← Search

Data · dataset · 2025

YOLO-Formatted Dataset of Bottles in Diverse Backgrounds (plastic_bottle & tetra_pak)

Listed in Teesside University Research Data Repository

The dataset consists of 548 bottle images that are gathered in different real-life scenarios such as streets, parks, shops, and indoor scenes.

Description

The pictures were taken in a variety of conditions like variation in lighting, background and object positions to create more variability. All of the images are annotated adequately in the YOLO format, where there are bounding boxes denoting two classes (plastic_bottle and tetra_pak).

The annotation files are in the YOLO TXT format (class_id x_center y_center width height with normalized coordinates) and accompanying the images so that it is ready-to-use. The dataset can help serve the study of computer application in the field of bottle type detection, waste classification, recycling, and environmental monitoring. It can be employed to train and test object detection models to differentiate recycling objects in complicated and noisy backgrounds.

Read the rest (1 more)

There is no predetermined division, and scientists can make their own train, validation, and test subsets as per their requirements. It should be of particular interest to students, researchers and practitioners who work with a YOLO-based pipeline (e.g., YOLOv5 including YOLOv8) but it can be converted into other formats like Pascal VOC or COCO. By presenting a diverse and labeled set of bottles, this work will help to drive the field of automated waste recognition and reinforce the use of sustainable tools via machine learning.

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Image 65%
Provenance · 1 source records, 13 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/tksn2jrckf.111 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].anzsrc:field:460304mapping · researchdata tees ac ukvocabulary-mapper@1.0.0keywords['Computer Vision']
concepts[field].local:field:computer-science-aimapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:engineeringmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:humanitiesmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:life-sciencesmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:social-sciencemapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[modality].local:modality:imageenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (65%)
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
licensesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/rights
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title