datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ROI-1555_Rebar_Detection_and_Instance_Segmentation_DatasetROI-1555: Rebar Detection and Instance Segmentation Dataset
ROI-1555 for rebar object detection and instance segmentation contains 1555 rebar images and their fine-labeled bounding boxes and pixel-wise masks.
Diverse rebar specifications, layouts, application scenarios, and environmental conditions.
Usage
Here is an example to convert the annotations to MSCOCO 2017 format
python
cp -r 1260/img_label tools/data_annotated/train2017
cd tools
python labelme2coco_instance.py… See the full description on the dataset page: https://huggingface.co/datasets/tsrobcvai/ROI-1555_Rebar_Detection_and_Instance_Segmentation_Dataset.ROI-1555_Rebar_Detection_and_Instance_Segmentation_DatasetROI-1555: Rebar Detection and Instance Segmentation Dataset
ROI-1555 for rebar object detection and instance segmentation contains 1555 rebar images and their fine-labeled bounding boxes and pixel-wise masks.
Diverse rebar specifications, layouts, application scenarios, and environmental conditions.
Usage
Here is an example to convert the annotations to MSCOCO 2017 format
python
cp -r 1260/img_label tools/data_annotated/train2017
cd tools
python… See the full description on the dataset page: https://huggingface.co/datasets/archispace/ROI-1555_Rebar_Detection_and_Instance_Segmentation_Dataset.Egg-Instance-Segmentation
Egg Instance Segmentation
This is a dataset with images of eggs that can be used for egg segmentation purposes. The dataset is divided into two classes: white-egg and brown-egg. This is YOLO format dataset.
The training and validation images are in the train and val folders respectively.
The polygon annotations specifying the exact boundaries of eggs are in the related labels folders.
Goal
This dataset is collected to train a YOLO model to segment different types of eggs… See the full description on the dataset page: https://huggingface.co/datasets/industoai/Egg-Instance-Segmentation.Egg-Instance-Segmentation
Egg Instance Segmentation
This is a dataset with images of eggs that can be used for egg segmentation purposes. The dataset is divided into two classes: white-egg and brown-egg. This is YOLO format dataset.
The training and validation images are in the train and val folders respectively.
The polygon annotations specifying the exact boundaries of eggs are in the related labels folders.
Goal
This dataset is collected to train a YOLO model to segment different types of eggs… See the full description on the dataset page: https://huggingface.co/datasets/afshin-dini/Egg-Instance-Segmentation.crack-instance-segmentation
Dataset Labels
['cracks-and-spalling', 'object']
Number of Images
{'valid': 73, 'test': 37, 'train': 323}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("fcakyon/crack-instance-segmentation", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/palmdetection-1cjxw/crack_detection_experiment/dataset/5
Citation… See the full description on the dataset page: https://huggingface.co/datasets/fcakyon/crack-instance-segmentation.ROI-1555_Rebar_Detection_and_Instance_Segmentation_DatasetROI-1555: Rebar Detection and Instance Segmentation Dataset
ROI-1555 for rebar object detection and instance segmentation contains 1555 rebar images and their fine-labeled bounding boxes and pixel-wise masks.
Diverse rebar specifications, layouts, application scenarios, and environmental conditions.
Usage
Here is an example to convert the annotations to MSCOCO 2017 format
python
cp -r 1260/img_label tools/data_annotated/train2017
cd tools
python… See the full description on the dataset page: https://huggingface.co/datasets/lllbbb123/ROI-1555_Rebar_Detection_and_Instance_Segmentation_Dataset.automotive-tools-instance-segmentation-demo
🚗 Automotive Hand Tools Instance Segmentation Demo
Real-World Computer Vision Dataset
A real-world Computer Vision dataset focused on automotive workshops, hand tools, and equipment.
Dataset Overview
This dataset contains 1,076 original real-world images photographed in automotive workshops and related environments.
All images were personally captured by the dataset creator using an iPhone. The dataset contains no AI-generated or web-scraped… See the full description on the dataset page: https://huggingface.co/datasets/Katteryna/automotive-tools-instance-segmentation-demo.cabbage_instance_segmentation
Cabbage Instance Segmentation
A dataset for semantic segmentation of Cabbage Instance Segmentation. The dataset contains 458 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{yokoyama2024instance,
title={An instance segmentation dataset of cabbages over the whole growing season for UAV imagery},
author={Yokoyama, Yui and Matsui, Tsutomu and Tanaka, Takashi… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/cabbage_instance_segmentation.synth-rod-instance-segmentation
Synthetic Nuclear Fuel Rods Instance Segmentation
This repository contains images and labels (black/white and instance masks) of synthetic nuclear fuel rods.
RGBD-Instance-Segmentation
IAM: Enhancing RGB-D Instance Segmentation with New Benchmarks
For detailed statistics about our datasets, please refer to the following paper:Preprint: https://arxiv.org/abs/2501.01685
Github pages:https://github.com/AIM-SKKU/NYUDv2-IS https://github.com/AIM-SKKU/SUN-RGBD-IS https://github.com/AIM-SKKU/Box-IS
corn-leaf-instance-segmentationPrototype_Coreset-Simple_Coreset_Selection_for_Instance_Segmentation_Before_Annotationcoco-instance-segmentation-toy-datasetlions-instance-segmentation
Dataset Card for "lions-instance-segmentation"
More Information needed
KG_Instance_Segmentationlabelme-instance-segmentation-toy-datasettrichomes_moment_lens_instance_segmentation
Dataset Card for "trichomes_moment_lens_instance_segmentation"
More Information needed
cvat-instance-segmentation-toy-datasetyolo-edible-fungi-disease-recognition-instance-segmentation
食用菌病害识别实例分割数据集
本数据集为食用菌病害识别实例分割数据集,适用于智慧农业领域的实例分割任务。
适用场景
农业智能化检测与病虫害识别
实例分割模型训练与部署
计算机视觉算法研究
网盘地址
在线下载链接:https://www.data2.cn
在线获取数据集:食用菌病害识别实例分割数据集
访问 https://www.data2.cn 访问 data2.cn 获取下载链接
cmu_panoptic_dataset_instance_segmentation_mask
CMU Panoptic person instance masks (SAM 3.1 pseudo-labels)
TODO before making this repo public: confirm permission from the CMU Panoptic
Studio organisers. Until then the repo must stay gated and private. See
LICENSE_NOTICE.md.
Per-person instance segmentation masks for the CMU Panoptic Studio dataset, generated
with SAM 3.1 (facebook/sam3.1 @ daa63191845a41281374e725f4c9e51c7a824460) and aligned to the
dataset's own 3D skeletons: masks and pose share the same person id across… See the full description on the dataset page: https://huggingface.co/datasets/EpicPinkPenguin/cmu_panoptic_dataset_instance_segmentation_mask.coconut_instance_segmentationEgg-Instance-Segmentation
Egg Instance Segmentation
This is a dataset with images of eggs that can be used for egg segmentation purposes. The dataset is divided into two classes: white-egg and brown-egg. This is YOLO format dataset.
The training and validation images are in the train and val folders respectively.
The polygon annotations specifying the exact boundaries of eggs are in the related labels folders.
Goal
This dataset is collected to train a YOLO model to segment different types of eggs… See the full description on the dataset page: https://huggingface.co/datasets/ATUMUNMOON/Egg-Instance-Segmentation.ROI-1555_Rebar_Detection_and_Instance_Segmentation_DatasetROI-1555: Rebar Detection and Instance Segmentation Dataset
ROI-1555 for rebar object detection and instance segmentation contains 1555 rebar images and their fine-labeled bounding boxes and pixel-wise masks.
Diverse rebar specifications, layouts, application scenarios, and environmental conditions.
Usage
Here is an example to convert the annotations to MSCOCO 2017 format
python
cp -r 1260/img_label tools/data_annotated/train2017
cd tools
python labelme2coco_instance.py… See the full description on the dataset page: https://huggingface.co/datasets/SYliuuuuuu/ROI-1555_Rebar_Detection_and_Instance_Segmentation_Dataset.yolo-various-starfish-instance-segmentation
各类海星实例分割数据集
本数据集为各类海星实例分割数据集,适用于生态保护领域的实例分割任务。
数据集标签信息
检测类别数(nc):28
类别名称:Ampheraster_marianus, Ceramaster_patagonicus, Crossaster_papposus, Dermasterias_imbricata, Evasterias_troschelii, Henricia_aspera, Henricia_leviuscula, Henricia_pumila, Henricia_sanguinolenta, Hippasteria_phrygiana, Leptasterias_hexactis, Lophaster_furcilliger, Luidia_foliolata, Mediaster_aequalis, Orthasterias_koehleri, Patiria_miniata, Pisaster_brevispinus, Pisaster_ochraceus… See the full description on the dataset page: https://huggingface.co/datasets/ybli/yolo-various-starfish-instance-segmentation.yolo-marine-organism-instance-segmentation
海洋生物实例分割数据集
本数据集为海洋生物实例分割数据集,适用于海洋AI、生态保护领域的实例分割任务。
数据集标签信息
检测类别数(nc):15
类别名称:BLUETANG(蓝吊鱼), CLOWN FISH(小丑鱼), CRABS(螃蟹), DOLPHINE(海豚), JELLY FISH(水母), LOBSTER(龙虾), OCTOPUS(章鱼), PUFFERS, RAYS, SEAHORSES, SHARKS, STARFISH, TURTLES, URCHINS, WHALE
适用场景
BLUETANG, CLOWN FISH, CRABS等多类目标的智能检测
实例分割模型训练与部署
计算机视觉算法研究
网盘地址
在线下载链接:https://www.data2.cn
在线获取数据集:海洋生物实例分割数据集
访问 https://www.data2.cn 访问 data2.cn 获取下载链接
InstanceSegmentationyolo-single-tree-segmentation-instance-segmentation
单木分割实例分割数据集
本数据集为单木分割实例分割数据集,适用于计算机视觉领域的实例分割任务。
适用场景
实例分割模型训练与部署
计算机视觉算法研究
网盘地址
在线下载链接:https://www.data2.cn
在线获取数据集:单木分割实例分割数据集
访问 https://www.data2.cn 访问 data2.cn 获取下载链接
yolo-building-instance-segmentation
建筑物实例分割数据集
本数据集为建筑物实例分割数据集,适用于智慧交通领域的实例分割任务。
适用场景
基础设施智能巡检与病害检测
实例分割模型训练与部署
计算机视觉算法研究
网盘地址
在线下载链接:https://www.data2.cn
在线获取数据集:建筑物实例分割数据集
访问 https://www.data2.cn 访问 data2.cn 获取下载链接
Automotive_Hand_Tools_Instance_SegmentationROI-1555_Rebar_Detection_and_Instance_Segmentation_DatasetROI-1555: Rebar Detection and Instance Segmentation Dataset
ROI-1555 for rebar object detection and instance segmentation contains 1555 rebar images and their fine-labeled bounding boxes and pixel-wise masks.
Diverse rebar specifications, layouts, application scenarios, and environmental conditions.
Usage
Here is an example to convert the annotations to MSCOCO 2017 format
python
cp -r 1260/img_label tools/data_annotated/train2017
cd tools
python labelme2coco_instance.py… See the full description on the dataset page: https://huggingface.co/datasets/lmr-123/ROI-1555_Rebar_Detection_and_Instance_Segmentation_Dataset.
