datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
vlm-plant-sim
VLM Plant Sim
This dataset update merges three sources into source-based splits:
synthetic: HELIOS simulation outputs from 2025 Davis generation.
real: orthophoto patches (PNG only).
real_dap10_boxes: annotated patch subset (plots 1-16 only).
Splits
synthetic: 2800
real: 560
real_dap10_boxes: 224
Notes
Real split intentionally excludes method outputs (*.json and *.md) from evaluation artifacts.
Initial-plant split includes only samples where… See the full description on the dataset page: https://huggingface.co/datasets/heesup/vlm-plant-sim.scanned-images-dataset-for-ocr-and-vlm-finetuning
Dataset Card for scanned_images_dataset
This is a FiftyOne dataset containing 3,482 scanned document images across 10 diverse document categories. Designed for OCR training and Vision-Language Model (VLM) fine-tuning, this dataset features real-world scanned documents with varied layouts, scanning quality, and document types.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/scanned-images-dataset-for-ocr-and-vlm-finetuning.Kinetics-700
Damaged Videos List
The following rows are removed due to damaged video files:
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5d9mIpws4cg_000130_000140
SYTMgaqGhfg_000010_000020
ixQrfusr6k8_000001_000011
BSN_nDiTwBo_000004_000014
y7cYaYX4gdw_000047_000057
A-FCzUzEd4U_000000_000010
_dbw-EJqoMY_001023_001033
zLD_q2djrYs_000030_000040
FAqHwAPZfeE_000018_000028
vlmn_tartandrive100_scand50_coda25_spot100_sub5_full_augmentation_processed_10
Trajectory Ranking Dataset
This dataset contains trajectory ranking results for autonomous navigation scenarios.
Dataset Statistics
Total examples: 39558
Chunks processed: 40
Upload date: 2025-09-13T00:44:30.335177
Features
Image data with terrain analysis
Trajectory rankings and reasoning
Quality and diversity analysis
Terrain and trajectory descriptions
scanned-images-dataset-for-ocr-and-vlm-finetuning
Dataset Card for scanned_images_dataset
This is a FiftyOne dataset containing 3,482 scanned document images across 10 diverse document categories. Designed for OCR training and Vision-Language Model (VLM) fine-tuning, this dataset features real-world scanned documents with varied layouts, scanning quality, and document types.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from… See the full description on the dataset page: https://huggingface.co/datasets/prabhats0605/scanned-images-dataset-for-ocr-and-vlm-finetuning.PALL-VLM-data
PALL-VLM-data — Dental Vision-Language Dataset
The training dataset for Harisundar/PALL-VLM,
a dental vision-language model. It contains 32,884 records over 52,461 images,
formatted as image+text conversations for LLaVA-style instruction tuning.
Curated by: Harisundar R
Used by: Harisundar/PALL-VLM · PALL on GitHub
Language: English
Layout
vlm_train/
├── images/ # 52,461 dental images
├── train.jsonl # 29,667 records
├── val.jsonl… See the full description on the dataset page: https://huggingface.co/datasets/Harisundar/PALL-VLM-data.Turkish-VLM-Mix-BenchmarkThis is a Turkish multimodal (image-text-text triplets) dataset consisting of Turkish translated samples from the datasets google/docci, tomg-group-umd/pixelprose, detection-datasets/coco, rafaelpadilla/coco2017, liuhaotian/LLaVA-Instruct-150K, liuhaotian/LLaVA-CC3M-Pretrain-595K, and HuggingFaceM4/FairFace.
The labels are in Turkish and the dataset is in an instruction-tuning format with separate columns for prompts and completion labels.
The original labels (except… See the full description on the dataset page: https://huggingface.co/datasets/ucsahin/Turkish-VLM-Mix-Benchmark.iconclass-vlm-brillfull
Iconclass VLM — brill full labels
Training-ready VLM iconclass-classification dataset rebuilt from the fuller, cleaner
source labels in biglam/brill_iconclass
(CC0). Recovers labels lost to truncation in davanstrien/iconclass-vlm-sft.
Source images: same Brill Arkyves images as biglam/brill_iconclass, bytes passed through verbatim (no re-encode).
Labels: full Iconclass codes with operators (+n), key-combos :, and qualifiers (TEXT) kept intact. Empty/sentinel tokens stripped; ~5… See the full description on the dataset page: https://huggingface.co/datasets/davanstrien/iconclass-vlm-brillfull.medical-vlm-unlearning-corpus
Incremental Medical VLM Unlearning Subset
Training-ready, leakage-audited configurations are published independently so
completed sources remain usable after interruption. VQA-RAD (CC0), English
SLAKE (CC BY 4.0), and an NIH ChestXray14 subset include pixels. CheXpert is a
source-controlled manifest whose pixels are resolved from the authorized Kaggle
input and are not redistributed. See progress/latest.json and reports/.
This is a research dataset, not a diagnostic product.… See the full description on the dataset page: https://huggingface.co/datasets/Yash908056/medical-vlm-unlearning-corpus.citrus-disease-vlm-instruct
Citrus Disease VLM Instruct
An instruction-tuning dataset for training a small vision-language model (VLM) to look at a photo of a citrus leaf, fruit or shoot, name the disease, pest or nutrient deficiency, explain the cause and symptoms, and recommend both biological/organic and chemical management.
Every example pairs one image with a chat conversation in the format used by TRL's SFTTrainer for multimodal models (Qwen-VL, SmolVLM, Idefics, LLaVA and similar).
What… See the full description on the dataset page: https://huggingface.co/datasets/ysharma/citrus-disease-vlm-instruct.pitvqa-unified-vlm
PitVQA Unified VLM Classification Dataset
Surgical workflow classification dataset for training vision-language models on pituitary surgery phase detection, step recognition, and instrument identification.
🔗 GitHub: https://github.com/matheus-rech/pit_project
🤖 Trained Model: mmrech/pitvqa-qwen2vl-unified
📄 Original Dataset: UCL Research Data Repository
Dataset Description
This dataset contains 5,184 surgical frames with classification annotations for surgical… See the full description on the dataset page: https://huggingface.co/datasets/mmrech/pitvqa-unified-vlm.medical-vlm-unlearning-incremental-subset
Incremental Medical VLM Unlearning Subset
Training-ready, leakage-audited configurations are published independently so
completed sources remain usable after interruption. VQA-RAD (CC0), English
SLAKE (CC BY 4.0), and an NIH ChestXray14 subset include pixels. CheXpert is a
source-controlled manifest whose pixels are resolved from the authorized Kaggle
input and are not redistributed. See progress/latest.json and reports/.
This is a research dataset, not a diagnostic product.… See the full description on the dataset page: https://huggingface.co/datasets/Yash908056/medical-vlm-unlearning-incremental-subset.vlm-compositionality-embeddings
VLM Compositionality Embeddings
Pre-computed image and text embeddings for the thesis "From Euclidean to Hyperbolic Vision-Language Spaces: A Study of Attribute–Object Compositionality" by Meelad Dashti (Politecnico di Torino & University of Twente, 2026).
Code repository: github.com/MelDashti/hyperbolic-vlm-compositionality
Models
Model
Geometry
Architecture
Training Data
CLIP ViT-L/14
Spherical
ViT-L/14
WIT (400M+ pairs)
DINOv2 ViT-L/14
Spherical
ViT-L/14… See the full description on the dataset page: https://huggingface.co/datasets/Meldashti/vlm-compositionality-embeddings.brain-mri-plane-aware-vlm
Brain MRI Plane-Aware VLM Dataset
Dataset Description
This dataset is derived from the BRISC 2025 dataset and has been processed specifically for training Vision-Language Models (VLMs) with plane-aware understanding of brain MRI scans.
Source Dataset
Original dataset: BRISC 2025
The BRISC 2025 dataset contains:
6,000 T1-weighted MRI images
Four tumor classes: Glioma, Meningioma, Pituitary Tumor, and No Tumor
Pixel-wise segmentation masks validated by… See the full description on the dataset page: https://huggingface.co/datasets/AhmadIshaqai/brain-mri-plane-aware-vlm.VLM-CASE_carla_dataset
VLM-CASE scene-context dataset
10,560 CARLA front-camera frames (1280×720) for driving scene-context classification, collected for the paper VLM-CASE: vision-language model enabled context-adaptive safety envelopes for anticipatory safe autonomous driving.
Each frame is labeled with four scene-context fields:
Field
Labels
road_surface
dry, wet, snow
weather
clear, heavy_rain, dense_fog
time_of_day
day, night
illumination_assistance
none, partial, strong… See the full description on the dataset page: https://huggingface.co/datasets/ytj254/VLM-CASE_carla_dataset.revisable-vlm-memory-results
Revisable VLM memory: artifacts, results, and plans
This dataset repository archives frozen representation artifacts, evaluation
reports, causal-intervention outputs, and preregistered execution plans for
Yunbo-max/revisable-vlm-memory.
It does not redistribute TAP-Vid images or model weights.
Current status (2026-08-18)
The frozen 3B K/V diagnostics previously showed held-out signal for simple
visibility and moving/static variables under their original two-frame… See the full description on the dataset page: https://huggingface.co/datasets/humanlong/revisable-vlm-memory-results.brain-mri-plane-aware-vlm
Brain MRI Plane-Aware VLM Dataset
Dataset Description
This dataset is derived from the BRISC 2025 dataset and has been processed specifically for training Vision-Language Models (VLMs) with plane-aware understanding of brain MRI scans.
Source Dataset
Original dataset: BRISC 2025
The BRISC 2025 dataset contains:
6,000 T1-weighted MRI images
Four tumor classes: Glioma, Meningioma, Pituitary Tumor, and No Tumor
Pixel-wise segmentation masks validated… See the full description on the dataset page: https://huggingface.co/datasets/zjj30/brain-mri-plane-aware-vlm.