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image_id
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int32
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keremberke/construction-safety-object-detection

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

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.

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