datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
KAIST-Multispectral-Pedestrian-Detection-DatasetKAIST-Multispectral-Pedestrian-Benchmarkcocoa_agroforestry_multispectral
Cocoa Agroforestry Multispectral
An unlabeled image dataset of Cocoa Agroforestry Multispectral. The dataset contains 1,272 images with no classification, segmentation, or bounding-box annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{lammoglia2024high,
title={High-resolution multispectral and RGB dataset from UAV surveys of ten cocoa agroforestry typologies in Côte d'Ivoire}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/cocoa_agroforestry_multispectral.tropical_dry_forest_multispectral
Tropical Dry Forest Multispectral
An unlabeled image dataset of Tropical Dry Forest Multispectral. The dataset contains 196 images with no classification, segmentation, or bounding-box annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{vegapuga2024high,
title={High resolution image dataset by RGB and multispectral cameras on an unmanned aerial vehicle over a secondary tropical dry forest}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/tropical_dry_forest_multispectral.wheat_mosaic_classification_multispectral
Wheat Mosaic Classification Multispectral
This dataset provides real multispectral images of wheat plants in field environments across South Africa, collected during August and October 2023. Captured using a specially adapted Canon EOS 800D DSLR, the images focus on early detection of Wheat Stripe Mosaic Virus, depicting plants at various stages of disease progression. The dataset contains 424 images across 2 classes: diseased, early.Images per class:
diseased: 252
early: 172… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/wheat_mosaic_classification_multispectral.Multispectral_SAR_IR_AnnotatedMini-KAIST-Multispectral-Pedestrian-Detection-Datasethotpotqa_clustered_spectral_multi-qa-MiniLM-L6-cos-v1_50hotpotqa_clustered_spectral_multi-qa-MiniLM-L6-cos-v1_10hotpotqa_clustered_spectral_multi-qa-MiniLM-L6-cos-v1_2hotpotqa_clustered_spectral_multi-qa-MiniLM-L6-cos-v1_5multispectral_cashew_aerial_imagesdual-validation-multispectral
Dataset Description
This is a Machine Learning-ready, multitemporal satellite dataset designed specifically for cloud gap imputation and stratified model evaluation. It acts as the foundational dataset for the framework introduced in "A Dual Validation Framework for Curating Machine Learning-Ready Satellite Datasets: A Scalable Pipeline and Stratified Analysis." The dataset is strictly curated from standard Analysis-Ready Data (ARD) to include intrinsic radiometric validation… See the full description on the dataset page: https://huggingface.co/datasets/trust-tad/dual-validation-multispectral.KAIST-Multispectral-Pedestrian-Detection-DatasetAniMonitor_False_NDVI_Dataset_Multispectral_Rice_Leaf_Images_RPiMultispectral-Image_Classificationhotpotqa_clustered_spectral_multi-qa-MiniLM-L6-cos-v1_20Multispectral_SAR_IR_Fused_Dataset