resciencelab/opc-skills

nanobanana

Generate and edit images using Google Gemini 3 Pro Image (Nano Banana Pro).

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사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/resciencelab/opc-skills --skill nanobanana

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

Nano Banana - AI Image Generation

Generate and edit images using Google's Gemini 3 Pro Image model (gemini-3-pro-image-preview, nicknamed "Nano Banana Pro" 🍌).

Prerequisites

Required:

  • GEMINI_API_KEY - Get from Google AI Studio
  • Python 3.10+ with google-genai package

Install dependencies:

bash
pip install google-genai pillow

Quick Start

Generate an image:

bash
python3 <skill_dir>/scripts/generate.py "a cute robot mascot, pixel art style" -o robot.png

Edit an existing image:

bash
python3 <skill_dir>/scripts/generate.py "make the background blue" -i input.jpg -o output.png

Generate with specific aspect ratio:

bash
python3 <skill_dir>/scripts/generate.py "cinematic landscape" --ratio 21:9 -o landscape.png

Generate high-resolution 4K image:

bash
python3 <skill_dir>/scripts/generate.py "professional product photo" --size 4K -o product.png

Script Reference

scripts/generate.py

Main image generation script.

Usage: generate.py [OPTIONS] PROMPT

Arguments:
  PROMPT              Text prompt for image generation

Options:
  -o, --output PATH   Output file path (default: auto-generated)
  -i, --input PATH    Input image for editing (optional)
  -r, --ratio RATIO   Aspect ratio (1:1, 16:9, 9:16, 21:9, etc.)
  -s, --size SIZE     Image size: 2K or 4K (default: standard)
  --search            Enable Google Search grounding for accuracy
  -v, --verbose       Show detailed output

Supported aspect ratios:

  • 1:1 - Square (default)
  • 2:3, 3:2 - Portrait/Landscape
  • 3:4, 4:3 - Standard
  • 4:5, 5:4 - Photo
  • 9:16, 16:9 - Widescreen
  • 21:9 - Ultra-wide/Cinematic

scripts/batch_generate.py

Generate multiple images with sequential naming.

Usage: batch_generate.py [OPTIONS] PROMPT

Arguments:
  PROMPT              Text prompt for image generation

Options:
  -n, --count N       Number of images to generate (default: 10)
  -d, --dir PATH      Output directory
  -p, --prefix STR    Filename prefix (default: "image")
  -r, --ratio RATIO   Aspect ratio
  -s, --size SIZE     Image size (2K/4K)
  --delay SECONDS     Delay between generations (default: 3)

Example:

bash
python3 <skill_dir>/scripts/batch_generate.py "pixel art logo" -n 20 -d ./logos -p logo

Python API

You can also use the module directly:

python
from generate import generate_image, edit_image

# Generate image
result = generate_image(
    prompt="a futuristic city at night",
    output_path="city.png",
    aspect_ratio="16:9",
    image_size="4K"
)

# Edit existing image
result = edit_image(
    prompt="add flying cars to the sky",
    input_path="city.png",
    output_path="city_edited.png"
)

Environment Variables

VariableDescriptionDefault
GEMINI_API_KEYGoogle Gemini API keyRequired
IMAGE_OUTPUT_DIRDefault output directory./nanobanana-images

Features

Text-to-Image Generation

Create images from text descriptions. The model excels at:

  • Photorealistic images
  • Artistic styles (pixel art, illustration, etc.)
  • Product photography
  • Landscapes and scenes

Image Editing

Transform existing images with natural language:

  • Style transfer
  • Object addition/removal
  • Background changes
  • Color adjustments

High-Resolution Output

  • Standard: Fast generation, good quality
  • 2K: Enhanced detail (2048px)
  • 4K: Maximum quality (3840px), best for text rendering

Google Search Grounding

Enable --search for factually accurate images involving:

  • Real people, places, landmarks
  • Current events
  • Specific products or brands

Best Practices

Prompt Writing

Good prompts include:

  • Subject description
  • Style/aesthetic
  • Lighting and mood
  • Composition details
  • Color palette

Example:

"A cozy coffee shop interior, warm lighting, vintage aesthetic, 
wooden furniture, plants on shelves, morning sunlight through windows, 
soft focus background, 35mm film photography style"

Batch Generation Tips

  1. Generate 10-20 variations to explore options
  2. Use consistent prompts for style coherence
  3. Add 3-5 second delays to avoid rate limits
  4. Review results and iterate on best candidates

Rate Limits

  • Gemini API has usage quotas
  • Add delays between batch generations
  • Check your quota at Google AI Studio

Troubleshooting

"API key not found"

  • Set GEMINI_API_KEY environment variable
  • Or pass via --api-key option

"No image in response"

  • Prompt may have triggered safety filters
  • Try rephrasing to avoid sensitive content

"Rate limit exceeded"

  • Wait a few seconds and retry
  • Reduce batch size or add longer delays

References

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