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Introduction

This hands-on tutorial guides you through the process of creating, training, and deploying a deep learning model for a practical use case: detecting defects in manufactured products.

By following this practical tutorial, you'll learn how to:

  • Create and prepare datasets specifically for defect detection
  • Configure a model tailored to identifying product defects
  • Train and evaluate your model with real-world data
  • Deploy your trained model to a production environment

Prerequisites:

  • A VisionCloud account with appropriate permissions
  • Basic understanding of computer vision concepts
  • Sample images of products (we'll provide guidance on obtaining these)

Training Workflow The workflow we'll follow in this hands-on tutorial