datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
flood-detection-pair-colombia
flood-detection-pair-colombia
110 paired Sentinel-2 satellite tile samples (4 PNGs per row) labeled for flood detection across 9 documented flood events in Colombia. Built for fine-tuning a small vision-language model that runs on a satellite or community ground station — see the humaid project.
What's in each sample
Each row in flood_train.jsonl / flood_eval.jsonl is a 4-image vlm_sft example. The user message contains four image content blocks (in this order) followed… See the full description on the dataset page: https://huggingface.co/datasets/jpmarindiaz/flood-detection-pair-colombia.colombia
UAV Thermal Imagery of Buried Landmines
Mirror of "Test Images of Buried landmines" (Universidad del Valle), repackaged from
.rar to .zip for use in Google Colab.
This is not the original source. If you use this data, cite the original authors and DOI
(see Citation). Content is unmodified — only the archive container changed.
Why a mirror? Mendeley's download endpoint redirects to an S3 bucket that returns
HTTP 403 for Google Cloud IP ranges, so the original link fails inside… See the full description on the dataset page: https://huggingface.co/datasets/dejanb/colombia.id_colombiaInversocolombia-viterbo-eq-ddamy_colombian_coffe_FO
Dataset Card for 2025.01.16.11.20.04
This is a FiftyOne dataset with 1593 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("pjramg/my_colombian_coffe_FO")
# Launch the App
session = fo.launch_app(dataset)
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/pjramg/my_colombian_coffe_FO.colombian_coffee