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MangoYOLO data set

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Version 2 2021-01-29, 00:11
Version 1 2021-01-17, 11:32
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posted on 2021-01-29, 00:11 authored by Anand KoiralaAnand Koirala, Kerry WalshKerry Walsh, Z Wang, C McCarthy
Datasets and directories are structured similar to the PASCAL VOC dataset, avoiding the need to change scripts already available, with the detection frameworks ready to parse PASCAL VOC annotations into their format. The sub-directory JPEGImages consist of 1730 images (612x512 pixels) used for train, test and validation. Each image has at least one annotated fruit. The sub-directory Annotations consists of all the annotation files (record of bounding box coordinates for each image) in xml format and have the same name as the image name. The sub-directory Main consists of the text file that contains image names (without extension) used for train, test and validation. Training set (train.txt) lists 1300 train images Validation set (val.txt) lists 130 validation images Test set (test.txt) lists 300 test images Each image has an XML annotation file (filename = image name) and each image set (training validation and test set) has associated text files (train.txt, val.txt and test.txt) containing the list of image names to be used for training and testing. The XML annotation file contains the image attributes (name, width, height), the object attributes (class name, object bounding box co-ordinates (xmin, ymin, xmax, ymax)). (xmin, ymin) and (xmax, ymax) are the pixel co-ordinates of the bounding box’s top-left corner and bottom-right corner respectively.

Funding

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

History

Start Date

2017-12-07

Publisher

Central Queensland University

Place of Publication

Rockhampton

Additional Rights

CC BY 4.0

Open Access

  • Yes

External Author Affiliations

University Southern Queensland

Author Research Institute

  • Institute for Future Farming Systems

Era Eligible

  • No

Number and size of Dataset

1730 images (612x512 pixels)

Usage metrics

    CQUniversity

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