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on-tree mango-branch instance segmentation dataset

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posted on 2024-07-15, 05:57 authored by Chiranjivi NeupaneChiranjivi Neupane

The dataset has been prepared for use in machine vision-based mango fruit and branch localisation for detection of fruit-branch occlusion. Images are from Honey Gold and Keitt mango varieties. The dataset contains:

- 250 RGB images (200 training + 50 test images) of mango tree canopies acquired using Azure Kinect Camera under artificial lighting condition.

- COCO JSON format label files with multi class (mango+branch), single classes (mango only and branch only) polygon annotations.

- Labels converted to txt format to use for YOLOv8-seg + other models training.

Annotation: The annotation tool - VGG Image Annotator (VIA) was used for ground truth labeling of images using polygon labelling tool.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Language

English

Open Access

  • Yes

Author Research Institute

  • Institute for Future Farming Systems

Medium

images(.jpg, .png etc), annotations (.json, .txt)

Number and size of Dataset

91 MB

Supervisor

Kerry Walsh, Anand Koirala

Geolocation

Queensland, Bungundarra

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