datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
chitralekha
Chitralekha
Dataset Details
Dataset Version
Some of the fonts do not have proper letters/rendering of different telugu letter combinations. Those have been removed as much as I can find them. If there are any other mistakes that you notice, please raise an issue and I will try my best to look into it
Dataset Description
This extensive dataset, hosted on Huggingface, is a comprehensive resource for Optical Character Recognition (OCR) in the Telugu… See the full description on the dataset page: https://huggingface.co/datasets/gksriharsha/chitralekha.Chicks4FreeID
Dataset Card for Chicks4FreeID
The very first publicly available dataset for chicken re-identification.
1 Dataset Details
1.1 Dataset Description
The Chicks4FreeID dataset contains top-down view images of individually segmented and annotated chickens (with roosters and ducks also possibly present and labeled as such). 11 different coops with 54 individuals were visited for manual data collection. Each of the 677 images depicts at least one chicken. The… See the full description on the dataset page: https://huggingface.co/datasets/dariakern/Chicks4FreeID.chihayafuru
Bangumi Image Base of Chihayafuru
This is the image base of bangumi Chihayafuru, we detected 58 characters, 8676 images in total. The full dataset is here.
Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters'… See the full description on the dataset page: https://huggingface.co/datasets/BangumiBase/chihayafuru.chicago-grantpark-photogrammetry
Chicago / Grant Park — Aerial Photogrammetry + Terrestrial Laser Dataset
2,751 aerial photos (45.0 GB) plus the terrestrial laser scans (9.3 GB, 43 stations) over
Grant Park and downtown Chicago, June 2020. CC BY 4.0.
⬇ Download
→ huggingface.co/datasets/Matt1up/chicago-grantpark-photogrammetry
Browse the Files tab and take what you want — no account needed. The 54 GB of imagery and
laser scans lives there because GitHub won't host files that size;… See the full description on the dataset page: https://huggingface.co/datasets/Matt1up/chicago-grantpark-photogrammetry.chinese-painting-collection
Chinese Painting Collection
91,438 images of Chinese paintings with bilingual (Chinese/English) VLM captions,
calligraphy OCR transcriptions, view-type classification, a long caption on part
of the set, and foreign-object detection with one final crop box per image.
Sources
Component
Source
Images
Image license
npm_tw_c0–npm_tw_c3
National Palace Museum (Taipei) Open Data
86,666
Taiwan Open Government Data License v1 (attribution required)
met_china… See the full description on the dataset page: https://huggingface.co/datasets/kaupane/chinese-painting-collection.regs-chilloutmixChinese_Landscape_Painting
数据集名称
Chinese_Landscape_Painting
数据集简介
这是一份为南京大学智能科学与技术专业大二秋季学期课程人工智能导论课程的项目训练而搭建的数据集。
由于目前较大规模、高质量、且适应现代flux模型的高分辨率的山水画数据集稀缺，故我们搭建了这个数据集，以进行flux模型的lora微调训练。
数据集包含了1017张局部图片，79张全景图片，全部采样自中国山水画的十大名画，并全部带有精细的严格结构化标注。
如果你想使用该数据集进行flux模型训练，可以直接下载并自行修改相应的子文件夹名称以改变每张图片的训练次数。
引用说明
如果您在研究或项目中使用了本数据集，请按以下格式引用：
BibTeX:
@dataset{Chinese_Landscape_Painting,
author = {Wei Liangxu},
title = {Chinese_Landscape_Painting},
year = {2025}… See the full description on the dataset page: https://huggingface.co/datasets/AmazarashiEndure/Chinese_Landscape_Painting.LLaVA-Instruct-600K-Chinese
仿照 LLaVA-Instruct-150K ，使用 Qwen2.5-VL-32B-Instruct 合成的用于微调中文VLM的数据；也可以与英文数据集混合使用，训练多语言VLM
任务类型为基于单张图片的问答和对话，每个样本都对应一张不同的图片，其中大部分图片包含中文字符，更适合中文场景下视觉语言模型的训练。
图片从各类中文网站上爬取
包含3类任务：日常对话、复杂推理、描述图片。日常对话通常是5轮对话，其余任务是1轮对话。
每种任务的数量如下：
任务类型
数量
日常对话
247,431
复杂推理
194,646
描述图片
199,791
用于生成对话数据的prompt如下
日常对话
设计一个你和一个询问这张照片的人之间的对话。答案应该是视觉AI助手看到图像并回答问题的语气。
你需要提出不同的问题并给出相应的答案。问题可以包括询问图像视觉内容的问题，包括对象类型、对象计数、对象动作、对象位置、对象之间的相对位置等。必须是有明确答案的问题，即
（1） 人们可以在图像中明确看到问题所问的内容，并且可以自信地回答；
（2）… See the full description on the dataset page: https://huggingface.co/datasets/opencsg/LLaVA-Instruct-600K-Chinese.ChineseTrafficRegulatorySignDataBase
CTRSDB: Chinese Traffic Regulatory Sign DataBase
数据集简介
CTRSDB是聚焦中国道路场景限速、禁行、让行三类核心管制交通标志的目标检测专用数据集，专为边缘端轻量级交通目标识别模型训练优化，覆盖阴天、雨雾、信号干扰等真实复杂道路场景，完美适配YOLO系列等主流检测模型。
核心亮点
场景针对性强：聚焦自动驾驶、辅助驾驶最核心的管制类交通标志，无冗余类别，标注精度高
恶劣场景适配：通过AI生成扩增了雨雾极端天气低能见度场景数据，提升模型在复杂天气下的鲁棒性
开箱即用：原生支持YOLO格式标注，配套训练配置文件，clone后可直接用于模型训练
合规开源：遵循CC BY-NC-SA 4.0协议，仅用于学术学习与非商用场景
数据集详情
项目
详情
总图片数量
3960张
核心类别
限速、禁行通行、禁止驶入、减速让行、停车让行
标注格式
YOLO原生txt格式
数据集划分
训练集:验证集:测试集=7:2:1… See the full description on the dataset page: https://huggingface.co/datasets/EpicZhang/ChineseTrafficRegulatorySignDataBase.RPINEchinese_landscape_paintings
Dataset Card for "chinese_landscape_paintings"
More Information needed
medical-prescription-datasetChinese_Children_Image_Captioning_Dataset_Split0
CODP-1200：Children Oral Description of Picture（Chinese-Child-Captions）
CODP-1200: An AIGC based benchmark for assisting in child language acquisition
数据集介绍
目前已知最大的儿童图像描述数据集，children image captioning
共有1200张图片
每张图片对应五个中文描述，每两张图片为一组
描述文字600*5=3000
如果使用CODP-1200数据集，请引用以下文章
@article{LENG2024102627,
title = {CODP-1200: An AIGC based benchmark for assisting in child language acquisition},
journal = {Displays},
volume = {82},
pages = {102627},
year =… See the full description on the dataset page: https://huggingface.co/datasets/svjack/Chinese_Children_Image_Captioning_Dataset_Split0.imagenet-lt-v2china
China AOI
Randomly sampled 5000 data tiles (3000 for training, and 1000 for validation and testing).
Occasionally, not all tiles were available for all datasets. We include a detailed breakdown of the number of chips per dataset below.
Datakind
Chips
s1grd-2020
5000
gssic
5000
gunw_2020-01-01_2020-03-31
4354
s2rgbm-2020
5000
biomass-2020
5000
esaworldcover-2020
5000
modis44b006veg
5000
ghsbuilts-2020
5000
srtmdem
5000
We provide '.csv' files with… See the full description on the dataset page: https://huggingface.co/datasets/M3LEO-miniset/china.reddit
Dataset Card for "reddit"
More Information needed
chimmd
ChiMMD: a Chicago Multi-Modal Dataset for Socio-economic and Urban Analysis
Socio-economic data plays an important role in understanding
how different aspects of a city—such as traffic, housing, social
activity—interact. While many unimodal datasets exist for major
cities, multi-modal datasets remain limited. In this work, we introduce ChiMMD, a large-scale multi-modal dataset for the city of
Chicago that integrates traffic, real estate, points of interest, and
social media activity… See the full description on the dataset page: https://huggingface.co/datasets/chimmd/chimmd.English-Chinese-Toxic-Contentruneterra-chill-assetsgarbage-classify-with-chineseCHIP
CHIP: A multi-sensor dataset for 6D pose estimation of chairs in industrial settings
🏠 Homepage
📄 Paper
Introduction
Accurate 6D pose estimation of complex objects in 3D environments is essential for effective robotic manipulation. Yet, existing benchmarks fall short in evaluating 6D pose estimation methods under realistic industrial conditions, as most datasets focus on household objects in domestic settings, while the few available industrial… See the full description on the dataset page: https://huggingface.co/datasets/FBK-TeV/CHIP.final_NPCzenodo-second-hand-fashion-v3
Second-Hand Fashion Dataset — wide (one row per garment)
Repack of Zenodo record 10.5281/zenodo.13788681 (Nauman et al., RISE + Wargön Innovation + Myrorna, CC-BY-4.0) into a one-row-per-garment wide layout so the HF dataset viewer shows every attribute — three images plus 25 metadata columns — on a single row.
Previous v3 releases stored one row per (garment, view) with satellite tables that had to be joined manually. That layout is preserved in git history if you need it; the… See the full description on the dataset page: https://huggingface.co/datasets/chibifire/zenodo-second-hand-fashion-v3.dancing-chibi-figures
Dancing Chibi Figures — v0.1
One template Q-version (chibi) character, animated by 1,430 motion clips, rendered with exact labels and motion-grounded captions — and paired frame-for-frame with Dancing Stick Figures.
1,423 clips · 6 s @ 20 fps · 128×128 RGBA · 514,800 frames · 143 text prompts × 10 seeds × 3 cameras ·
every frame carries the 3D skeleton, camera, depth, camera-space normals, part segmentation, motion events and five
levels of caption.
One row per motion group;… See the full description on the dataset page: https://huggingface.co/datasets/sprited/dancing-chibi-figures.CHIRLA
Dataset Card for CHIRLA
CHIRLA (Comprehensive High-resolution Identification and Re-identification for Large-scale Analysis) is a long-term, multi-camera person Re-Identification (Re-ID) and tracking dataset. It spans 7 months, 7 cameras, 22 identities, and ~1M identity-annotated bounding boxes across ~596k frames, captured in connected indoor environments.
Dataset Details
Dataset Description
CHIRLA targets long-term appearance change (e.g., clothing changes… See the full description on the dataset page: https://huggingface.co/datasets/bdager/CHIRLA.chiyumahounomachigattatsukaikata
Bangumi Image Base of Chiyu Mahou No Machigatta Tsukaikata
This is the image base of bangumi Chiyu Mahou no Machigatta Tsukaikata, we detected 57 characters, 5047 images in total. The full dataset is here.
Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual. If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples… See the full description on the dataset page: https://huggingface.co/datasets/BangumiBase/chiyumahounomachigattatsukaikata.editscore-rl-train
Introduction
Training data for OmniGen2 Online-RL using EditScore.
Usage
# meta file: rl.jsonl
# images:
cat images_part_* > images.tar.gz && tar -xzvf images.tar.gz
Citation
@article{luo2025editscore,
title={EditScore: Unlocking Online RL for Image Editing via High-Fidelity Reward Modeling},
author={Xin Luo and Jiahao Wang and Chenyuan Wu and Shitao Xiao and Xiyan Jiang and Defu Lian and Jiajun Zhang and Dong Liu and… See the full description on the dataset page: https://huggingface.co/datasets/chibifire/editscore-rl-train.chinese-traditional-cultureperceptual-constancy
Perceptual Constancy
Perceptual Constancy is a multimodal benchmark designed to evaluate high-level perceptual invariance in large vision-language models (VLMs). It probes a model’s understanding of physical and geometric stability under varying sensory appearances. This dataset is part of the Grow AI Like a Child benchmark initiative.
🧠 Dataset Overview
The Perceptual Constancy dataset focuses on appearance-invariant reasoning using both static images and short… See the full description on the dataset page: https://huggingface.co/datasets/grow-ai-like-a-child/perceptual-constancy.anny-render-corpus-generated-train
anny-render-corpus-generated
Images generated by OmniGen2 from the constructed renders in
chibifire/anny-render-corpus.
Code: weftspun/anny-render-corpus, on the 6-datasource side of the hexagon.
Why this is a separate repository
These are generated synthetic, not constructed. They were sampled from a model rather than
rendered deterministically from a rig, so their labels are inferred and not true by
construction. Our working agreement requires generated data to… See the full description on the dataset page: https://huggingface.co/datasets/chibifire/anny-render-corpus-generated-train.