Nano Banana — The Creative Professional's Guide

Timon 3 months ago

Executive Summary:

Nano-Banana (Nano Banana) marks a shift from one-shot AI art toys to intelligent creative partners, bringing context-aware edits and multi-modal fusion for serious speed-ups in professional workflows[^1][^2]
Professional use cases span packaging, virtual try-ons, architecture, and brand marketing—giving creative teams real opportunities to streamline production[^2][^1]
Accessible yet powerful: prompt-first controls meet multi-image synthesis, unlocking pro-grade results for designers and product managers without steep learning curves[^3][^1][^2]

What is Nano-Banana?

Nano-Banana is Google’s advanced AI image editing model that helps creative professionals build visuals faster and smarter. Instead of generating from nothing, it understands the context, lighting, and spatial layout of existing images to make intelligent, precise edits. Whether you’re prototyping products, preparing marketing assets, or visualizing campaigns, Nano-Banana (Nano Banana) tightens the gap between creative intent and technical output with impressive accuracy.[^1][^2][^3]

Curated Case Collection

Case #1 — Illustration to Product Figure

Source: @ZHO_ZHO_ZHO via GitHub Repository[^1][^2]

A. Case Introduction — Nano-Banana can turn a 2D artwork into a realistic product figure and stage it like a commercial shot: packaging, base, even a screen showing the Blender process. For product designers and toy makers, this compresses concept-to-prototype time.

B. Case Prompt

turn this photo into a character figure. Behind it, place a box with the character's image printed on it, and a computer showing the Blender modeling process on its screen. In front of the box, add a round plastic base with the character figure standing on it. set the scene indoors if possible

Prompt Variants:

Create figure with LED light base and premium packaging (presentation quality)
Generate limited edition figure with metallic finish base (premium positioning)

C. Case Effect — Expected results: high-quality figure rendering; packaging with brand elements; natural indoor lighting; authentic Blender interface on screen; a commercial-ready composition. Business takeaway: faster concept validation for collectibles and merch.

Case #2 — Map Arrow to Street View

Source: @tokumin via GitHub Repository[^1][^2]

A. Case Introduction — It converts aerial map hints (arrows, context) into realistic ground-level views—great for real estate previews, urban planning, and navigation.

B. Case Prompt

draw what the red arrow sees 
/ 
draw the real world view from the red circle in the direction of the arrow.

Prompt Variants:

Generate street view photo with sunny weather and clear visibility (weather control)
Create dusk street scene with warm lighting and traffic (atmosphere)

C. Case Effect — AI-generated reproduction prompt (reproducible):

Street level view of urban intersection with buildings, showing realistic perspective from aerial map reference point with directional arrow

Reproduction note: architectural details and traffic will vary. Expected results: perspective matching; believable architecture; signs/vehicles/pedestrians; natural lighting and depth; reasonable geographic alignment. Business takeaway: instant location previews and better route visualization.

Case #3 — AR Information Overlay

Source: @bilawalsidhu via GitHub Repository[^1][^2]

A. Case Introduction — Identify points of interest and layer clean AR-style annotations onto photos—useful for tourism, education, and smart-city content.

B. Case Prompt

you are a location-based AR experience generator. highlight [point of interest] in this image and annotate relevant information about it.

Prompt Variants:

Add tourist information with multilingual labels and ratings (tourism)
Create business directory overlay with hours and contact info (commerce)

C. Case Effect — AI-generated reproduction prompt (reproducible):

Urban street scene with AR-style information overlays highlighting buildings and landmarks with text annotations and interface elements

Reproduction note: text and UI styling may differ. Expected results: clean UI; unobtrusive callouts; consistent typography/colors; realistic integration; modern AR look. Business takeaway: engaging, low-cost location-based content without heavy AR dev.

Case #4 — Isometric 3D Building Extraction

Source: @Zieeett via GitHub Repository[^1][^2]

A. Case Introduction — From real building photos to clean isometric 3D assets for games, archviz, and planning—no specialized modeling required.

B. Case Prompt

Make Image Daytime and Isometric [Building Only]

Prompt Variants:

Create night version with illuminated windows and street lighting (time variation)
Generate pixel art style isometric building for game assets (style)

C. Case Effect — Expected results: precise isometric proportions; clean architectural lines; simplified but recognizable features; even lighting; archviz-grade clarity. Business takeaway: rapid isometric assets for demos and prototypes.

!AI-generated isometric 3D model of a hospital building showcasing detailed architectural design and urban context.

Case #5 — Era-Specific Portrait Transformation

Source: @AmirMushich via GitHub Repository[^1][^2]

A. Case Introduction — Send a subject through time while keeping facial identity intact—handy for casting, education, and personalized entertainment.

B. Case Prompt

Change the characer's style to 's classical [male] style
Add [long curly] hair, 
[long mustache], 
change the background to the iconic [californian summer landscape]
Don't change the character's face

Prompt Variants:

Transform to 1920s Shanghai style with qipao and vintage setting (cultural period)
Create 1980s disco look with neon lighting and club atmosphere (era switch)

C. Case Effect — Expected results: preserved facial identity; authentic period styling; era-accurate backgrounds; natural vintage characteristics; believable time-travel effect. Business takeaway: quick period tests for entertainment and nostalgia marketing.

!AI-generated vintage-style portraits showcasing hairstyles and attire from the mid-20th century, illustrating AI transformation effects on modern photos.

Case #6 — Multi-Image Composition

Source: @MrDavids1 via GitHub Repository[^1][^2]

A. Case Introduction — Nano-Banana merges multiple references into one photo-real scene—perfect for ad visuals without complex shoots.

B. Case Prompt

A model is posing and leaning against a pink bmw. She is wearing the following items, the scene is against a light grey background. The green alien is a keychain and it's attached to the pink handbag. The model also has a pink parrot on her shoulder. There is a pug sitting next to her wearing a pink collar and gold headphones.

Prompt Variants:

Shoot at golden hour with warm atmospheric lighting (lighting)
Use fashion magazine style with professional studio setup (style)

C. Case Effect — AI-generated reproduction prompt (reproducible):

Fashion photography scene with model leaning against pink BMW, multiple colorful accessories, pets with headphones, professional lighting and composition

Reproduction note: model and prop arrangements will differ. Expected results: seamless integration; consistent light/shadows; cohesive pink palette; sharp, pro exposure; natural interactions. Business takeaway: complex shots without costly locations or large crews.

Case #7 — Intelligent Photo Enhancement

Source: @op7418 via GitHub Repository[^1][^2]

A. Case Introduction — Not a generic filter: Nano-Banana analyzes image content to enhance contrast, color, and composition while keeping a natural look.

B. Case Prompt

This photo is very boring and plain. Enhance it! Increase the contrast, boost the colors, and improve the lighting to make it richer,You can crop and delete details that affect the composition.

Prompt Variants:

Optimize for portraits with skin softening and eye enhancement (portrait)
Enhance landscapes with dramatic sky and foreground detail (landscape)

C. Case Effect — AI-generated reproduction prompt (reproducible):

Before and after comparison showing enhanced photo with improved contrast, vibrant colors, and optimized composition

Reproduction note: source content and exact adjustments will vary. Expected results: vivid color without oversaturation; deeper contrast; smarter crop; natural feel with elevated impact; publication-ready polish. Business takeaway: pro quality without heavy post-production.

Case #8 — Sketch-Controlled Character Poses

Source: @op7418 via GitHub Repository[^1][^2]

A. Case Introduction — Hand sketches become control rigs for pose and interaction—AI handles the heavy lifting, you keep the art direction.

B. Case Prompt

Have these two characters fight using the pose from Figure 3. Add appropriate visual backgrounds and scene interactions,Generated image ratio is 16:9

Prompt Variants:

Add motion lines and effects for a comic-book vibe (effects)
Use cinematic lighting with dramatic shadows (mood)

C. Case Effect — AI-generated reproduction prompt (reproducible):

Two characters in fighting poses based on sketch reference, dramatic background with dynamic composition in 16:9 aspect ratio

Reproduction note: characters and backgrounds will differ. Expected results: pose accuracy; believable anatomy and motion; cohesive scene; correct 16:9 output; energetic composition. Business takeaway: quick prototyping for animation and games.

Case #9 — Perspective Transformation

Source: @op7418 via GitHub Repository[^1][^2]

A. Case Introduction — Convert ground photos to top-down views and mark the photographer’s position—useful for planning, security, and documentation.

B. Case Prompt

Convert the photo to a top-down view and mark the location of the photographer.

Prompt Variants:

Generate floor-plan-like view with dimension annotations (technical)
Create traffic flow analysis view with path markings (planning)

C. Case Effect — AI-generated reproduction prompt (reproducible):

Aerial top-down view of urban area with photographer position marked, accurate spatial relationships and geographic features

Reproduction note: locations and mark styles will vary. Expected results: accurate spatial transform; clear position marker; preserved landmarks; logical layout; mapping-quality visualization. Business takeaway: quick overhead analysis without aerial shoots.

Case #10 — Custom Sticker Creation

Source: @op7418 via GitHub Repository[^1][^2]

A. Case Introduction — Turn photos into sticker-ready illustrations with integrated playful text while keeping the subject recognizable—on-brand and on-trend.

B. Case Prompt

Help me turn the character into a white outline sticker similar to Figure 2. The character needs to be transformed into a web illustration style, and add a playful white outline short phrase describing Figure 1.

Prompt Variants:

Create a colorful version while keeping the cartoon look (color)
Add drop shadow for extra dimension (visual depth)

C. Case Effect — AI-generated reproduction prompt (reproducible):

Character transformed into white outline sticker design with web illustration style and integrated typography

Reproduction note: character details and text will vary. Expected results: clean white outline; simplified yet recognizable features; integrated playful type; scalable vector-like feel; modern sticker aesthetics. Business takeaway: fast custom merch and marketing visuals.

Tips & Prompt-Writing Insights

From the above cases, here are eight prompt-writing moves for Nano-Banana (Nano Banana):

Specify Subject Precisely — Name the target clearly to avoid ambiguity (see Case #8)[^1]
Define Environmental Context — State indoor/outdoor or specific backgrounds (see Case #5)[^1]
Layer Style Keywords — Combine descriptors (e.g., period + hair) for richer results (Case #5)[^1]
State Technical Requirements — Aspect ratios, isometric views, etc. (Cases #4, #8)[^2][^1]
Use Preservation Commands — “Don’t change” for must-keep elements like faces (Case #5)[^1]
Structure Multi-Step Instructions — Break complex tasks into steps (Case #1)[^1]
Reference Multi-Image Sources — Clarify relationships between images to avoid confusion[^1]
Include Enhancement Verbs — Action plus target (enhance, boost, improve) (Case #7)[^1]

Ready-to-Use Prompt Templates

# Product Visualization Template
Transform [subject/character] into [display format]. Add [packaging elements], place in [environment setting], use [photography style]

Use for: product concepts, figures, merchandise mockups

# Perspective Conversion Template
Convert image from [current viewpoint] to [target perspective], and mark [key information points]

Use for: architectural drawings, map conversions, spatial analysis

# Era Transformation Template
Change character's style to [time period]'s [gender] [style type], add [specific features], background [environment description], preserve [unchanging elements]

Use for: historical content, vintage marketing, character design

# Multi-Element Fusion Template
Create scene: [main subject] at [location], combine with [item list], environment [background description], overall style [aesthetic requirements]

Use for: advertising photography, product displays, creative compositing

# Enhancement Template
This image [problem description]. Please [improvement actions]! Specifically [technical requirements list], you may [permitted operations]

Use for: post-processing, content optimization, quality improvement

# Pose Control Template
Have [character description] use [reference figure]'s pose for [action], add [scene elements], output ratio [dimension requirements]

Use for: animation, game design, comic creation

# AR Information Template
You are [professional role]. Highlight [target objects] in image and annotate [information type]

Use for: education, navigation, smart city

# Sticker Style Template
Convert [object] to [style type] sticker, using [visual characteristics], add [text content]

Use for: brand marketing, social content, personalization

Quick Workflow & Checklist

Nano-Banana Production-Ready Image Generation Workflow:

Step 1: Asset Preparation — Gather high-resolution references (>1024px), ensure clean, watermark-free sources, and define requirements with clear success criteria

Step 2: Prompt Construction — Pick a template, fill in specifics, iterate and refine, and record winning configurations

Step 3: Generation Testing — Run initial generations, compare with expectations, isolate adjustments, A/B test variants

Step 4: Quality Control — Check detail completeness and accuracy, verify style consistency, validate commercial standards, test scalability across sizes

Step 5: Delivery Optimization — Apply final adjustments based on usage context, prepare multiple format versions for different applications, establish standardized output procedures for team consistency