keremberke/yolov5n-construction-safety
Object Detection
•
Updated
•
666
•
5
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End of preview. Expand
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Dataset Labels
['barricade', 'dumpster', 'excavators', 'gloves', 'hardhat', 'mask', 'no-hardhat', 'no-mask', 'no-safety vest', 'person', 'safety net', 'safety shoes', 'safety vest', 'dump truck', 'mini-van', 'truck', 'wheel loader']
Number of Images
{'train': 307, 'valid': 57, 'test': 34}
How to Use
- Install datasets:
pip install datasets
- Load the dataset:
from datasets import load_dataset
ds = load_dataset("keremberke/construction-safety-object-detection", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1
Citation
@misc{ construction-site-safety_dataset,
title = { Construction Site Safety Dataset },
type = { Open Source Dataset },
author = { Roboflow Universe Projects },
howpublished = { \\url{ https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety } },
url = { https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jan },
note = { visited on 2023-01-26 },
}
License
CC BY 4.0
Dataset Summary
This dataset was exported via roboflow.com on December 29, 2022 at 11:22 AM GMT
Roboflow is an end-to-end computer vision platform that helps you
- collaborate with your team on computer vision projects
- collect & organize images
- understand unstructured image data
- annotate, and create datasets
- export, train, and deploy computer vision models
- use active learning to improve your dataset over time
It includes 398 images. Construction are annotated in COCO format.
The following pre-processing was applied to each image:
- Auto-orientation of pixel data (with EXIF-orientation stripping)
No image augmentation techniques were applied.
- Downloads last month
- 51
Size of downloaded dataset files:
27.6 MB
Size of the auto-converted Parquet files:
28.1 MB
Number of rows:
407
Models trained or fine-tuned on keremberke/construction-safety-object-detection