3D Mechanical Part Image to Technical Drawing Conversion
{ "task": "image_to_image", "input_image": "3d_render_of_mechanical_part.png", "prompt": "Reference scale: the outer diameter of the f…
Prompt
{
"task": "image_to_image",
"input_image": "3d_render_of_mechanical_part.png",
"prompt": "Reference scale: the outer diameter of the flange is exactly 360 mm. Mechanical engineering drawing sheet with three separate drawings of the same part placed in clearly separated rectangular areas. Drawing 1: fully dimensioned orthographic views (front, top, side) with precise numeric measurements in millimeters, diameter symbols, radius annotations, hole count notation and center lines. Drawing 2: sectional view taken through the center axis of the part, showing internal geometry with proper section hatching and wall thickness clearly visible. Drawing 3: isometric reference view of the part without any dimensions, used only for spatial understanding. ISO mechanical drafting standard, consistent line weights, monochrome black lines on white background, manufacturing-ready technical documentation, no perspective distortion.",
"negative_prompt": "single combined drawing, merged views, artistic rendering, perspective view, realistic lighting, shadows, textures, colors, gradients, sketch style, hand drawn look, missing dimensions, decorative presentation",
"settings": {
"model": "sdxl",
"sampler": "DPM++ 2M Karras",
"steps": 45,
"cfg_scale": 6,
"denoising_strength": 0.45,
"resolution": {
"width": 1024,
"height": 1024
}
},
"output_expectation": "one technical drawing sheet containing three clearly separated drawings: dimensioned orthographic views, a centered sectional view, and an undimensioned isometric reference, suitable for manufacturing reference"
}
,FALSE,STRUCTURED,senoldakHow to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
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