project description

A visual pipeline that takes a user's photo and maps their likeness onto an illustrated brand character. The system keeps the original body, color palette, and graphic style completely intact while accurately capturing the user's facial features.

the problem

One-shot AI generation is too unpredictable. Trying to transfer a real photo's identity into a specific illustration style all at once usually breaks visual consistency, causes weird artifacts, or loses the likeness entirely. This makes it useless for scalable, brand-safe applications.

the architecture

The setup minimizes AI randomness by splitting the workload into controlled, isolated steps:

• prep (crop & upscale): Isolates the face and boosts resolution to capture maximum detail.

• conditional routing: Analyzes the input's gender to automatically route the process to the correct base character (male or female).

• structural alignment: Positions the input head to match the exact posture and scale of the base character.

• style translation: Converts the positioned photo into the brand's specific illustration style.

• final assembly: Composites the stylized head back onto the original body, ensuring the brand's core design remains untouched.

core takeaway

Scalability in generative AI isn't about writing the perfect prompt, it's about system design: breaking down generation into predictable stages to minimize randomness and guarantee consistent results.

further steps

Expanding the Conditional Routing logic to support diverse skin tones and body types.