AMIGA_fruit_counting

DOI

This project is a python implementation for fruit detection and tracking using YOLOv5 and ByteTrack. The project was build to be tested jointly with AMIGA robot for in-field fruit conting purposes. It was tested in the Farm@thon organized by Lleida Drone, where it was recognized with the first prize. The code was prepared to be used with a ZED camera, but it could be easily adapted for other cameras such as Oak-D.

This software is stored and maintained in the following github repository: https://github.com/GRAP-UdL-AT/AMIGA_fruit_counting

Identifier
DOI https://doi.org/10.34810/data2332
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/data2332
Provenance
Creator Gené Mola, Jordi ORCID logo; Net Barnés, Francesc (ORCID: 0000-0001-6888-519X); Felip Pomés, Marc
Publisher CORA.Repositori de Dades de Recerca
Contributor Gené Mola, Jordi; Universitat de Lleida; Centre de Recerca en Agrotecnologia
Publication Year 2025
Funding Reference Agencia Estatal de Investigación RTI2018-094222-B-I00 ; European Union ERDF, a way of making Europe
Rights MIT; info:eu-repo/semantics/openAccess; https://opensource.org/licenses/MIT
OpenAccess true
Contact Gené Mola, Jordi (Universitat de Lleida)
Representation
Resource Type Program source code; Dataset
Format image/png; text/x-python; text/plain; application/octet-stream; image/jpeg; text/markdown; application/x-docker-file; text/plain; charset=UTF-8; application/x-sh; text/plain; charset=US-ASCII; text/xml; application/x-ipynb+json; video/mp4
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Version 1.0
Discipline Agricultural Sciences; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Construction Engineering and Architecture; Engineering; Engineering Sciences; Life Sciences