datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tomato_quality_classification
Tomato Quality Classification
A dataset for quality classification of Tomatoes. The dataset contains raw and augmented versions.The raw dataset contains 1,986 images.Images per class:
Fresh: 1,350
Rotten: 636
The augmented dataset contains 6,000 images.Images per class:
Fresh: 3,000
Rotten: 3,000
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{khatun2023extensive,
title={An extensive real-world… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/tomato_quality_classification.FruitNet_quality_classification
Fruitnet Quality Classification
A dataset for image classification of Fruitnet Quality Classification. The dataset contains 19,526 images across 3 classes: Bad, Good, Mixed.Images per class:
Bad: 6,788
Good: 11,664
Mixed: 1,074
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{meshram2022fruitnet,
title={FruitNet: Indian fruits image dataset with quality for machine learning applications}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/FruitNet_quality_classification.FruitVision_quality_classification
FruitVision Quality Classification
A dataset for quality classification of apples, bananas, mangoes, grapes, and oranges. The dataset contains raw and augmented versions.The raw dataset contains 10,154 images.Images per class:
Formalin-mixed: 3,176
Fresh: 3,800
Rotten: 3,178
The augmented dataset contains 73,389 images.Images per class:
Formalin-mixed: 22,228
Fresh: 30,400
Rotten: 20,761
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/FruitVision_quality_classification.Luffa_quality_classification
Luffa Quality Classification
This dataset provides real RGB images of luffa plants captured in a field environment in Bangladesh using a handheld smartphone. Collected during October 2023, the images depict natural variations in luffa quality relevant to agricultural disease classification. It serves as a practical resource for developing computer vision models in agricultural quality assessment under real-world field conditions. The dataset contains 343 images across 2 classes:… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/Luffa_quality_classification.banana_guava_quality_classification
Banana Guava Quality Classification
A dataset for quality classification of bananas and guavas. The dataset contains 1,748 images across 3 classes: Class_A, Class_B, Defect.Images per class:
Class_A: 671
Class_B: 469
Defect: 608
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{kumari2024banana,
title={Banana and Guava dataset for machine learning and deep learning-based quality classification}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/banana_guava_quality_classification.pomegranate_quality_classification
Pomegranate Quality Classification
A dataset for classification of Pomegranate quality. The dataset contains 1,080 images across 3 classes: G1_Q1, G2_Q1, G3_Q1.Images per class:
G1_Q1: 360
G2_Q1: 360
G3_Q1: 360
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{kumar2021image,
title={Image dataset of pomegranate fruits (Punica granatum) for various machine vision applications},
author={Kumar, Arun… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/pomegranate_quality_classification.VegNet_quality_classification
VegNet Quality Classification
A dataset for quality classification of various crops. The dataset contains 6,150 images across 5 classes: Damaged, Dried, Old, Ripe, Unripe.Images per class:
Damaged: 317
Dried: 1,389
Old: 2,044
Ripe: 1,787
Unripe: 613
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{suryawanshi2022vegnet,
title={VegNet: dataset of vegetable quality images for machine learning… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/VegNet_quality_classification.dragonfruit_quality_classification
Dragonfruit Quality Classification
A dataset for quality classification of dragonfruit. The dataset contains raw and augmented versions.The raw dataset contains 1,652 images.Images per class:
Defect Dragon Fruit: 754
Fresh Dragon Fruit: 898
The augmented dataset contains 5,000 images.Images per class:
Defect Dragon Fruit: 3,000
Fresh Dragon Fruit: 2,000
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/dragonfruit_quality_classification.coffee_bean_quality_classification
Coffee Bean Quality Classification
A dataset for quality classification of Coffee Beans. The dataset contains 464 images across 9 classes: A, AA, AAA, AB, Bits, Bulk, C, PB-I, PB-II.
Images per class:
A: 50
AA: 61
AAA: 50
AB: 50
Bits: 51
Bulk: 50
C: 51
PB-I: 51
PB-II: 50
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{bj2025cbd,
title={CBD: Coffee Beans Dataset},
author={BJ, Bipin Nair and KM… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/coffee_bean_quality_classification.