Project-AgML/mango_pest_original_classification

Mango Pest Original Classification

This dataset contains real RGB images of mango leaves, capturing various pest infestations and healthy (normal) conditions. The images were collected directly in agricultural field settings from mango farms using standard color imaging equipment. The dataset contains raw and augmented versions.
The raw dataset contains 510 images.
Images per class:

• apoderus_javanicus: 63
• aulacaspis_tubercularis: 13
• ceroplastes_rubens: 11
• cisaberoptus_kenyae: 19
• dappula_tertia: 38
• dialeuropora_decempuncta: 30
• erosomyia_sp: 13
• icerya_seychellarum: 27
• ischnaspis_longirostris: 7
• mictis_longicornis: 86
• neomelicharia_sparsa: 36
• normal: 36
• orthaga_euadrusalis: 22
• procontarinia_matteiana: 27
• procontarinia_rubus: 26
• valanga_nigricornis: 56

The augmented dataset contains 46,700 images.
Images per class:

• apoderus_javanicus: 5,725
• aulacaspis_tubercularis: 1,205
• ceroplastes_rubens: 1,054
• cisaberoptus_kenyae: 1,807
• dappula_tertia: 3,465
• dialeuropora_decempuncta: 2,712
• erosomyia_sp: 1,205
• icerya_seychellarum: 2,560
• ischnaspis_longirostris: 454
• mictis_longicornis: 7,685
• neomelicharia_sparsa: 3,314
• normal: 3,314
• orthaga_euadrusalis: 2,108
• procontarinia_matteiana: 2,560
• procontarinia_rubus: 2,410
• valanga_nigricornis: 5,122

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

The original train/test/val split has been preserved in the split column.

Citation

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The dataset itself can be cited as:

Chandramouli, K. (2020). Dataset for pest classification in Mango farms from Indonesia [Dataset]. Mendeley. https://doi.org/10.17632/94JF97JZC8.1

This dataset was reformatted from its original format to match HuggingFace standards.