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.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.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.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.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/lmr-123/ROI-1555_Rebar_Detection_and_Instance_Segmentation_Dataset.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
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.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.lions-instance-segmentation
Dataset Card for "lions-instance-segmentation"
More Information needed
coco-instance-segmentation-toy-datasetInstanceSegmentationcvat-instance-segmentation-toy-datasettrichomes_moment_lens_instance_segmentation
Dataset Card for "trichomes_moment_lens_instance_segmentation"
More Information needed
labelme-instance-segmentation-toy-datasetEgg-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.