datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CTTA-AD-Benchmarks
CTTA-AD Benchmarks
Dataset collection for CTTA-AD: Continual Test-Time Adaptation for Unified Few-Shot Visual Anomaly Detection (AAAI 2027 submission).
Datasets
Dataset
Domain
Categories
Train Normal
License
MVTec-AD
Industrial
15
209–391 per category
CC BY-NC-SA 4.0
VisA
Industrial
12
400–905 per category
CC BY-NC-SA 4.0
MVTec-LOCO
Logical
5
varies
CC BY-NC-SA 4.0
BrainMRI
Medical
1
7,500
Research only
LiverCT
Medical
1
1,542
Research only… See the full description on the dataset page: https://huggingface.co/datasets/Hammadhaideerr/CTTA-AD-Benchmarks.plant-seedlings-dataset
Plant Seedlings Dataset
Image dataset of 12 species of plant seedlings for classification tasks. Originally from the Plant Seedlings Classification Kaggle competition.
Dataset Structure
train/ — 4,750 labeled images organized by species folder
test/ — 794 unlabeled images for submission
sample_submission.csv
Labels.csv
Species (12 classes)
Black-grass (263)
Charlock (390)
Cleavers (287)
Common Chickweed (611)
Common wheat… See the full description on the dataset page: https://huggingface.co/datasets/Khalid-Hamad/plant-seedlings-dataset.sdxl-turbo-sae-labels
SDXL-Turbo SAE Feature Labels
20,480 labeled sparse autoencoder features across 4 UNet attention blocks in SDXL-Turbo, plus 50K generated images with full activation logs.
Built for latent-dance — a real-time audio-reactive music visualizer using SAE steering at 50 FPS.
Important attribution: The SDXL-Turbo sparse autoencoders/checkpoints used here were trained and released by Surkov et al. / EPFL through sdxl-unbox. This dataset does not claim authorship of the SAE training. It… See the full description on the dataset page: https://huggingface.co/datasets/hammamiomar/sdxl-turbo-sae-labels.ham10000_bbox
HAM10000 with Spatial Annotations and Bounding Box Coordinates
Enhanced version of HAM10000 dataset with bounding box coordinates and spatial descriptions for skin lesion localization.
Dataset Description
This dataset extends the original HAM10000 dermatology dataset with:
Bounding box coordinates for lesion localization
Spatial descriptions (e.g., "located in center-center region")
Area coverage statistics
Mask availability flags
Features
image: RGB skin… See the full description on the dataset page: https://huggingface.co/datasets/abaryan/ham10000_bbox.ham1ok
The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
Original Paper and Dataset here
Kaggle dataset here
Introduction to datasets
Training of neural networks for automated diagnosis of pigmented skin lesions is hampered by the small size and lack of diversity of available dataset of dermatoscopic images. We tackle this problem by releasing the HAM10000 ("Human Against Machine with 10000 training images") dataset.… See the full description on the dataset page: https://huggingface.co/datasets/karoladelk/ham1ok.HAM10000