FOCAL v0.1.0

A AI toolkit for fiber-cleave quality classification using Convolutional Neural Networks (CNN) and tension prediction using a Multi-Layer Perceptron (MLP) or XGBoost Regression Model

Contents

• Getting Started
  • Prerequisites
  • Step 1: Clone and Install
  • Step 2: Prepare Your Data
  • Step 3: Create a Minimal Configuration
  • Step 4: Run the Training
  • Step 5: Track Your Run with MLflow
  • Step 6: What’s Next?
  • Troubleshooting
• Installation
  • Requirements
  • Install from Source
  • Verify the Installation
  • Dependencies
• Configuration Reference
  • Example Configuration
  • Common Parameters
  • Mode-Specific Parameters
• Step-by-Step Guide
  • Step 1: Train CNN
  • Step 2: CNN Hyperparameter Search
  • Step 3: Train CNN (With Optimal Parameters)
  • Step 4: Train MLP or XGBoost Regression Model
  • Step 5: MLP Hyperparameter Search
  • Step 6: Train MLP Model (With Optimal Hyperparameters)
  • Step 7: Prediction Testing for CNN Model
  • Step 8: Prediction Testing for MLP/XGBoost Models
  • Step 9 (Optional): Train Reinforcement Learning (RL) Agent
  • Step 10 (Optional): Test Reinforcement Learning (RL) Agent
• API Reference
  • focal package

Indices and tables

• Index

• Module Index

• Search Page