Streamlit Guide

This project uses YOLO object detection together with a Basler industrial camera to verify the completeness of assembly kits.
It compares detected parts against a reference (master kit) and marks them as:

• ✅ Correct parts (green)
• ❌ Incorrect / Extra parts (red)
• ⚠️ Missing parts (purple)

Features

• Real-time object detection with YOLOv8
• Integration with Basler camera via pypylon
• Interactive Streamlit interface
• GPU/CPU device selection
• Visualization of missing, correct, and incorrect parts
• Structured output regions: Inventory, Master Kit, and Assembly area

Code Workflow

1. Initialize Basler camera and YOLO model
2. Capture images from camera
3. Detect objects using YOLO
4. Sort items into:
   • Inventory objects
   • Master kit objects
   • Assembly objects
5. Compare counts:
   • Mark missing parts
   • Mark extra parts
   • Mark correct parts
6. Display results in Streamlit dashboard

Flowchart

The process flow is summarized below: