datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IconArt🖼️ The dataset IconArt dataset was introduced in the following paper : "Weakly Supervised Object Detection in Artworks" Gonthier et al. ECCV 2018 Workshop Computer Vision for Art Analysis - VISART 2018.
This datasest is designed to evaluate Weakly Supervised object detection methods in paintings.
You can also find project page for the paper here.
This dataset contains 5955 images (from WikiCommons) : a train set of 2978 images and a test set of 2977 images (for classification task). 1480 of… See the full description on the dataset page: https://huggingface.co/datasets/NGonthier/IconArt.win-tiles-icons
Dataset Details
Dataset Description
The pictures were taken from the Discord server https://discord.gg/VMz3GD4d
Relevance as of 29.11.2024
I tried to classify some parts, but I have clumsy and crooked paws to make a proper classifier for all this.
ICON-QA
Large-scale Multi-modality Models Evaluation Suite
Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval
🏠 Homepage | 📚 Documentation | 🤗 Huggingface Datasets
This Dataset
This is a formatted version of ICONQA. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.
@inproceedings{lu2021iconqa,
title = {IconQA: A New Benchmark for Abstract Diagram Understanding and… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/ICON-QA.IconQAretro-icon-rl
RetroIcon-RL: 32x32 Retro Pixel-Art Icon Generation with Deterministic Verification
This repository implements RetroIcon-RL — training and evaluating small code models with Reinforcement Learning (RL) and programmatic verification to generate consistent, crisp retro pixel-art icon packs from natural language prompts using sharp SVG block geometry.
🎯 Phase 1 — The 32x32 Task Specification
Canvas: Exactly $32 \times 32$ integer grid (viewBox="0 0 32 32").… See the full description on the dataset page: https://huggingface.co/datasets/mayank-dubey-ai/retro-icon-rl.IconAssetsios-app-icons
IOS App Icons
Overview
This dataset contains images and captions of iOS app icons obtained from the iOS Icon Gallery. Each image is paired with a generated caption using a Blip Image Captioning model. The dataset is suitable for image captioning tasks and can be used to train and evaluate models for generating captions for iOS app icons.
Images
The images are stored in the 'images' directory, and each image is uniquely identified with a filename (e.g.… See the full description on the dataset page: https://huggingface.co/datasets/ppierzc/ios-app-icons.MMSVG-IconOmniSVG: A Unified Scalable Vector Graphics Generation Model
![Project Page]
Dataset Card for MMSVG-Icon
Dataset Description
This dataset contains SVG icon examples for training and evaluating SVG models for text-to-SVG and image-to-SVG task.
Dataset Structure
Features
The dataset contains the following fields:
Field Name
Description
id
Unique ID for each SVG
svg
SVG code (resized to 200×200, simplified with picosvg)
description… See the full description on the dataset page: https://huggingface.co/datasets/OmniSVG/MMSVG-Icon.pid-icons-merged3d_icon
3D icons Dataset
This dataset contains free-licensed images, downloaded from unsplash. Curated and created by:
Maria Shalabaieva
Alexander Shatov
IconQA_liteeasyr1-126k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP-aug-jitter
easyr1-126k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP-aug-jitter
Augmented version of datasets/easyr1-63k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP with coordinate jitter.
For each original example, 1 additional copies were created. Each copy
randomly jitters the target coordinate by ±1 pixel in both X and Y. The
assistant coordinate in messages is updated, and bbox/normalized_bbox
are shifted when present.… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-cua-dev/easyr1-126k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP-aug-jitter.easyr1-63k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP
easyr1-63k-hard-qwen7b-easy-gta1-nores-jedi-fix-synced-ui-vision-grounding-pro-apps-manually-labeled-icon-data-from-yt-4MP
Merged dataset composed of the following sources:
/Users/anasawadalla/Desktop/easyr1-57k-hard-qwen7b-easy-gta1-4MP-nores-jedi-fix-synced (57011 samples in split train)
ui-vision-grounding-4MP (5790 samples in split train)
easyr1-v2-pro-apps-manually-labeled-icon-data-from-yt-4MP (230 samples in split train)
Summary
Generated on: 2025-09-10… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-cua-dev/easyr1-63k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP.brill_iconclass
Dataset Card for Brill Iconclass AI Test Set
Dataset Summary
A test dataset and challenge to apply machine learning to collections described with the Iconclass classification system.
This dataset contains 87749 images with Iconclass metadata assigned to the images. The iconclass metadata classification system is intended to provide 'the comprehensive classification system for the content of images.'.
Iconclass was developed in the Netherlands as a standard… See the full description on the dataset page: https://huggingface.co/datasets/biglam/brill_iconclass.ICON_Materialmm_iconqaeasyr1-63k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP-answer-keyiconclass-vlmIconQA_filterediconclass-vlm-sfticonclass-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.easyr1-63k-nores-jedi-fix-synced-ui-vision-manually-labeled-icon-data-from-yt-4MP-dense-rewardicon-q1Генерация датасета скрипт как есть для python 3.10, 3.12
import os
import random
import glob
import json
import numpy as np
from PIL import Image, ImageDraw
target_dataset_dir = "dataset"
icons_root = "icons"
img_size = 640
page_idx = 0 # Начальный индекс
classes_file = os.path.join(target_dataset_dir, '..', 'classes.txt')
if not os.path.exists(classes_file):
classes_file = 'classes.txt'
if not os.path.exists(classes_file):
# Если файла classes.txt нет, создаем его автоматически на… See the full description on the dataset page: https://huggingface.co/datasets/Sanchezzzhak/icon-q1.Anime_Iconsosworld-iconspokemon-icons
Dataset Card for pokemon-icons
Dataset Summary
Pokemon Icons. Most of them are collected and cropped from screenshots captured in Pokémon Sword and Shield.
Supported Tasks and Leaderboards
Image classification
iconclass_with_splitsStability_Landscapes
📚 Overview: Kuramoto-Stability-Landscape (KSL)
The dataset consists of synthetic oscillator network topologies created using a random growth algorithm. Dynamical simulations are conducted by applying the second-order Kuramoto model to the nodes. This model is widely recognized for its effectiveness in analyzing synchronization dynamics in complex systems such as power grids and neuronal networks.
Two ensembles are included, each containing 10,000 unique network topologies:… See the full description on the dataset page: https://huggingface.co/datasets/PIK-ICoNe-landscape/Stability_Landscapes.easyr1-v2-pro-apps-with-electron-data-plus-icon-data-from-yt-2k-4MP
easyr1-v2-pro-apps-with-electron-data-plus-icon-data-from-yt-2k-4MP
This dataset was generated using the EasyR1 grounding dataset pipeline.
Generation Details
Generated on: 2025-09-03 08:32:38 UTC
Script: push_easyr1_to_hf.py
Data directory: datasets
Parameters Used
Maximum samples: 2000
Image resize (max megapixels): 4.0 MP
Minimum native image resolution: 0.0 MP
Prompt format: gta1
Output format: coordinates
Random seed: 42
Resampling enabled: False
Icon… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations-cua-dev/easyr1-v2-pro-apps-with-electron-data-plus-icon-data-from-yt-2k-4MP.orc-assist-icons