Nano Banana Asset Master
Overview
This skill helps students transform text prompts into high-fidelity visual assets (custom placemark icons, logo overlays, balloon graphics, tour thumbnails, or data visualization icons) that look stunning on the Liquid Galaxy video wall. It covers the full pipeline: Generation -> Transparent Processing -> LG Integration.
Phase 1: The Perfect Generation Prompt
To get a usable LG asset, you must be specific. Nano Banana generates squares, but we need clean icons and overlays.
Prompt Template:
"Top-down view of a [Aesthetic, e.g., Modern Flat] [Object, e.g., Earthquake Pin Icon]. Feature: [Details, e.g., Concentric seismic rings, bold center dot]. Background: Solid bright neon green (#00FF00). High contrast, symmetrical, icon asset, 4k. The object must occupy the center of the frame. No checkerboard, no grid, no shadowed ground."
Why Green?
Generating with a solid neon green background allows us to use a Chroma Key algorithm (like in Hollywood movies) to remove the background, as AI models often struggle to export true transparency (Alpha channel). After processing, we get clean PNGs for KML <Icon> and <ScreenOverlay> elements.
Phase 2: Background Removal (Dart/Flutter)
Add this utility to your Flutter app to process AI-generated assets.
import 'dart:typed_data';
import 'package:image/image.dart' as img;
/// Removes bright green backgrounds from AI-generated assets.
/// Returns a PNG-encoded Uint8List with transparency.
Uint8List makeTransparent(Uint8List imageBytes) {
final image = img.decodeImage(imageBytes);
if (image == null) return imageBytes;
for (int y = 0; y < image.height; y++) {
for (int x = 0; x < image.width; x++) {
final pixel = image.getPixel(x, y);
final r = pixel.r.toInt();
final g = pixel.g.toInt();
final b = pixel.b.toInt();
// Chroma Key: Target the bright Green (#00FF00)
if (g > 100 && r < 100 && b < 100) {
image.setPixelRgba(x, y, 0, 0, 0, 0); // Set Alpha to 0
}
}
}
return Uint8List.fromList(img.encodePng(image));
}
Dependency: Add image: ^4.0.0 to pubspec.yaml.
Phase 3: Sizing & Integration for LG
Liquid Galaxy screens are high-resolution (1080×1920 portrait, tiled across 3-7 screens). Assets must be crisp.
- Icon Resolution: Generate at 512×512 minimum for placemark icons. Google Earth scales them down, but low-res icons look blurry on the video wall.
- Logo Overlays: For
<ScreenOverlay>logos, use 1024×512 or wider. These span a fraction of the slave screen. - Hosting for KML: KML
<Icon><href>needs a URL. Options:- Host on the LG rig: SCP to
/var/www/html/assets/and referencehttp://lg-master:81/assets/icon.png. - Host externally: GitHub raw URL, Firebase Storage, etc.
- Host on the LG rig: SCP to
- Test in Google Earth Pro: Always preview the asset in Google Earth desktop before sending to the rig.
Example Task: Custom Earthquake Placemark Icon
Used in earthquake visualizer apps:
- Prompt: "Top-down view of a seismic wave icon. Concentric red-orange rings radiating from a bold red center dot. Background: Solid bright neon green (#00FF00). High contrast, icon asset, 4k."
- Resolution: 512×512 PNG.
- KML Usage:
<Style><IconStyle><Icon><href>http://lg-master:81/assets/quake_icon.png</href></Icon></IconStyle></Style>
Example: Satellite Tracker Pin
- Prompt: "Top-down view of a modern satellite with solar panels extended. Metallic blue and silver tones. Background: Solid bright neon green (#00FF00). High contrast, icon asset, 4k."
- Strategy: Use as a custom placemark icon for ISS or satellite tracking apps.
Example: Custom LG Logo Overlay
- Prompt: "A sleek modern logo banner for Liquid Galaxy. Text 'LG' in futuristic font. Gradient blue-to-purple. Background: Solid bright neon green (#00FF00)."
- KML Usage:
<ScreenOverlay>on slave screen with<overlayXY>and<screenXY>positioning.
⛔ Student Interaction Checkpoints
After Asset Generation — Dimensions and Transparency
⛔ STOP and WAIT — After generating the asset, ask:
"Why did we generate at 512×512 minimum? What happens if you use a 64×64 icon on a Liquid Galaxy video wall that's 5760×1080 across 3 screens?"
Wait for the student's answer.
Background Removal — Understand the Technique
⛔ STOP and WAIT — After processing the image, ask:
"Why do we use a bright neon green (#00FF00) background instead of asking the AI to generate a transparent PNG? What is chroma keying, and where else is it used?"
This is a "predict what happens" exercise — let them reason about why AI models struggle with alpha channels.
KML Integration — Trace the Pipeline
⛔ STOP and WAIT — Ask:
"Trace the full asset pipeline: from the text prompt → generated image → processed PNG → hosted URL → KML
<Icon>element → Google Earth display. What could go wrong at each step?"
Verification Checklist
- Is the object centered in the generated image?
- Is the green background completely removed (no "halo" effect)?
- Does the asset render correctly in Google Earth Pro (desktop preview)?
- Is the resolution high enough for the Liquid Galaxy video wall (512px+ for icons)?
- Is the asset hosted at a URL accessible by the LG rig?
🔗 Skill Chain
After the asset is generated, processed, and the student understands the pipeline, automatically offer to return to initialization:
"Asset generation complete! The icon is processed and ready for KML integration. Let's continue setting up the project. Ready to go back? 🎨"
If student says "ready" → activate .agent/skills/lg-init/SKILL.md (asset generation phase complete).
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