How to Train AI Models for Better Images & Videos

How to Train AI Models for Better Images & Videos

AI image and video generation has evolved rapidly, offering powerful creative possibilities. But without the right approach, results can feel inconsistent or unrealistic.

 

The difference isn’t just the tool it’s how you guide it.

 

At Ishikawa Solutions, we approach AI like any system:
structured input = better output.

 

Here’s a simple framework to help you generate more accurate and visually consistent results.

 

 


 

 

1. Start with a Compositional Reference

 

 

A basic png montage for reference to train the AI

 

 

Before prompting, define the structure.

A compositional reference helps AI understand:

 

  • Layout
  • Scale
  • Spacing
  • Visual hierarchy

 

This can be:

 

  • A rough sketch
  • A wireframe
  • A PNG collage
  • A basic layout mock

 

Focus on structure, not realism.

 

Think of it as a blueprint the AI fills in details, but you define the foundation.

 

 


 

 

2. Define a Style Reference

 

 

 

Once structure is clear, guide the aesthetics.

 

Style defines:

  • Mood
  • Lighting
  • Color tone
  • Visual language

 

Different tools handle this differently:

  • Midjourney → style references / codes
  • Adobe Firefly → image-based references

 

You can use platforms like Pinterest to find visual direction.

 

👉 This ensures your output isn’t random it’s intentional.

 

 


 

 

3. Prompt with Clarity (Not Noise)

 

Prompt for creating the image

 

Prompt for generating a video from the image

 

Most beginners overcomplicate prompts.

 

Avoid unnecessary words like:

  • “create”
  • “generate”
  • “add”

 

Instead:

  • Be descriptive
  • Be logical
  • Be specific

 

Use:

  • Your composition → for structure
  • Your style → for aesthetics

 

Example approach:
👉 Subject + Environment + Lighting + Mood + Style

 

The clearer your input, the better the output.

 

 


 

Applying This in Real Projects

 

AI works best when treated as a system, not magic.

 

In real-world use:

  • Start with a clear idea
  • Structure the output
  • Refine through iteration

 

At Ishikawa Solutions, we use this approach to build AI-driven workflows, visual systems, and scalable creative outputs not just one-off results.

 

Explore our AI & Automation services to see how we implement this in real business use cases.

 

 


 

 

Final Thought

 

 

Image Result

 

 

Video Result

 

 

AI doesn’t replace creativity it amplifies it.

 

But only when guided correctly.

 

The goal isn’t just to generate images or videos.
It’s to build repeatable, reliable creative systems.

 

 


 

Attribution

 

This article is inspired by insights shared by Mahesh Ravi, adapted and expanded with Ishikawa Solutions’ approach to structured problem-solving and AI workflows.

Tags:

Leave a Reply

Your email address will not be published. Required fields are marked *