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STN-PLAD Dataset
Load the STN-PLAD dataset in Python with one line of code in seconds and plug it in TensorFlow and PyTorch with Activeloop Hub.
Visualization of STN-PLAD Dataset on the Activeloop Platform

STN-PLAD Dataset

What is STN-PLAD Dataset?

This STN-PLAD (STN Power Line Assets Dataset) dataset was generated to aid power line companies in detecting high voltage power line towers in order to avoid putting workers at risk. Dataset contains 5 different annotated object classes such as Stockbridge damper, spacer, transmission tower, tower plate, and insulator. Each object class has on avergae of 18.1 annotated instances in total images of 133 of power lines. The images were taken in various angles, resolutions, backgrounds, and illumination. All the images were taken through a hi-res UAV. This dataset can make use of popular deep object detection methods.

Downloading STN-PLAD Dataset in Python

Instead of downloading the STN-PLAD in Python, you can effortlessly load it in Python via our open-source package Hub with just one line of code.

Load STN-PLAD Dataset Subset in Python

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import hub
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ds = hub.load('hub://activeloop/stn-plad')
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STN-PLAD Dataset Structure

Data Fields

  • images: tensor containing the image
  • images_meta: contains meta information of images
  • boxes: group of tensors holding boxes information of the categories
  • categories: tensor containing categories of Power Line Assets
  • super_categories: tensor containing super category of the Power Line Assets
  • areas: tensor holding the information of area of the bbox
  • iscrowds: bool value containing information about whether a certain image should be allowed for training
  • date_captured: date at which the images were collected
  • file_name: contains name of the image
  • height: contains height of the image
  • width: contains width of the image

How to use STN-PLAD Dataset with PyTorch and TensorFlow in Python

Train a model on STN-PLAD dataset with PyTorch in Python

Let's use Hub's built-in PyTorch one-line dataloader to connect the data to the compute:
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dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
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Train a model on STN-PLAD dataset with TensorFlow in Python

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dataloader = ds.tensorflow()
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Additional Information about STN-PLAD Dataset

STN-PLAD Dataset Description

STN-PLAD Dataset Licensing Information

Creative Commons CCO 1.0

STN-PLAD Dataset Citation Information

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@inproceedings{vieira2021stn,
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title={STN PLAD: A Dataset for Multi-Size Power Line Assets Detection in High-Resolution UAV Images},
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author={Vieira-e-Silva, Andr{\'e} Luiz Buarque and de Castro Felix, Heitor and de Menezes Chaves, Thiago and Sim{\~o}es, Francisco Paulo Magalh{\~a}es and Teichrieb, Veronica and dos Santos, Michel Mozinho and da Cunha Santiago, Hemir and Sgotti, Virginia Ad{\'e}lia Cordeiro and Neto, Henrique Baptista Duffles Teixeira Lott},
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booktitle={2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)},
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pages={215--222},
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year={2021},
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organization={IEEE}
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}
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