Published April 11, 2025 | Version v2.0.0

M-Vet Livestock Dataset

  • 1. Makerere University
  • 1. National Livestock Resources Research Institute
  • 2. ROR icon Veterinarians Without Borders
  • 3. ROR icon Makerere University

Description

M-Vet Livestock Dataset is an open-access dataset created by the M-Vet project (www.m-vet.net) based at Makerere University Artificial Intelligence & Data Science Research Lab (www.air.ug) and supported by Lacuna Fund. It is aimed at supporting machine learning models for image classification tasks in Livestock. This dataset contains about 18,000 images of different animal types, including cows, goats, and pigs, collected from various farms and regions and annotated for animal type with corresponding classes. The dataset is designed to facilitate research and development in livestock management, particularly in animal classification tasks using computer vision. It is a valuable resource for researchers, developers, and agricultural stakeholders looking to innovate in animal health monitoring and diagnostics. Available on GitHub for public use.

The dataset consists of nine subfolders (0001 to 0009), each containing three directories: labels, images, and data. Each image has a corresponding .txt file containing its annotations.

For example, given the image:

  • M-Vet_Livestock-Dataset-main/0001/images/e0b206bf-ee2f-4d6a-bdbe-ea29d70402aa7725714119516389484_jpg.rf.31cf1c70bbd1a46bfb83404ffe9414dc.jpg
  • The corresponding label file: M-Vet_Livestock-Dataset-main/0001/labels/e0b206bf-ee2f-4d6a-bdbe-ea29d70402aa7725714119516389484_jpg.rf.31cf1c70bbd1a46bfb83404ffe9414dc.txt
  • Contains the following annotation: 0 1 0.07107843124999999 0.311274509375 0.07107843124999999 0.311274509375 0.51992034375 1 0.51992034375 1 0.07107843124999999

Acknowledgement: Dataset is created by M-Vet project(www.m-vet) led by Daniel Mutembesa(www.linkedin.com/in/mutembesa-daniel-447452165), in collaboration with 162 Expert and rural based Veterinarians and a network of over 1,500 Livestock farmers in Uganda, the National Livestock Resources and Research Institute(https://naro.go.ug/naris/nalirri/), Veterinarians Without Boarders (https://vetswithoutbordersus.org), and Research Consortium on African Swine Fever at Makerere University.

Files

MVet-Platform/M-Vet_Livestock-Dataset-v2.0.0.zip

Files (1.6 GB)

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Additional details

Related works

Funding

Meridian Institute
Lacuna Fund: Datasets for Machine Learning Diagnostics in Livestock

Dates

Collected
2024-07-11

Software