Overview
Compare four popular AI upscalers (Stable Diffusion, Topaz Gigapixel, Magnific AI, and Photoshop's Neural Filters) with side-by-side results to determine which tool best enhances image quality for your specific workflow needs.
Syllabus
-
- Course Introduction
-- Overview of Image Upscaling
-- Importance and Applications of AI Upscalers
-- Course Objectives
- Understanding AI Upscalers
-- What is AI Upscaling?
-- Key Metrics for Evaluating Image Quality
- Introduction to Popular AI Upscalers
-- Stable Diffusion
-- Topaz Gigapixel
-- Magnific AI
-- Photoshop's Neural Filters
- Setting Up Tools and Software Installation
-- System Requirements and Installation Guides
-- Preparing Test Images for Upscaling
- Evaluation Framework
-- Criteria for Comparison (Sharpness, Noise Reduction, Color Accuracy, etc.)
-- Defining Workflow Needs and Use Cases
- In-Depth Tool Analysis
-- Stable Diffusion: Features, Strengths, and Weaknesses
-- Topaz Gigapixel: Features, Strengths, and Weaknesses
-- Magnific AI: Features, Strengths, and Weaknesses
-- Photoshop's Neural Filters: Features, Strengths, and Weaknesses
- Practical Upscaling Sessions
-- Hands-on Exercise with Stable Diffusion
-- Hands-on Exercise with Topaz Gigapixel
-- Hands-on Exercise with Magnific AI
-- Hands-on Exercise with Photoshop's Neural Filters
- Side-by-Side Comparison and Results Analysis
-- Analyzing Output from Each Upscaler
-- Interpreting Side-by-Side Comparisons
- Conclusion and Recommendations
-- Determining the Best AI Upscaler for Different Scenarios
-- Tips for Implementing Upscaling into Your Workflow
- Final Project
-- Conduct Your Own Upscaling Comparison
-- Present Findings and Recommendations
- Course Review and Feedback
-- Summary of Key Learnings
-- Student Feedback and Q&A Session
Taught by
Tags
On-Demand
