lipi17/building-cracks

Dataset Labels

['crack']

Number of Images

{'valid': 433, 'test': 211, 'train': 1490}

How to Use

• Install datasets:

pip install datasets

• Load the dataset:

from datasets import load_dataset

ds = load_dataset("lipi17/building-cracks", name="full")
example = ds['train'][0]

Roboflow Dataset Page

https://universe.roboflow.com/antonio-raimundo/crack-detection-y5kyg/dataset/2

Citation

@misc{ crack-detection-y5kyg_dataset,
    title = { Crack Detection Dataset },
    type = { Open Source Dataset },
    author = { António Raimundo },
    howpublished = { \\url{ https://universe.roboflow.com/antonio-raimundo/crack-detection-y5kyg } },
    url = { https://universe.roboflow.com/antonio-raimundo/crack-detection-y5kyg },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { feb },
    note = { visited on 2023-10-21 },
}

License

CC BY 4.0

Dataset Summary

This dataset was exported via roboflow.com on February 10, 2023 at 3:51 PM 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 and search unstructured image data
• annotate, and create datasets
• export, train, and deploy computer vision models
• use active learning to improve your dataset over time

For state of the art Computer Vision training notebooks you can use with this dataset, visit https://github.com/roboflow/notebooks

To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com

The dataset includes 2134 images. Soil are annotated in COCO format.

The following pre-processing was applied to each image:

• Auto-orientation of pixel data (with EXIF-orientation stripping)
• Resize to 640x640 (Stretch)

No image augmentation techniques were applied.