datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
wds_objectnetwds_imagenet_sketchwds_imagenet-rwds_imagenet-ahdr-demo-clips
HDR Demo Clips (Lightricks SDR→HDR)
Paired SDR (input) / HDR (output) frame sequences from the Lightricks SDR-to-HDR pipeline (IC-LoRA on LTX-2).
Each clip contains:
hdr_exr/frame_XXXXX.exr — HDR output (f16, linear Rec.709/sRGB primaries, scene-referred)
sdr_png/frame_XXXXX.png — SDR input (8-bit sRGB, display-referred)
thumbnail.jpg — 280px preview from the middle frame
Dimensions: HDR is symmetrically cropped from SDR to match model-friendly dimensions (typically 28–56px… See the full description on the dataset page: https://huggingface.co/datasets/oumoumad/hdr-demo-clips.wds_imagenet1kwds_imagenetv2clientsClinicalAgentBenchMore detail about the dataset and the agentic framework can be found in https://github.com/BlueZeros/ReflecTool
instructpix2pix-clip-filtered
Dataset Card for InstructPix2Pix CLIP-filtered
Dataset Summary
The dataset can be used to train models to follow edit instructions. Edit instructions
are available in the edit_prompt. original_image can be used with the edit_prompt and
edited_image denotes the image after applying the edit_prompt on the original_image.
Refer to the GitHub repository to know more about
how this dataset can be used to train a model that can follow instructions.
Supported Tasks… See the full description on the dataset page: https://huggingface.co/datasets/timbrooks/instructpix2pix-clip-filtered.wds_fer2013wds_sun397CVC-ClinicDB
CVC-ClinicDB: Colonoscopy Polyp Segmentation Dataset
Dataset Description
CVC-ClinicDB is a colonoscopy polyp segmentation dataset containing 612 frames extracted from 29 colonoscopy sequences with corresponding ground truth segmentation masks.
Task: Binary segmentation (polyp vs. background)
Modality: Colonoscopy
Format: PNG images (384x288 pixels) with binary masks
Splits: Training, Validation, and Test sets
Dataset Structure
CVC-ClinicDB/
├── train/
│… See the full description on the dataset page: https://huggingface.co/datasets/Aeoo/CVC-ClinicDB.wds_carsSMAT-CLIP8
SMAT · CLIP8
The frozen train/dev/test splits for Table 2 of SMAT: Simple and Efficient Merge-Aware Training. Eight image-classification tasks, with 200 development examples per task. Original image bytes, labels and class metadata are preserved.
Paper · GitHub & usage
This is a benchmark repackaging, not newly collected data. Original dataset rights and usage terms apply; sources and attribution. No additional rights to the images are granted.
Arabic_Flicker_8kPMC-Clinical-VQA
PMC-VQA: A Large-Scale Visual Question Answering Dataset for Clinical Figures
This dataset contains over 1,700,000 Visual Question Answering (VQA) samples derived from figures and charts in biomedical articles from PubMed Central (PMC).
This is a preliminary release. A full dataset card and an accompanying research paper are currently in preparation.
Raw version of this dataset with licenses and metadata can be found on Hugging Face: DermaVLM/pmc_clinical_VQA_raw
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/DermaVLM/PMC-Clinical-VQA.M-BEIR-CIRR-Imageswds_flickr30kwds_vtab-caltech101wds_fgvc_aircraftwds_vtab-cifar10wds_mscoco_captionswds_vtab-eurosat22k_CLIP_Negitivewds_vtab-petswds_vtab-pcamwds_food101Real-UI-Clickboxes
RUC: Real UI Clickboxes
Click carefully, even when the page is trying to trick you! 👀
Official Hugging Face release for RUC: Real UI Clickboxes, the dataset accompanying our ACL 2026 paper Don't Click That: Teaching Web Agents to Resist Deceptive Interfaces on deceptive UI understanding for web agents.
ACL Anthology: https://aclanthology.org/2026.acl-long.310/
PDF: https://aclanthology.org/2026.acl-long.310.pdf
DOI: https://doi.org/10.18653/v1/2026.acl-long.310… See the full description on the dataset page: https://huggingface.co/datasets/DUDE-Framework/Real-UI-Clickboxes.wds_vtab-cifar100