Chinese Conceptual Poster Generator - Image 1

Image prompt

Chinese Conceptual Poster Generator

A sophisticated system prompt for generating high-end Chinese conceptual posters based on a single title, focusing on social issues, metaphors, and cinematic magazine-style layouts.

Model
GPT Image 2 Prompts
Category
Poster / Flyer
Source
Internal curation
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Full Prompt

Copy directly into the target model and adjust for your input assets.

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Based on the provided [Title], automatically generate a high-end Chinese conceptual poster. User only provides Title: {argument name="title content" default="Enter title here"}. Your task: Understand the theme, mood, social issues, and metaphors behind the title, then complete the visual design. Do not mechanically illustrate the title; translate it into a cinematic, magazine-style visual poster. 1. Style: High-end horizontal concept poster. Mood can range from social issues, psychological insights, humanity, intimacy, to workplace pressure. It should look like a deep-dive article cover or art exhibition visual. 2. Layout: Large title on the left/top, visual metaphor on the right/bottom. Strong relationship between text and image. High impact, memory points, and whitespace. Default to landscape 16:9, 4:3, or 3:1. 3. Typography: Main title must be huge and central. Subtitle generated automatically (max 24 characters) explaining the deep issue. Bottom tags (4-6) separated by vertical lines. Fonts matched to theme (Serif for social critique, bold Sans-serif for psychological insight). 4. Visual Metaphor: Use elements like broken statues, empty chairs, mirrors, night cityscapes, or medical images. Focus on 1 strong metaphor + 2-4 details. 5. Atmosphere: Low saturation, advanced lighting, cinematic grain, depth of emotion. No cute or bright internet template styles. 6. Output: A single high-res 4K complete poster in Chinese. No process explanation, just the image.

Source Record

Original source details are kept for attribution and review.

GitHub source:YouMind-OpenLab/gpt-image-2-prompts-search

This page is adapted from YouMind OpenLab GitHub prompt libraries. License: MIT。