🤖 IR Control Panel
Machine Learning Image Recognition System
System Status
🟢 YOLO Detector
Real-Time Object Detection Engine
- Status: Running
- Version: YOLOv8
- Function: Object Localization & Detection
- Output: Bounding Boxes + Class Labels
- Detection Mode: Real-time
🧠 ResNet Classifier
Deep Visual Feature Analyzer
- Status: Running
- Architecture: ResNet-50
- Function: Fine-Grained Classification
- Output: Class Probabilities & Embeddings
- Feature Mode: Hierarchical Visual Features
🚀 Detection + Classification Pipeline
- YOLO: Detects object location and type
- ResNet: Analyzes visual appearance
- Pipeline: Detection → Cropping → Classification
- Purpose: High-accuracy grading and inspection
🧪 ResNet Deep Feature Capability
Low-Level:Edges Lines Corners Color Gradients
Mid-Level:
Shapes Textures Patterns Object Parts
High-Level:
Object Identity Condition Analysis Structural Features Semantic Meaning
💎 System Summary
YOLO locates objects in the image, while ResNet evaluates their visual characteristics to determine class, condition, and grading. This hybrid architecture enables robust and precise image recognition suitable for inspection, monitoring, and automated decision systems.