Image prompt
A unique structural prompt for generating dual-read negative-space posters using a parametric logic style.
Copy directly into the target model and adjust for your input assets.
2x2 grid, do this for ai inferred figures and colors: python_scene_graph :: parametric_optical_illusion class variables: topic = "{argument name="topic" default="[topic]"}" duality = "infer opposing or layered meanings" primary_silhouette = "infer dominant readable outer shape" hidden_image = "infer secondary image from negative space" symbols = "infer minimal supporting symbols" palette = "infer 2-4 colors from mood" style = "minimalist negative-space poster" class composition: first_read = variables.primary_silhouette second_read = variables.hidden_image rule = "both images must share edges and contours" density = "low detail, high clarity" class shapelogic: black_shapes = "define primary silhouette" white_or_color_voids = "define hidden image" intersections = "designed so both readings remain intentional" class render: camera = "flat poster view" texture = "subtle paper grain optional" lighting = "none; graphic design clarity" output = "clean optical metaphor poster" def generate(): return "render {argument name="topic" default="[topic]"} as a dual-read negative-space image with no hard-coded symbols."
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。