谷歌nano banana官方Prompt模板

原文链接

同样适用于即梦AI。

1.写实摄影

要获得逼真的图像，请像摄影师一样思考。提及相机角度、镜头类型、光线和精细细节，将引导模型达到逼真的效果。

示例模板:

A photorealistic [shot type] of [subject]， [action or expression]， set in [environment]. The scene is illuminated by [lighting description]， creating a [mood] atmosphere. Captured with a [camera/lens details]， emphasizing [key textures and details]. The image should be in a [aspect ratio] format.
​
大意:一张写实风格的[镜头类型]，[主体]，[动作或表情]，场景设定在[环境]。画面由[光线描述]照明，营造出[情绪]氛围。使用[相机/镜头参数]拍摄，突出[关键材质与细节]。图像应为[纵横比]格式。

示例Prompt:

A photorealistic close-up portrait of an elderly Japanese ceramicist with deep， sun-etched wrinkles and a warm， knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic， sun-drenched workshop. The scene is illuminated by soft， golden hour light streaming through a window， highlighting the fine texture of the clay. Captured with an85mm portrait lens， resulting in a soft， blurred background （bokeh）. The overall mood is serene and masterful. Vertical portrait orientation.
​
大意:一张写实风格的特写人像:一位日本老陶艺家，脸上被岁月与阳光刻下的深深皱纹，露出温暖而睿智的微笑。他正仔细端详一个刚上釉的茶碗。场景位于他质朴、阳光充足的工作室。柔和的黄金时刻光线自窗外倾泻而入，凸显陶土的细腻纹理。使用85mm人像镜头拍摄，带来柔和的背景虚化（bokeh）。整体氛围宁静而老练。竖版人像构图。

生成的图片:

调用API生图示例Python代码:

from google import genai
from google.genai import types
from PIL import Image
from io import BytesIO
​
client = genai.Client()
​
# Generate an image from a text prompt
response = client.models.generate_content(
model="gemini-2.5-flash-image-preview"，
contents="A photorealistic close-up portrait of an elderly Japanese ceramicist with deep， sun-etched wrinkles and a warm， knowing smile. He is carefully inspecting a freshly glazed tea bowl. The setting is his rustic， sun-drenched workshop with pottery wheels and shelves of clay pots in the background. The scene is illuminated by soft， golden hour light streaming through a window， highlighting the fine texture of the clay and the fabric of his apron. Captured with an 85mm portrait lens， resulting in a soft， blurred background (bokeh). The overall mood is serene and masterful."，
)
​
image_parts = [
part.inline_data.data
for