datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ITLP-Campus-Outdoor🌳 ITLP Campus Outdoor is a multimodal dataset for Place Recognition research in diverse university campus environments. Captured by a mobile robot with front and back RGB cameras and a 3D LiDAR, it covers 3.6 km of outdoor paths across different seasons (winter and spring) and times of day (day, night, twilight). The dataset includes synchronized LiDAR point clouds, RGB images, semantic segmentation masks, and natural language scene descriptions for many of the frames. Semantic masks and text… See the full description on the dataset page: https://huggingface.co/datasets/OPR-Project/ITLP-Campus-Outdoor.outdoor-garbage
Outdoor Garbage - Smart Cities Dataset
Dataset comprises 5,000+ images of trash cans captured in various outdoor environments at different times of day and under diverse weather conditions. This extensive collection is designed for research in waste classification and detection methods, researchers can advance their capabilities in deep learning and machine learning applications, specifically in the areas of image recognition and instance segmentation.
By utilizing this dataset… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/outdoor-garbage.outdoor-depthThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"observation.images.depth": {
"dtype": "image",
"shape": [
720,
1280,
1
],
"names": [
"height",
"width",
"channels"
],
"info": {
"is_depth_map":… See the full description on the dataset page: https://huggingface.co/datasets/lerobot/outdoor-depth.bb_outdoor_1mit-indoor-outdooroutdoor-door-handle-push-pull-training-set-next-pack-1c340bea-fea6c091
Door Handle Detection & Push/Pull Direction — Training Pack
Training dataset to teach a robot to locate door handles and infer whether each door must be pushed or pulled to open. Renders staged in home and office environments (office, home entrance, break area) that frame doors with various handle types. Outputs RGB with metric depth and world-space normals for contact geometry, per-frame annotations (bounding boxes, camera pose), authored lighting, at 1024×1024. Targets object… See the full description on the dataset page: https://huggingface.co/datasets/physicl-community/outdoor-door-handle-push-pull-training-set-next-pack-1c340bea-fea6c091.coco-outdoor-intention
COCO Outdoor Intention Dataset
Outdoor/street scene images with human intention annotations for object interaction.
Dataset Description
This dataset is derived from COCO 2017, focusing on 27 outdoor object categories (vehicles, street furniture, sports equipment, etc.).
Each sample contains an outdoor scene image, a target object, and 3 GPT-generated plausible human intentions for interacting with that object.
Splits
Split
Images/Queries
Source… See the full description on the dataset page: https://huggingface.co/datasets/Nanase1234/coco-outdoor-intention.Amazon_Sports_and_Outdoors_2014
Amazon Sports & Outdoors Dataset
Directory Structure
metadata: Contains product information.
reviews: Contains user reviews about the products.
filtered:
e5-base-v2_embeddings.jsonl: Contains "asin" and "embeddings" created with e5-base-v2.
metadata.jsonl: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
reviews.jsonl: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include… See the full description on the dataset page: https://huggingface.co/datasets/milistu/Amazon_Sports_and_Outdoors_2014.165-People-CCTV-Re-ID-Data-in-Outdoor-Night-Scenes
Description
165명 규모의 실외 야간 CCTV Re-ID 데이터셋으로, 실제 실외 야간 모니터링 환경에서 수집된 데이터를 포함합니다. 데이터는 남성과 여성을 모두 포함하며, 아동부터 중년까지 다양한 연령대로 구성되어 있고 청년층을 중심으로 분포합니다. 데이터 모달리티는 RGB와 IR의 2가지 모달리티를 지원합니다.
어노테이션은 사람 신체의 직사각형 바운딩 박스와 15종의 인체 속성 정보를 포함합니다. 본 데이터셋은 Re-ID(Person Re-Identification) 등 다양한 컴퓨터 비전 모델의 학습 및 평가에 활용할 수 있습니다.
자세한 내용은 아래 링크를 참고해 주세요: https://ko.nexdata.ai/datasets/computervision/1811?source=hf.kr
Data size
165명, 인당 32장의 이미지에 대해 어노테이션 수행
Population… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata-kr/165-People-CCTV-Re-ID-Data-in-Outdoor-Night-Scenes.bb_outdoor_3_liftpolyhaven_outdoornature-outdoor
Dataset Card for "nature-outdoor"
More Information needed
FireDetectionDataset-flame-outdoor-small-flame-vn
Fire VN YOLO11-Seg v1
Fire VN YOLO11-Seg v1 is a prepared fire and smoke segmentation dataset focused
on Vietnamese visual contexts. It is intended for training and evaluating
YOLO11 segmentation models for early fire/smoke detection in scenes such as
urban alleys, residential areas, distant fire/smoke events, hard negative
visual distractors, and normal ambient scenes.
This dataset package is distributed as a ready-to-train YOLO segmentation zip:
fire_vn_yolo11seg_v1.zip… See the full description on the dataset page: https://huggingface.co/datasets/baizhanquan/FireDetectionDataset-flame-outdoor-small-flame-vn.XMRec_metadata_fr_Sports_and_Outdoors
Description
Cleaned version of the Office Products subset (metadata folder) of XMRec dataset.In particular, we have made the images available as PILs.
Possible use cases are :
text classification, using the categories column as a label
product recommendation using the related column
hybrid text/image search (cf. this Jina.ai blog post)
Original paper citation
@inproceedings{bonab2021crossmarket,
author = {Bonab, Hamed and Aliannejadi, Mohammad and Vardasbi, Ali… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/XMRec_metadata_fr_Sports_and_Outdoors.outdoorbb_outdoor_0dataset_outdoor