sour vessel
I want to share a real-world use case from complex image generation, where correctness and structure matter more than aesthetics.
🎯 Goal
Create images with hard constraints, such as:
a single image containing exactly 8 distinct vehicles,
a storyboard-style layout (e.g. 5 cubes × 3 faces = 15 scenes), each showing a different step.
⚠️ Problem
When generating these in one pass, I repeatedly encountered:
missing or merged objects (e.g. 7 instead of 8),
repeated elements across panels,
loss of logical separation in small panels.
This happened even with numbered prompts, explicit descriptions, and consistent style constraints.
🔁 What worked in practice
Not a better prompt, but a process change:
generate single objects or scenes separately,
validate count and structure,
assemble the final layout manually or with tools.
This greatly reduced failed generations and iteration time.
🧠 Key insight
The bottleneck wasn’t creativity, but lack of planning before rendering.
Structured visuals benefit from layout-first thinking, object validation, and multi-step generation.
🌍 Context: Terraforming & real-time operation
I’m also interested in real-time, data-driven systems that recognize many objects, understand sunlight, cloud impact, shading, and spatial relations to support planning in terraforming scenarios. This requires models that truly think over images, not just render them.
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