
3D城市立體模型地圖
一個複雜的參數化場景圖提示,用於產生高端 3D 城市地形圖,並將宏偉的字體融入建築之中。
這是一個其他靈感的GPT Image 2範例。請使用下方可直接使用的提示資訊產生類似的視覺素材,並在重複使用前查看Awesome GPT Image 2 Prompts署名和商業用途授權資訊。
需要完整的提示符號集?請使用 其他靈感 主題中心提供更多相關範例,或打開 GPT Image 2 提示庫 有關完整範例索引、可重複使用結構和來源歸屬的資訊。
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提示詞
可直接複製的提示
PYTHON_SCENE_GRAPH :: PARAMETRIC_CITY_RELIEF class Variables: city = "{argument name="city" default="[CITY]"}" city_name_text = "{argument name="city name" default="literal city name from input"}" region_context = "infer country, terrain, climate, culture, urban identity" topography = "infer mountains, rivers, coastlines, plains, islands, deserts, hills" urban_grid = "infer district density, roads, transit corridors, urban pattern" landmarks = "infer landmark_set(city)" signature_core = "infer most symbolic central landmark or public space" style = "luxury 3D cartographic city model" class TerrainSlab: form = "thick raised cutout map base" surface = Variables.topography edges = "engraved title panel, legend, compass, scale, inset regional map" material = "matte stone/plaster/cartographic model material" class CityTypography: text = Variables. city_name_text form = "monumental 3D letters" function = "each letter is an inhabitable building mass" placement = "integrated into city map, not floating" rule = "word must remain readable from aerial view" class UrbanLayer: roads = Variables.urban_grid districts = "infer neighborhoods and density zones" landmarks = Variables.landmarks core = Variables.signature_core labels = "derive place labels from city geography" class Atmosphere: camera = "elevated three-quarter macro" lighting = "soft premium studio daylight" details = "vehicles, clouds, aircraft, trees, people only if appropriate" def render(): return """ Render {argument name="target city" default="[CITY]"} as a raised terrain-map diorama where the city name becomes monumental architecture, surrounded by inferred geography, landmarks, labels, roads, and atlas-style cartographic details. """提示變數
提示符號中可編輯的參數佔位符及其預設值。
多變的
city
預設
[CITY]
多變的
city name
預設
literal city name from input
多變的
target city
預設
[CITY]
Best for
- - 其他靈感 visual exploration
- - Image generation and reference-image edits
- - Reusable briefs that keep source attribution visible
Change these parts
- - Subject, product, character, or scene
- - Aspect ratio, camera, lighting, and background
- - Brand, text, color, and output constraints
Recommended model and settings
- - Model: gpt-image-2
- - Input mode: 文生圖
- - Aspect ratio: source
- - Commercial status: review original source
How to use this prompt
- 1. Copy the prompt and preserve its structure for the first test.
- 2. Replace the subject, context, and publishing channel.
- 3. Change one camera, lighting, or style variable per iteration.
- 4. Inspect the output, source, text, and rights before reuse.
Limitations, source, and reuse cautions
- - Generated output is an editable draft, not factual, legal, or rights evidence.
- - Review the linked source, people, brands, logos, text, and third-party media before commercial use.
內容來自Awesome GPT Image 2 Prompts 。必須註明出處。商業用途狀態為allowed ;付費使用前請查看來源版權資訊。
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重用和來源註釋
預覽案例後,請謹慎使用此提示。
- 1.複製提示或直接在 Dovoo 中使用生成按鈕開啟提示。
- 2.根據您的實際使用情況調整變數、寬高比和參考影像。
- 3.發布或付費使用前,請確認版權、署名要求以及品牌或肖像權風險。





