Parametric Dual-Read Optical Illusion Poster AI Image Prompt
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."
Content: The prompt uses pseudo-code with classes and variables to steer a parametric dual-read negative-space poster. Core: topic, negative-space dual read, minimalist flat style; palette inferred from mood (2-4 colors); optional paper grain; no lighting; flat poster view. Requires shared edges/contours; low detail, high clarity.
Pros: 1. Structured parametric design for easy variations. 2. Emphasizes negative space and dual reading, highly creative.
Cons: 1. Over-relies on AI inference, results may be inconsistent. 2. The 2x2 grid requirement conflicts with the actual output, causing confusion.
Reference image: No obvious reference-image dependency
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