datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
lgg-mri-segmentation-research
LGG Brain MRI Segmentation with Genomic Clusters
This repository provides a Patient-Centric version of the Lower-Grade Glioma (LGG) Segmentation dataset. While other versions of this data exist, they often treat slices as independent images. This version preserves the 3D patient volume and integrates all genomic/clinical labels directly into a multimodal-ready format.
🌟 Why This Version?
Developed for Multimodal AI Research, this dataset addresses several limitations… See the full description on the dataset page: https://huggingface.co/datasets/Ehsan-rmz/lgg-mri-segmentation-research.AVM_Segmentation_train
Dataset Card for AVM (Around View Monitoring) Semantic Segmentation Dataset
This repository provides a FiftyOne-compatible version of the AVM semantic segmentation dataset for autonomous parking systems, with enhanced metadata and visualization capabilities.
This is a FiftyOne dataset with 6763 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/AVM_Segmentation_train.SDD-Seg_Structural_Damage_Dataset_for_Segmentation
Struct-Damage-Seg-V1 (Structural Damage Segmentation Dataset)
📌 소개 (Introduction)
이 데이터셋은 토목 구조물(교량, 터널, 옹벽 등)의 손상 탐지(Damage Detection)와 구조물 부재 분류(Structural Component Classification)를 동시에 수행하기 위해 구축된 멀티태스크 데이터셋입니다.
AI Hub의 '시설물 균열 탐지 데이터' 등을 기반으로 재가공되었으며, ConvNeXt V2 등의 최신 모델 학습에 최적화된 14채널 세그멘테이션 마스크를 포함하고 있습니다.
📂 데이터셋 구조 (Structure)
데이터셋은 원본 이미지, 전처리된 마스크, 그리고 메타데이터가 담긴 CSV 파일로 구성됩니다.
images/: 원본 촬영 이미지 (JPG)
masks/: 전처리된 마스크 이미지 (PNG, Indexed Color)… See the full description on the dataset page: https://huggingface.co/datasets/onlywonhand/SDD-Seg_Structural_Damage_Dataset_for_Segmentation.lgg-mri-segmentation-research
LGG Brain MRI Segmentation with Genomic Clusters
This repository provides a Patient-Centric version of the Lower-Grade Glioma (LGG) Segmentation dataset. While other versions of this data exist, they often treat slices as independent images. This version preserves the 3D patient volume and integrates all genomic/clinical labels directly into a multimodal-ready format.
🌟 Why This Version?
Developed for Multimodal AI Research, this dataset addresses several limitations… See the full description on the dataset page: https://huggingface.co/datasets/vpasx/lgg-mri-segmentation-research.standford_cars_masks
Stanford Cars with SAM3 Segmentation Masks
This dataset was created using segmentationAPI.com
A version of the Stanford Cars dataset
augmented with per-image segmentation masks generated by SAM3 (Segment Anything Model 3).
Schema
Column
Type
Description
image
Image
Original car photograph (JPEG)
label
int
Class label (0–195, 196 car models)
split
string
train or test
mask
Image
Binary segmentation mask (grayscale PNG)
bbox
list[int]
Bounding box [x1, y1… See the full description on the dataset page: https://huggingface.co/datasets/segmentationAPIs/standford_cars_masks.plantations_segmentationThe images consist of aerial photography of agricultural plantations with crops
such as cabbage and zucchini. The dataset addresses agricultural tasks such as
plant detection and counting, health assessment, and irrigation planning.
The dataset consists of plantations' photographs with object and class
segmentation of cabbage.hair-detection-and-segmentationThe dataset consists of images of parking spaces along with corresponding bounding box
masks. In order to facilitate object detection and localization, every parking space in
the images is annotated with a bounding box mask.
The bounding box mask outlines the boundary of the parking space, marking its position
and shape within the image. This allows for accurate identification and extraction of
individual parking spaces. Each parking spot is also labeled in accordance to its
occupancy: free, not free or partially free.
This dataset can be leveraged for a range of applications such as parking lot
management, autonomous vehicle navigation, smart city implementations, and traffic
analysis.hair-loss-segmentation-dataset
Hair Loss Segmentation Dataset - 1 080 images
The dataset comprises 1,080 images of 540 women with alopecia, featuring top-view scalp images paired with segmentation masks. Each image is annotated with precise segmentation masks, enabling analysis of hair follicles, hair density, and baldness patterns. — Get the data
Dataset characteristics:
Characteristic
Data
Description
Photos of women with varying degrees of hair loss for segmentation tasks
Data… See the full description on the dataset page: https://huggingface.co/datasets/ud-medical/hair-loss-segmentation-dataset.fruitseg30_segmentation
FruitSeg30 Segmentation
A dataset for semantic segmentation of common types of fruit in a lab environment. The dataset contains 1,969 images with pixel-level mask annotations.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{shamrat2024fruitseg30_segmentation,
title={FruitSeg30\_Segmentation dataset \& mask annotations: A novel dataset for diverse fruit segmentation and classification}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/fruitseg30_segmentation.