxes and labels)
- Manual annotation using LabelBox
- Review by Taxonomy expert for ensured quality
Considerations for Using the Data
Appreciate creditaion of Bower (Sugi Group AB) from usage of the data
Social Impact of Dataset
This dataset was created in a collaboration with Google.org and Google employees as part of the Google Impact Challenge: Tech for social good support that Bower got H1 2024. Goal with the project was to increase recycling rates throughout the world - this by incorporating Computer vision solutions in to the Bower-app to enable users to scan any type of trash and get correct sorting guidance on these items. Which had as goal to create impact in the area of sustainability and waste. Any use of this data that contributes to this purpose is highly appreciated! Let us know how you contribute.
Discussion of Biases
Other Known Limitations
Additional Information
Contributors
Lucas Nilsson, Linda Attby, Louise Rönne, Henrik Erskérs, Jeremy, Suhani
Licensing Information
This work is licensed under a MIT license
Contributions
Thanks to Google.org for making this possible, as well as the Google Fellows joining Bower for 6 months to enable this (Jeremy, Vicent, Suhani, Vivek, Ole and Rita).
