
原始文档
GPT Image 2 · en
I'm creating a magazine page with the theme "Visual Multilingualism". The title in the center of the image should be "{argument name="title" default="Create Everything at Once"} Please create an artwork that celebrates visual creation, not limited to exquisite photography, but encompassing the full breadth of human visual culture and natural visual elements. The image should include carefully curated collages with diverse distributions: scientific charts, the periodic table, the solar system, medieval manuscript pages, botanical illustrations, anatomical diagrams, ancient maps, climate charts, engineering diagrams, traffic signs, multilingual text, comic panels, and UI elements. Screenshots, camera photos, butterfly specimens, pie charts, architectural blueprints, and elevation drawings. The text positions the model as proficient in various languages, symbol systems, interfaces, cultural forms, and visual conventions—capable of shifting from practicality to aesthetics, from document understanding to art generation. Incorporate elements from all art forms, including pixel art, style, history, sculpture, nature, photography, and painting. These are just examples; I need you to actively consider other elements or styles that might suit excellent design, not just these concepts. The overall effect should have the quality of a high-end research announcement or a museum-style manifesto: elegant, grand, and designed to demonstrate that image intelligence should be trained on the entire visual world, not just refined aesthetics. Use unstructured, creative, and artistic layouts, such as, but not limited to, fan-shaped layouts, avoiding grid-like layouts. Use a 4:5 aspect ratio. Do not add any content text other than the "Create Everything at Once" heading. Text as part of the art is acceptable. Avoid an overall beige tone, as we want vibrant elements to remain vibrant.使用方法
- 复制完整原始提示词,并保留其中的参数。
- 按需求替换主体、文字和构图要求。
- 在兼容的外部工具中使用,核对当前使用条件并检查结果。
开始前需了解
- 先确认是否需要参考图。标注兼容模型,不代表该示例由这个模型生成。
- 核对名称、数字与画面文字;不同模型版本的结果可能不同。





