datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
emit-test-dataset
Dataset Card for EMIT-MSeg Dataset
If you use this dataset, please cite our article:
@misc{herec2026fastmethanedetectionpipeline,
title={A Fast Methane Detection Pipeline on Board Satellites Based on Mag1c-SAS and LinkNet},
author={Jonáš Herec and Vít Růžička and Rado Pitoňák and Jan Sedmidubsky},
year={2026},
eprint={2606.03675},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2606.03675},
}… See the full description on the dataset page: https://huggingface.co/datasets/onboard-coop/emit-test-dataset.scarlet-test-dataLora_Cloud_Dataset_Test
VLM Safety Inspector (2B / 4B / 8B) Mac 端评测与闭环套件
VLM Safety Inspector (2B / 4B / 8B) Mac 端闭环评测包
本目录是一个完全自包含（Self-Contained）的独立评测套件，专门适配您的 Mac（Apple Silicon / MPS）目录布局。
本目录是一个完全独立、自包含（Self-Contained）的评测套件，专为在 Mac (Apple Silicon / MPS) 上运行。
一、Mac 端文件布局自动识别（针对您的 iild 结构）
一、核心架构与流水线
评测脚本已内置针对您 Mac 端 iild/ 目录结构的全自动路径解析器：
在本次评测中，整条上行与闭环流水线严格遵循您的设想：
上游双塔一致性（In-Domain Consistency）：
输入给 Planner 和 Inspector 的 150 个任务安全规则，已在 PC 端由纯 Legacy… See the full description on the dataset page: https://huggingface.co/datasets/lvesucces/Lora_Cloud_Dataset_Test.isu-challenge-dataset
Dataset Card for ISU Challenge Dataset
Dataset Summary
ISU Challenge Dataset is a multi-modal in-cabin automotive dataset with a controlled synthetic core and paired real-reference scenes.
The synthetic core contains 1,000 synchronized Blender-rendered samples with:
RGB render
depth (EXR and PNG)
instance segmentation
canny edge map
structured scenario labels
An additional 60 paired real-reference scenes occupy sample_00000 through sample_00059. Each paired… See the full description on the dataset page: https://huggingface.co/datasets/ISU-Test/isu-challenge-dataset.smart-product-pricing-2025_test_datatestdatatestdatatest-big-dataset
Dataset Card for Danish WIT
Dataset Summary
Google presented the Wikipedia Image Text (WIT) dataset in July
2021, a dataset which contains
scraped images from Wikipedia along with their descriptions. WikiMedia released
WIT-Base in September
2021,
being a modified version of WIT where they have removed the images with empty
"reference descriptions", as well as removing images where a person's face covers more
than 10% of the image surface, along with inappropriate images… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/test-big-dataset.vla-data-aug-veo31-test
VLA Data Augmentation (Veo 3.1)
Synthetic video samples for vision-language-action (VLA) data augmentation: 8s clips generated with Veo 3.1 on Vertex AI, with per-clip frames and prompt metadata.
Dataset summary
Model: veo-3.1-generate-001
Duration: 8 seconds per clip, 16:9, no audio
Content: Multi-scene prompts (meetings, care, logistics, office, etc.)
First batch (runs/): 11 prompts × 6 clips each (English prompts); see RUN_PLAN_5D_11PROMPTS_X6.md. 補齊至每題 18… See the full description on the dataset page: https://huggingface.co/datasets/sou35/vla-data-aug-veo31-test.Coursera_homework_dataset_test
Dataset Card for Homework Test Set for Coursera MOOC - Hands Data Centric Visual AI
This dataset is the test dataset for the homework in the Hands-on Data Centric Visual AI Coursera course.
This is a FiftyOne dataset with 4572 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'max_samples'… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Coursera_homework_dataset_test.image-matching-test-datasettest-data
Data for Nunchaku Tests
Coursera_lecture_dataset_test
Dataset Card for Lecture Test Set for Coursera MOOC - Hands Data Centric Visual AI
This dataset is the test dataset for the in-class lectures of the Hands-on Data Centric Visual AI Coursera course.
This is a FiftyOne dataset with 4159 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Coursera_lecture_dataset_test.test-dataset-v1ssynth_data-test
S-SYNTH
S-SYNTH is an open-source, flexible skin simulation framework to rapidly generate synthetic skin models and images using digital rendering of an anatomically inspired multi-layer, multi-component skin and growing lesion model. It allows for generation of highly-detailed 3D skin models and digitally rendered synthetic images of diverse human skin tones, with full control of underlying parameters and the image formation process.
Framework Details
S-SYNTH… See the full description on the dataset page: https://huggingface.co/datasets/didsr/ssynth_data-test.test_datasetautotrain-data-the_test_pictureskorean_wild_dataset_testexternal_data_test_examplerestoration_test_data
Restoration Test Data
This dataset repo stores curated test data used by restoration_agent wrapper and eval scripts.
Scope:
Test inputs only.
No model weights.
No prediction outputs.
No runtime environments.
No logs.
No known-invalid legacy HDF5 files.
Layout
Upload status as of 2026-05-08:
All-in-one, HSI, MP-HSIR raw zips, and Haze1k test splits are uploaded.
SEN12MS-CR-TS america and europa raw archives are uploaded; africa, asiaEast, and asiaWest raw archives are… See the full description on the dataset page: https://huggingface.co/datasets/zzqsb/restoration_test_data.text_det_test_dataset
文本检测测试集
数据集简介
该测试集包括卡证类、文档类和自然场景三大类。其中卡证类有82张，文档类有75张，自然场景类有55张。
该数据集可以结合文本检测指标评测库-TextDetMetric使用，快速评测各种文本检测算法。
关于该数据集，欢迎小伙伴贡献更多数据呦！有任何想法，可以前往issue讨论。
数据集支持的任务
可用于自定义数据集下的模型验证和性能评估等。
数据集加载方式
from datasets import load_dataset
dataset = load_dataset("SWHL/text_det_test_dataset")
test_data = dataset['test']
print(test_data)
数据集生成的相关信息
原始数据
数据来源于网络，如侵删。
数据集标注… See the full description on the dataset page: https://huggingface.co/datasets/SWHL/text_det_test_dataset.test-data-bonsai2test_datatest-image-classifier-datasetAdaGaR_testdatazalo-ai-2025-public-test-data-v2
Zalo AI Challenge 2025 - RoadBuddy Public Test Data V2set
This dataset contains public test data v2 for the RoadBuddy – Understanding the Road through Dashcam AI challenge from Zalo AI Challenge 2025.
Dataset Description
The challenge aims to build a driving assistant capable of understanding video content from dashcams to quickly answer questions about traffic signs, signals, and driving instructions in Vietnam.
Dataset Structure
Files
frames/:… See the full description on the dataset page: https://huggingface.co/datasets/OpenHay/zalo-ai-2025-public-test-data-v2.DAEFR_test_datasetsWe evaluate DAEFR on one synthetic dataset CelebA-Test, and two real-world datasets LFW-Test and WIDER-Test.
Datasets
Filename
Short Description
Source
CelebA-Test (HQ)
celeba_512_validation.zip
3000 (HQ) ground truth images for evaluation
RestoreFormer
CelebA-Test (LQ)
self_celeba_512_v2.zip
3000 (LQ) synthetic images for testing
Ourselves
LFW-Test (LQ)
lfw_cropped_faces.zip
1711 real-world images for testing
VQFR… See the full description on the dataset page: https://huggingface.co/datasets/LIAGM/DAEFR_test_datasets.test_lerobot_dataset
DataArm Dataset
Dataset created with DataArm robot system for LeRobot v3.0 compatibility.
Dataset Description
DataArm teleoperation
Dataset Structure
episodes.json: Episode information
train/: Training data in Parquet format
meta/: Metadata and dataset card
images/: Camera frames (if available)
Features
observation.state: float32 [8] (observation)
observation.gripper_state: float32 [1] (observation)
observation.images.cam_left: uint8 [480, 640, 3]… See the full description on the dataset page: https://huggingface.co/datasets/lr-2002/test_lerobot_dataset.test_vla_data8This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.0",
"robot_type": "aloha-stationary",
"total_episodes": 2,
"total_frames": 421,
"total_tasks": 1,
"total_videos": 0,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:2"
},
"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/mphielipp/test_vla_data8.table_rec_test_dataset
表格识别测试集
数据集简介
该数据集包含百度生成工具 20 张有线 20 张无线，wtw 数据集 15, pubnet val 集 20 张，自我零散标注 18 张，共计 93 张表格图片,涵盖多种场景、不同光照条件、不同的图像分辨率。
该数据集可以结合 表格指标评测库-TableRecognitionMetric 使用，快速评测各种表格还原算法。
关于该数据集，欢迎小伙伴贡献更多数据呦！有任何想法，可以前往 issue讨论。
如果遇到标注有误的，还请指出。
数据集支持的任务
可用于自定义数据集下的模型验证和性能评估等。
数据集的格式和结构
数据格式
数据集只有测试集，仅用于客观评估算法表现。
data
└── test
├── images
│ ├── 000cce9ca593055d4618466e823e6d7c.jpg
│ ├── 0aNtiNtRRLqEZ9y6PuShtAAAACMAAQED.jpg
│ ├──… See the full description on the dataset page: https://huggingface.co/datasets/SWHL/table_rec_test_dataset.