datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
vlm_wsi_patch
VLM WSI Patch
Closed-answer WSI patch VQA dataset with 48,766 metadata-eligible rows and
48,609 valid 1344×1344 RGB top-4 mosaics, picked from of PathGen. Rows without an image retain an
explicit processing rejection status. Each patch uses a WSI level-0 top-left coordinate and
672×672 pixels; backfill and patch substitution are excluded.
The image field is a repository-relative PNG path. metadata/manifest.jsonl and
metadata/manifest.parquet contain QA labels, top-4 coordinates… See the full description on the dataset page: https://huggingface.co/datasets/HCOOH/vlm_wsi_patch.patch-aliasing-bayesian
Patch-Aliasing Bayesian Analysis Data
Raw and processed data from the Bayesian analysis of structural patch-aliasing in Chronos-Bolt Tiny.
Companion to the model weights at federicosabbadini/chronos-bolt-patch-aliasing-models.
Structure
clean_15model/ # 15 preregistered (P,S) configurations
full_22model/ # all 22 configurations (adds 7 robustness checks)
h1_fixed_offset/ # supplementary H1 analysis with fixed offset
Each run folder… See the full description on the dataset page: https://huggingface.co/datasets/federicosabbadini/patch-aliasing-bayesian.patchlet-embed-preprocessedPatchMap_v1cc12m_openai_clip-vit-base-patch32_image_image_retrieval_pairs_2022-09-13e621-tagger-patchpatch_camelyonvessel-detection-labeled-patches
Vessel Detection Labeled Patches
Validated/confirmed satellite image patches exported from the military-boat-detection review workflow.
Contents
images/: patch images.
metadata.csv: one row per patch, compatible with Hugging Face image-folder metadata.
metadata.jsonl: rich patch metadata with nested objects.
annotations.csv: one row per vessel annotation.
annotations.jsonl: JSONL version of the object annotations.
labels/: YOLO-format labels. Hard negatives have empty… See the full description on the dataset page: https://huggingface.co/datasets/DefendIntelligence/vessel-detection-labeled-patches.PatchCamelyon
PatchCamelyon (PCam)
This is a reupload of the PatchCamelyon (PCam) dataset to make it more readily usable instead of manipulating H5 files. The original can be found in the author's Github repo.
If you use this dataset, please cite the original publications:
@inproceedings{veeling2018rotation,
title={Rotation Equivariant CNNs for Digital Pathology},
author={Veeling, Bastiaan S and Linmans, Jasper and Winkens, Jim and Cohen, Taco and Welling, Max},
booktitle={Medical Image… See the full description on the dataset page: https://huggingface.co/datasets/zacharielegault/PatchCamelyon.cc12m_openai_clip-vit-base-patch32_image_image_retrieval_pairs_2022-09-15ink-8um-v8-patchpack
ink-8um v8 patch pack
This is the complete training and validation corpus of the
v8-in ink-detection model, frozen to disk as
64 × 64 × 24 uint8 patches. It holds 508,006 training and 43,249 validation patches from 19
surface segments at ~8 µm: Scroll 1, Scroll 5, PHerc. 1667, 0139, 0814, 0500P2 and 0009B, plus
fragments 1, 3 and 4.
The patches were extracted with the training code's own loaders and admission rules, so training
from the pack is equivalent to training from the… See the full description on the dataset page: https://huggingface.co/datasets/YoussefMoNader/ink-8um-v8-patchpack.patch-of-behavior-1k
BEHAVIOR-1K Asset Database (Patch)
Complete metadata and visualizations for all 8662 BEHAVIOR-1K object assets.
Contents
Path
Description
assets.db
SQLite database — descriptions + DoF for all 8662 assets
objects/{category}/{model}/description.json
VLM-generated visual description (5676 assets)
objects/{category}/{model}/dof.json
Articulation / DoF metadata
objects/{category}/{model}/front.png
Front-view visualization
objects/{category}/{model}/back.png… See the full description on the dataset page: https://huggingface.co/datasets/EastDong0704/patch-of-behavior-1k.patch_region_128mtg-scryfall-cropped-art-embeddings-siglip-so400m-patch14-384cc12m_openai-clip-vit-patch32vtab_patch_camelyon
VTAB PatchCamelyon
This dataset has been used for the paper Fantastic Features and Where to Find Them: A Probing Method to combine Features from Multiple Foundation Models (NeurIPS 2025).
It reproduces the settings (splits, labels) used for the Visual Task Adaptation Benchmark (VTAB).
VTAB Paper: A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark
VTAB Repository: google-research/task_adaptation
Details of the original dataset:
Original… See the full description on the dataset page: https://huggingface.co/datasets/bramtoula/vtab_patch_camelyon.patch_region_512PatchCamelyon
PatchCamelyon (PCam)
Description
The PatchCamelyon benchmark is a new and challenging image classification dataset. It consists of 327.680 color images (96 x 96px) extracted from histopathologic scans of lymph node sections. Each image is annoted with a binary label indicating presence of metastatic tissue. PCam provides a new benchmark for machine learning models: bigger than CIFAR10, smaller than imagenet, trainable on a single GPU
Why PCam
Fundamental… See the full description on the dataset page: https://huggingface.co/datasets/pavan316/PatchCamelyon.idc-patchesPatchCamelyon
PatchCamelyon (PCam)
Description
The PatchCamelyon benchmark is a new and challenging image classification dataset. It consists of 327.680 color images (96 x 96px) extracted from histopathologic scans of lymph node sections. Each image is annoted with a binary label indicating presence of metastatic tissue. PCam provides a new benchmark for machine learning models: bigger than CIFAR10, smaller than imagenet, trainable on a single GPU
Why PCam
Fundamental… See the full description on the dataset page: https://huggingface.co/datasets/KE9037/PatchCamelyon.cc12m_openai-clip-vit-patch32_image_retrieval_top15_start1000000_end3500000sentinel-lfm-mining-patches
sentinel-lfm — illegal-mining single-frame patches
128px RGB patches cropped from the Roboflow illegal-mining dataset, labelled
mine (1) / no-mine (0). Split by source image (no leakage) into
train/val/test. Provided as PNGs + vlm_sft-format JSONL (one image + prompt
-> JSON answer) so it drops straight into VLM fine-tuning.
split
pos
neg
total
train
1410
555
1965
val
303
66
369
test
303
116
419
RGB only (no multispectral). Each JSONL row is a single-turn VLM… See the full description on the dataset page: https://huggingface.co/datasets/ASTRALK/sentinel-lfm-mining-patches.lidc-idri-patchesA dataset of patches (most 64x64 pixels from the LIDC-IDRI CT scans). These are 16-bit images with a 1024 shift from the original HU values.
The dataset is incomplete as of 2024-12-02. If you find it useful, I will add more patches.
---
license: apache-2.0
task_categories:
- image-classification
language:
- en
pretty_name: LIDC IDRI patches for classification
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: annotation_id… See the full description on the dataset page: https://huggingface.co/datasets/ykeselman/lidc-idri-patches.ALL-IDB-Patches
ALL-IDB Patches
MATLAB source code for creating image patches and labels used in the paper “ALL-IDB Patches: Whole slide imaging for Acute Lymphoblastic Leukemia detection using Deep Learning”, presented at ICASSP Workshops 2023.
The repository converts annotated ALL-IDB1 whole-slide microscope images into fixed-size overlapping patches, preserving the position of white blood cell centroids and generating patch-level labels for probable lymphoblasts… See the full description on the dataset page: https://huggingface.co/datasets/AngeloUNIMI/ALL-IDB-Patches.Airbus-Wind-Turbines-Patches
Dataset Card for "Airbus-Wind-Turbines-Patches"
Split Information
This HuggingFace dataset repository contains just the Validation split.
Licensing Information
CC BY-NC-SA 4.0
Citation Information
Airbus Wind Turbine Patches
@misc{kaggle_awtp,
author = {Airbus DS GEO S.A.},
title = {Airbus Wind Turbine Patches},
howpublished = {\url{https://www.kaggle.com/datasets/airbusgeo/airbus-wind-turbines-patches}},
year = {2021},
version = {1.0}
}
patch_tasks_vllm
Dataset Card for Patch-Based Visual Question Answering Dataset
Dataset Details
Dataset Description
This dataset contains approximately 305,000 triplets of question, answer, and image designed for patch-based visual reasoning tasks.
A standard question in this dataset is formatted as follows:
Image Grid: The image is divided into a 4x4 grid of 16 equal-sized patches. Patches are numbered sequentially from the top-left corner and moving right, then down to the… See the full description on the dataset page: https://huggingface.co/datasets/yurkes/patch_tasks_vllm.merged_libero_scale_40_mask_depth_noops_lerobot_patch_size7_chunk10_mask_interestcc12m_openai-clip-vit-patch32_image_retrieval_top15_start1000000_end3500000_SHORT500KA85_patch_52bln600-img-patch
BLN600 Image Patches
This dataset provides BLN600's image patches for fine-tuning vision-language models on post-OCR correction, introduced in "Image-Informed Post-OCR Correction with Vision-Language Models" (EMNLP 2026 Findings). Each patch corresponds to a text sequence in BLN600 and is cropped from the Gale British Library Newspapers collection, using word-level bounding boxes from the collection's ALTO XML OCR layout data. It is intended to be used alongside the code and… See the full description on the dataset page: https://huggingface.co/datasets/pykale/bln600-img-patch.