Generating Consistent Imagery with Gemini | Towards Data Science

image-generationgeminiconsistencygenerative-ai

Abstraction: Pipeline for consistent multi-image character storytelling using Gemini 2.5 Flash Image

Key points:

Uses Gemini 2.5 Flash Image ("Nano Banana", model ID gemini-2.5-flash-image) to generate a consistent series of images from a single reference character extracted from an archive
Workflow: extract character → generate character sheet (front/back views) → use character sheet + previous scene as inputs for each successive scene, maintaining visual consistency
Supports 10 aspect ratios (1:1 through 21:9); 16:9 generates 1344×768 px; aspect ratio inferred from last input image if unspecified
Key prompt technique: label input images explicitly ("Image 1: Robot character sheet. Image 2: Previous scene.") to prevent model confusing multiple subjects
Scene composition described in either descriptive or imperative style; unspecified details invite creative variation; explicit removals needed (e.g., "Remove the ice axes") to prevent carryover
Asset pipeline can be modeled as a directed graph (using networkx); generation process is 10x–100x faster than prior approaches

Connections: Google · Gemini · Generative AI · Multimodal AI