datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SQuADDS_Layouts
SQuADDS Layouts - versioned GDS artifacts for superconducting quantum hardware
SQuADDS Layouts is the geometry-artifact companion to
SQuADDS_DB, the
Superconducting Qubit And Device Design and Simulation Database. It provides
checksum-verified GDS files, stable geometry identities, and machine-readable
geometry metadata so a simulation result can be traced to the exact layout
that produced it.
Homepage: https://lfl-lab.github.io/SQuADDS/
Repository:… See the full description on the dataset page: https://huggingface.co/datasets/SQuADDS/SQuADDS_Layouts.LayoutSAM
LayoutSAM Dataset
Overview
The LayoutSAM dataset is a large-scale layout dataset derived from the SAM dataset, containing 2.7 million image-text pairs and 10.7 million entities. Each entity is annotated with a spatial position (i.e., bounding box) and a textual description.
Traditional layout datasets often exhibit a closed-set and coarse-grained nature, which may limit the model's ability to generate complex attributes such as color, shape, and texture.… See the full description on the dataset page: https://huggingface.co/datasets/HuiZhang0812/LayoutSAM.FloorplanQA-Layouts
FloorplanQA (Layouts Only)
This repository contains 2,000 JSON layouts used in the paper:
"FloorplanQA: A Benchmark for Spatial Reasoning in LLMs Using Structured Representations"
arXiv: https://arxiv.org/abs/2507.07644
Project Page: https://olddelorean.github.io/FloorplanQA/
Contents
600 synthetic kitchens
600 synthetic living rooms
600 synthetic bedrooms
200 layouts derived from HSSD-200
The release includes only the layouts.
Structure
layouts/… See the full description on the dataset page: https://huggingface.co/datasets/OldDelorean/FloorplanQA-Layouts.LayoutSAM-eval
LayoutSAM-eval Benchmark
Overview
LayoutSAM-Eval is a comprehensive benchmark for evaluating the quality of Layout-to-Image (L2I) generation models. This benchmark assesses L2I generation quality from two perspectives: region-wise quality (spatial and attribute accuracy) and global-wise quality (visual quality and prompt following). It employs the VLM’s visual question answering to evaluate spatial and attribute adherence, and utilizes various metrics including IR score… See the full description on the dataset page: https://huggingface.co/datasets/HuiZhang0812/LayoutSAM-eval.adresyze-ad-layouts
AdResyze Ad Layout Annotations (v2)
Layout annotations for 302 Indian brand advertisements: which region of an ad is the
logo, the headline, the call to action, the product, the price, the background — and
where each one sits.
Built for AdResyze, which uses these
layouts to reflow a single creative into every platform aspect ratio without squashing
the logo or cropping the call to action.
Try it: builditwithgk--adresyze-ui.modal.run
· Code:… See the full description on the dataset page: https://huggingface.co/datasets/builditwithgk/adresyze-ad-layouts.GenManip-Banana-Layoutsmyanmar_complex_document_layouts
🇲🇲 Myanmar Complex Document Layouts
A large-scale, high-quality synthetic dataset containing 17,632 images of complex document layouts, dashboards, and infographics entirely in the Myanmar (Burmese) language.
This dataset is specifically designed to train and benchmark modern Computer Vision and multimodal LLMs on complex Myanmar typography, structured data, and diverse graphical layouts.
📊 Dataset Overview
Total Images: 17,632 high-resolution pages.… See the full description on the dataset page: https://huggingface.co/datasets/freococo/myanmar_complex_document_layouts.rb-box-layouts-inlinelayouts_donut_1
Dataset Card for "layouts_donut_1"
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donut_two_layouts
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three_layouts
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dynamic_layoutsrb-box-layoutsdino_coco_image_layoutslayouts_spanish2
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layouts_donut
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layouts_spanish
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Nayana-Seed-en-100k-safedocs-layouts