datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
imagenet-aThe ImageNet-A dataset contains 7,500 natural adversarial examples.
Source: https://github.com/hendrycks/natural-adv-examples.Also see the ImageNet-C and ImageNet-P datasets at https://github.com/hendrycks/robustness
@article{hendrycks2019nae, title={Natural Adversarial Examples}, author={Dan Hendrycks and Kevin Zhao and Steven Basart and Jacob Steinhardt and Dawn Song}, journal={arXiv preprint arXiv:1907.07174}, year={2019}}
There are 200 classes we consider. The WordNet ID and a… See the full description on the dataset page: https://huggingface.co/datasets/barkermrl/imagenet-a.BarkVN-50
Dataset Card for BarkVN-50: Tree Species Identification from Bark Texture
This is a FiftyOne dataset with 5578 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("Voxel51/BarkVN-50")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/BarkVN-50.womenbark-ambrosia-beetle-benchmark
Bark and Ambrosia Beetle Detection Benchmark
Version 2.0.1 · 14,491 images · 175 species · 21 tribes · 70 genera · COCO detection format
A specimen-disjoint, species-level object-detection benchmark for bark and ambrosia
beetles (Coleoptera: Curculionidae: Scolytinae and Platypodinae), derived from the
Bark and Ambrosia Gallery (https://barkandambrosiagallery.org/). Species
determinations are made or reviewed by taxonomists; individual specimens carry
bounding boxes.
This Zenodo… See the full description on the dataset page: https://huggingface.co/datasets/IBBI-bio/bark-ambrosia-beetle-benchmark.barkleyAITube_Commercialsbark-partial-s100spruce-log-bark-segmentation
Spruce Log Bark Segmentation
512×512 overlapping patches of Norway spruce (Picea abies) log bark with pixel-level segmentation masks for three classes. 681 image/mask pairs.
This is the training-ready subset of a larger dataset. The full collection (raw photos, processed full-resolution images, and patches at native, 1024, and 512 resolution) is archived on Zenodo: [DOI — to be added].
Classes
Masks are single-channel; each pixel holds the class index:
0 — bark —… See the full description on the dataset page: https://huggingface.co/datasets/jakobkreft/spruce-log-bark-segmentation.Barkley-T1Barkley-V1