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DanielCerda/pid-object-detection

Dataset Labels ['ball-valve', 'butterfly-valve', 'centrifugal-pump', 'check-valve', 'gate-valve'] Number of Images {'valid': 12, 'test': 12, 'train': 128} How to Use Install datasets: pip install datasets Load the dataset: from datasets import load_dataset ds = load_dataset("DanielCerda/pid-object-detection", name="full") example = ds['train'][0] Roboflow Dataset Page… See the full description on the dataset page: https://huggingface.co/datasets/DanielCerda/pid-object-detection.

sourceHugging Faceupdated 3y agoView on Hugging Face
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Dataset Card

<div align="center"> <img width="640" alt="DanielCerda/pid-object-detection" src="https://huggingface.co/datasets/DanielCerda/pid-object-detection/resolve/main/thumbnail.jpg"> </div>

Dataset Labels

['ball-valve', 'butterfly-valve', 'centrifugal-pump', 'check-valve', 'gate-valve']

Number of Images

json
{'valid': 12, 'test': 12, 'train': 128}

How to Use

bash
pip install datasets
  • —Load the dataset:
python
from datasets import load_dataset

ds = load_dataset("DanielCerda/pid-object-detection", name="full")
example = ds['train'][0]

Roboflow Dataset Page

https://universe.roboflow.com/pid-smart-reader/pid_dataset/dataset/2

Citation

@misc{ pid_dataset_dataset,
    title = { pid_dataset Dataset },
    type = { Open Source Dataset },
    author = { PID Smart Reader },
    howpublished = { \\url{ https://universe.roboflow.com/pid-smart-reader/pid_dataset } },
    url = { https://universe.roboflow.com/pid-smart-reader/pid_dataset },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { feb },
    note = { visited on 2023-10-28 },
}

License

CC BY 4.0

Dataset Summary

This dataset was exported via roboflow.com on February 10, 2023 at 3:14 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 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 152 images. Piping-elements are annotated in COCO format.

The following pre-processing was applied to each image:

No image augmentation techniques were applied.