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Infrastructure Keypoint Detection

Fine-tuned transformer for precise keypoint extraction in utility infrastructure.

TransformersPyTorchFine-tuningVLM

Overview

Fine-tuned a transformer model on custom annotations for precise keypoint extraction in utility infrastructure images. Built automated error-analysis loops to continuously improve extraction reliability.

The Problem

Utility infrastructure analysis needs pixel-precise keypoints (attachment heights, wire positions), but generic vision models don't understand domain-specific structures, and expert annotation is too expensive to throw at every failure mode.

The Approach

  1. 01Built a custom annotation pipeline to capture domain-specific keypoints with consistent quality
  2. 02Fine-tuned a transformer model on those annotations for precise keypoint extraction
  3. 03Designed automated error-analysis loops: failure cases are mined, categorized, and fed back into training, so the model improves where it actually fails
  4. 04Deployed for communication-wire detection in production infrastructure analysis

The Outcome

Fine-tunedtransformer on custom domain annotations
Self-improvingautomated error-analysis loop drives each iteration
Productioncommunication-wire detection deployment

Key Features

  • ✓Custom annotation pipeline
  • ✓Automated error analysis and correction
  • ✓Communication wire detection
  • ✓High-precision key-point extraction