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.vintage-photography-450k-high-quality-captionsThis is a 450k image datastet focused on photography from the 20th century, and their analog aspect. Many of the images are in high resolution. This dataset currently has 20k images captioned with InternVL2 26B, and is a work in progress (I plan to caption the entire dataset and also have short captions for all of the images, compute is an issue for now).
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.jwst-quality-analysis-dataset
JWST Quality Analysis Dataset
Overview
This dataset contains comprehensive quality analysis for 2,709 JWST (James Webb Space Telescope) NIRCam images from the MAST archive. Each image has been automatically analyzed for quality metrics, artifact detection, and noise characteristics.
Dataset Information
Size: 2,709 images
Format: JSONL (JSON Lines)
Source: JWST NIRCam observations from MAST
Targets: M16, NGC 3132, NGC 3324, SMACS 0723, Stephan's Quintet… See the full description on the dataset page: https://huggingface.co/datasets/norbertm/jwst-quality-analysis-dataset.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.vintage-photography-450k-high-quality-captionsThis is a 450k image datastet focused on photography from the 20th century, and their analog aspect. Many of the images are in high resolution. This dataset currently has 20k images captioned with InternVL2 26B, and is a work in progress (I plan to caption the entire dataset and also have short captions for all of the images, compute is an issue for now).