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Power Pole Equipment Detection

This model generates annotated images to view and download as well as a spreadsheet that lists the equipment detected, the model’s confidence level for each detection, the total number of equipment found, and more.

40 credits (with a subscription)

80 credits (without a subscription)

Version 1.0
Free Trial available!
PowerPoleEquipmentVision
Power Pole Equipment Detection
Powerful Computer Vision
This machine learning model uses object detection to detect and classify equipment installed on power poles.
Use Case
Ideal for integration with a construction site camera for advanced analytics, this model produces results that can help optimize safety training and respond to safety audits.
Fast Analysis
The model is currently trained to detect the following equipment:
  • Animal Guards
  • Arrestors
  • Bracket Poles
  • Crossarms, including:
    • Crossarm Brackets
    • Crossarm Double Wood
    • Crossarm Fiberglass
    • Crossarm Steels
  • Fuses, including:
    • Fuse Loadbreaks
    • Fuse Tripsavers
  • Insulators, including:
    • Bell Insulators
    • Pin Insulators
    • Polymer Insulators
    • Porcelain Insulators
  • Lights, including:
    • LED Lights
    • Light Floods
    • LV Risers
  • Overhead Transformers (Oh Tx)
  • Spools

Required Inputs

  • PNG, JPG, or JPEG files

Note: This model is trained on ground view imagery, looking up at an approximately 45 degree angle.

Expected Outputs

  • Annotated images
  • A summary report in XLSX format

The Power Pole Equipment Detection model analyzes utility pole images, classifying the equipment detected on the pole. Model results are an excellent source for asset inventory and training purposes.

Note: Current mAP (Mean Average Precision) score is 63%. Results will continue to be refined as the model is trained on more data.