191 lines
6.0 KiB
Markdown
191 lines
6.0 KiB
Markdown
---
|
|
name: gemini-imagegen
|
|
description: Generate and edit images using the Gemini API (Nano Banana). Use this skill when creating images from text prompts, editing existing images, applying style transfers, generating logos with text, creating stickers, product mockups, or any image generation/manipulation task. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images.
|
|
---
|
|
|
|
# Gemini Image Generation (Nano Banana)
|
|
|
|
Generate and edit images using Google's Gemini API. The environment variable `GEMINI_API_KEY` must be set.
|
|
|
|
## Available Models
|
|
|
|
| Model | Alias | Resolution | Best For |
|
|
|-------|-------|------------|----------|
|
|
| `gemini-2.5-flash-image` | Nano Banana | 1024px | Speed, high-volume tasks |
|
|
| `gemini-3-pro-image-preview` | Nano Banana Pro | Up to 4K | Professional assets, complex instructions, text rendering |
|
|
|
|
## Quick Start Scripts
|
|
|
|
### Text-to-Image
|
|
```bash
|
|
python scripts/generate_image.py "A cat wearing a wizard hat" output.png
|
|
```
|
|
|
|
### Edit Existing Image
|
|
```bash
|
|
python scripts/edit_image.py input.png "Add a rainbow in the background" output.png
|
|
```
|
|
|
|
### Multi-Turn Chat (Iterative Refinement)
|
|
```bash
|
|
python scripts/multi_turn_chat.py
|
|
```
|
|
|
|
## Core API Pattern
|
|
|
|
All image generation uses the `generateContent` endpoint with `responseModalities: ["TEXT", "IMAGE"]`:
|
|
|
|
```python
|
|
import os
|
|
import base64
|
|
from google import genai
|
|
|
|
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
|
|
|
response = client.models.generate_content(
|
|
model="gemini-2.5-flash-image",
|
|
contents=["Your prompt here"],
|
|
)
|
|
|
|
for part in response.parts:
|
|
if part.text:
|
|
print(part.text)
|
|
elif part.inline_data:
|
|
image = part.as_image()
|
|
image.save("output.png")
|
|
```
|
|
|
|
## Image Configuration Options
|
|
|
|
Control output with `image_config`:
|
|
|
|
```python
|
|
from google.genai import types
|
|
|
|
response = client.models.generate_content(
|
|
model="gemini-3-pro-image-preview",
|
|
contents=[prompt],
|
|
config=types.GenerateContentConfig(
|
|
response_modalities=['TEXT', 'IMAGE'],
|
|
image_config=types.ImageConfig(
|
|
aspect_ratio="16:9", # 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
|
|
image_size="2K" # 1K, 2K, 4K (Pro only for 4K)
|
|
),
|
|
)
|
|
)
|
|
```
|
|
|
|
## Editing Images
|
|
|
|
Pass existing images with text prompts:
|
|
|
|
```python
|
|
from PIL import Image
|
|
|
|
img = Image.open("input.png")
|
|
response = client.models.generate_content(
|
|
model="gemini-2.5-flash-image",
|
|
contents=["Add a sunset to this scene", img],
|
|
)
|
|
```
|
|
|
|
## Multi-Turn Refinement
|
|
|
|
Use chat for iterative editing:
|
|
|
|
```python
|
|
from google.genai import types
|
|
|
|
chat = client.chats.create(
|
|
model="gemini-2.5-flash-image",
|
|
config=types.GenerateContentConfig(response_modalities=['TEXT', 'IMAGE'])
|
|
)
|
|
|
|
response = chat.send_message("Create a logo for 'Acme Corp'")
|
|
# Save first image...
|
|
|
|
response = chat.send_message("Make the text bolder and add a blue gradient")
|
|
# Save refined image...
|
|
```
|
|
|
|
## Prompting Best Practices
|
|
|
|
### Photorealistic Scenes
|
|
Include camera details: lens type, lighting, angle, mood.
|
|
> "A photorealistic close-up portrait, 85mm lens, soft golden hour light, shallow depth of field"
|
|
|
|
### Stylized Art
|
|
Specify style explicitly:
|
|
> "A kawaii-style sticker of a happy red panda, bold outlines, cel-shading, white background"
|
|
|
|
### Text in Images
|
|
Be explicit about font style and placement. Use `gemini-3-pro-image-preview` for best results:
|
|
> "Create a logo with text 'Daily Grind' in clean sans-serif, black and white, coffee bean motif"
|
|
|
|
### Product Mockups
|
|
Describe lighting setup and surface:
|
|
> "Studio-lit product photo on polished concrete, three-point softbox setup, 45-degree angle"
|
|
|
|
### Landing Pages
|
|
Specify layout structure, color scheme, and target audience:
|
|
> "Modern landing page hero section, gradient background from deep purple to blue, centered headline with CTA button, clean minimalist design, SaaS product"
|
|
|
|
> "Landing page for fitness app, energetic layout with workout photos, bright orange and black color scheme, mobile-first design, prominent download buttons"
|
|
|
|
### Website Design Ideas
|
|
Describe overall aesthetic, navigation style, and content hierarchy:
|
|
> "E-commerce homepage wireframe, grid layout for products, sticky navigation bar, warm earth tones, plenty of whitespace, professional photography style"
|
|
|
|
> "Portfolio website for photographer, full-screen image galleries, dark mode interface, elegant serif typography, minimal UI elements to highlight work"
|
|
|
|
> "Tech startup homepage, glassmorphism design trend, floating cards, neon accent colors on dark background, modern illustrations, hero section with product demo"
|
|
|
|
## Advanced Features (Pro Model Only)
|
|
|
|
### Google Search Grounding
|
|
Generate images based on real-time data:
|
|
|
|
```python
|
|
response = client.models.generate_content(
|
|
model="gemini-3-pro-image-preview",
|
|
contents=["Visualize today's weather in Tokyo as an infographic"],
|
|
config=types.GenerateContentConfig(
|
|
response_modalities=['TEXT', 'IMAGE'],
|
|
tools=[{"google_search": {}}]
|
|
)
|
|
)
|
|
```
|
|
|
|
### Multiple Reference Images (Up to 14)
|
|
Combine elements from multiple sources:
|
|
|
|
```python
|
|
response = client.models.generate_content(
|
|
model="gemini-3-pro-image-preview",
|
|
contents=[
|
|
"Create a group photo of these people in an office",
|
|
Image.open("person1.png"),
|
|
Image.open("person2.png"),
|
|
Image.open("person3.png"),
|
|
],
|
|
)
|
|
```
|
|
|
|
## REST API (curl)
|
|
|
|
```bash
|
|
curl -s -X POST \
|
|
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
|
|
-H "x-goog-api-key: $GEMINI_API_KEY" \
|
|
-H "Content-Type: application/json" \
|
|
-d '{
|
|
"contents": [{"parts": [{"text": "A serene mountain landscape"}]}]
|
|
}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 --decode > output.png
|
|
```
|
|
|
|
## Notes
|
|
|
|
- All generated images include SynthID watermarks
|
|
- Image-only mode (`responseModalities: ["IMAGE"]`) won't work with Google Search grounding
|
|
- For editing, describe changes conversationally—the model understands semantic masking
|