datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
STRIDE-QA-Dataset
STRIDE-QA Dataset
📦 Dataset
STRIDE-QA is a large-scale visual question answering (VQA) dataset for physically grounded spatiotemporal reasoning in autonomous driving. Constructed from 100 hours of multi-sensor driving data in Tokyo, it offers 16 M QA pairs over 270 K frames with dense annotations including 3D bounding boxes, segmentation masks, and multi-object tracks.
Category
Description
Object-centric Spatial QA
Spatial relations between two… See the full description on the dataset page: https://huggingface.co/datasets/turing-motors/STRIDE-QA-Dataset.MotionMillion
🔑 Key Features
Over 2000 hours of high-quality human motion captured from web-scale human video data, covering:
Martial Arts (23.7%)
Fitness (26.4%)
Performance (17.5%)
Dance (14.9%)
Non-Human (2.9%)
Sports (2.4%)
Over 20 detailed annotations per motion, including:
Age
Body Characteristics
Movement Styles
Emotions
Environments
👨🏫 Get Started
Download the Dataset
To download the full dataset, use the following code. If you encounter any… See the full description on the dataset page: https://huggingface.co/datasets/InternRobotics/MotionMillion.Motion324RACER-Mini
RACER-Mini
RACER (Rationale-Aware Captioning of Edge-Case Driving Scenarios) is a reasoning caption dataset designed for training vision-language-action (VLA) models in autonomous driving.
This repository provides approximately 1,000 samples, as a small subset of the RACER dataset. Each sample consists of a temporal sequence of front camera images, the ego vehicle’s future trajectory, and a corresponding reasoning caption.
For details, please refer to our techblog RACER:… See the full description on the dataset page: https://huggingface.co/datasets/turing-motors/RACER-Mini.butterflies-moths-austria
Butterflies & Moths Austria
Dataset Summary
This is a repackaged version of the Austria butterflies and moths dataset in PyTorch ImageFolder format.
Note: All credit goes to the original authors.
Compared to the original release, this upload:
Converts all images to WebP
Resizes each image so that the total number of pixels < 589,824 (=768×768), preserving aspect ratio
Pre-splits the dataset into train/validation/test using a 70:20:10 split
Packs the data in an… See the full description on the dataset page: https://huggingface.co/datasets/birder-project/butterflies-moths-austria.