Ming Image
Ming Image is an AI image generation model that employs a JSON-structured prompting style. It supports fine-grained control over image composition, layers, coordinates, lighting, and color through structured JSON parameters, enabling high-precision image generation.
Timeline (last 90 days)
A creator shared a Prompt Builder for Ming Image in the StableDiffusion community on Reddit.
Ming Image adopts a prompting style similar to Ideogram's, but relies more heavily on JSON-structured prompts to achieve deep model comprehension.
Ming Image prompts define overall parameters within canvas_settings, including aspect ratio, ambient lighting, and image style.
Each layer in the layers array of a Ming Image prompt contains four key fields: description, coordinates, hierarchy_and_relation, and color_specs.
In the layer coordinate system, cx and cy represent the normalized coordinates of an element's center point on the canvas, with values ranging from 0 to 1, where (0,0) corresponds to the top-left corner and (1,1) to the bottom-right corner.
The color_specs field uses hexadecimal color values to precisely define colors, avoiding ambiguous color expressions.
Some community members have noted that information and content about the Ming Image model on the StableDiffusion community is nearly nonexistent.
Publicly available real-world test samples and usage documentation for Ming Image are currently quite scarce.
All Facts (5)
Ming Image adopts a prompting style similar to Ideogram's, but relies more heavily on JSON-structured prompts to achieve deep model comprehension.
50%UnverifiedMing Image prompts define overall parameters within canvas_settings, including aspect ratio, ambient lighting, and image style.
50%UnverifiedEach layer in the layers array of a Ming Image prompt contains four key fields: description, coordinates, hierarchy_and_relation, and color_specs.
50%UnverifiedIn the layer coordinate system, cx and cy represent the normalized coordinates of an element's center point on the canvas, with values ranging from 0 to 1, where (0,0) corresponds to the top-left corner and (1,1) to the bottom-right corner.
50%UnverifiedThe color_specs field uses hexadecimal color values to precisely define colors, avoiding ambiguous color expressions.
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