datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
wds_imagenet_sketchimagenet-sketch-datasketchvlm-physics-ball-drop
SketchVLM: Physics Ball Drop Dataset
This dataset is part of the SketchVLM project, introduced in the paper: SketchVLM: Vision language models can annotate images to explain thoughts and guide users.
Project Page | GitHub | Interactive Demo
Description
SketchVLM is a training-free, model-agnostic framework that enables vision-language models (VLMs) to produce non-destructive, editable SVG overlays on input images to visually explain their reasoning.
The Physics Ball… See the full description on the dataset page: https://huggingface.co/datasets/loganbolton/sketchvlm-physics-ball-drop.splataverse-sketchfab
Splataverse: Sketchfab
imagenet_sketch
Dataset Card for ImageNet-Sketch
This dataset was duplicated from songweig/imagenet_sketch so I could create validation splits and use parquets for caching the dataset instead of requiring python code execution.
The dataset was replicated using the following script:
from datasets import load_dataset, DatasetDict
import os
def main():
ds = load_dataset("songweig/imagenet_sketch", split="train").shuffle(seed=42)
ds_train = ds.select(range(40_000))
ds_validate =… See the full description on the dataset page: https://huggingface.co/datasets/vaughankraska/imagenet_sketch.QuickdrawHDSketch2CodeThe Sketch2Code dataset consists of 731 human-drawn sketches paired with 484 real-world webpages from the Design2Code dataset, serving to benchmark Vision-Language Models (VLMs) on converting rudimentary sketches into web design prototypes.
Each example consists of a pair of source HTML and rendered webpage screenshot (stored in webpages/ directory under name {webpage_id}.html and {webpage_id}.png), as well as 1 to 3 sketches drawn by human annotators (stored in sketches/ directory under name… See the full description on the dataset page: https://huggingface.co/datasets/SALT-NLP/Sketch2Code.sketch-scene
Dataset Card for Sketch Scene Descriptions
Dataset used to train Sketch Scene text to image model
We advance sketch research to scenes with the first dataset of freehand scene sketches, FS-COCO. With practical applications in mind, we collect sketches that convey well scene content but can be sketched within a few minutes by a person with any sketching skills. Our dataset comprises around 10,000 freehand scene vector sketches with per-point space-time information by 100 non-expert… See the full description on the dataset page: https://huggingface.co/datasets/zoheb/sketch-scene.wds_imagenet_sketchobjaversexl_sketchfabsketchybusinessImagenet_Sketchobjaversexl_sketchfab_pmap1objaversexl_sketchfab_pmapsketch_libero_distillThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "panda",
"total_episodes": 182,
"total_frames": 22629,
"total_tasks": 10,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 10,
"splits": {
"train": "0:182"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/ductaingn/sketch_libero_distill.FreeCAD_Sketches_Pics
🧩 FreeCAD Sketch Python Dataset
This dataset contains approximately 1,000 Python files and their corresponding images defining parametric FreeCAD sketches. Each python file represents a geometric sketch scripted using the FreeCAD Python API.
The dataset is intended for training and fine-tuning large language models (LLMs) and vision large language models (vLLMs) and other AI systems to understand and generate CAD-based parametric geometry code, particularly for text-to-CAD and… See the full description on the dataset page: https://huggingface.co/datasets/Yas1n/FreeCAD_Sketches_Pics.SketchGraphstikz-sketch-splits
tikz-sketch-splits
Synthetic-sketch data augmentation splits generated from
loss-boss/tikz-train, for
sketch-to-TikZ model training/evaluation.
Each row in loss-boss/tikz-train has two source variants:
with_text (image_with_text/code_with_text/llm_description_with_text)
without_text (image_without_text_full/code_without_text_full/llm_description_without_text_full only populated for a minority of rows)
For every row processed here, one variant was picked at random (falling back… See the full description on the dataset page: https://huggingface.co/datasets/03kiko/tikz-sketch-splits.BigDocs-Sketch2Flow
Dataset Card for ServiceNow/BigDocs-Sketch2Flow
Dataset Summary
The BigDocs-Sketch2Flow dataset is introduced in the StarFlow paper. It contains workflow diagrams paired with structured JSON workflows for the task of converting sketches or diagrams into executable workflow representations. Samples include both synthetic programmatically generated diagrams and human-created sketches (manual, digital, whiteboard) as well as user interface screenshots.
The dataset supports… See the full description on the dataset page: https://huggingface.co/datasets/ServiceNow/BigDocs-Sketch2Flow.sketchylaion_aesthetics_sketchsketchrefiner-real-world-test-protocolcoco2017_caption_sketchsketchvlm-maze-navigation
SketchVLM: Maze Navigation
This dataset is associated with the paper: SketchVLM: Vision Language Models Can Annotate Images to Explain Thoughts and Guide Users.
SketchVLM is a training-free, model-agnostic framework that enables Vision-Language Models (VLMs) to produce non-destructive, editable SVG overlays on input images to visually explain their answers. The Maze Navigation dataset is one of the benchmarks introduced to evaluate a model's ability to trace a path from start to end… See the full description on the dataset page: https://huggingface.co/datasets/loganbolton/sketchvlm-maze-navigation.dcode-imagenet-sketch
dcode: ImageNet-Sketch to G-code Dataset
A dataset of ImageNet-Sketch images paired with generated G-code for training text-to-gcode diffusion models.
Overview
This dataset enables training models that convert text descriptions directly into G-code for CNC machines, plotters, and polargraph drawing robots.
Feature
Value
Source Images
ImageNet-Sketch
Classes
1,000 ImageNet categories
Images
~50,000 black/white sketches
G-code Files
~200,000 (4 algorithms ×… See the full description on the dataset page: https://huggingface.co/datasets/twarner/dcode-imagenet-sketch.Face-Sketches40
Dataset Card for "Face-Sketches"
This are 40 images of the CUFS Dataset https://www.kaggle.com/datasets/arbazkhan971/cuhk-face-sketch-database-cufs
sketchvlm-connect-dots
SketchVLM: Physics Ball Drop Dataset
This dataset is part of the SketchVLM framework, which enables Vision-Language Models (VLMs) to produce non-destructive, editable SVG overlays on input images to visually explain their reasoning. The Physics Ball Drop benchmark specifically evaluates a model's ability to predict the trajectory of a ball through obstacles (based on PHYRE).
Paper: SketchVLM: Vision language models can annotate images to explain thoughts and guide users
Project… See the full description on the dataset page: https://huggingface.co/datasets/loganbolton/sketchvlm-connect-dots.hyper-scenery-sketches-dataset
Shiro's Hyper-Scenery Dataset
This dataset contains 1000 synthetic image-text pairs used to train the Hyper-Brain.
Images: High-detail sceneries and sketches.
Prompts: Detailed 8K descriptive text for each image.
ImageNet-Sketch-HQA Selection From https://huggingface.co/datasets/songweig/imagenet_sketch (actually I download from https://opendatalab.com/OpenDataLab/ImageNet-Sketch and the hash is same)
The original ImageNet-Sketch data set consists of 50000 images, 50 images for each of the 1000 ImageNet classes. We construct the data set with Google Image queries "sketch of __", where __ is the standard class name. We only search within the "black and white" color scheme. We initially query 100 images for every class… See the full description on the dataset page: https://huggingface.co/datasets/tumuyan2/ImageNet-Sketch-HQ.sketch2stl-sketches-image
sketch2stl-sketches-image
36 original 224 x 224 line sketches, each labelled with whether the drawing is a flat outline meant to be
extruded or a depiction of a 3D object, plus 360 label-preserving augmented images.
1. Purpose
Built for Homework 1 of Designing with AI, in direct support of my Project 1 system: a Gradio app that turns
a 2D sketch into an editable, 3D-printable STL.
This dataset sits directly under that pipeline. The input to my system is a drawing… See the full description on the dataset page: https://huggingface.co/datasets/sunkaiwen/sketch2stl-sketches-image.