Image to 3D API

An image to 3D API generates a three-dimensional asset from reference pictures. It uses visible shape and appearance to infer a mesh and supported textures. Hidden surfaces are reconstructed rather than measured, so inspect the complete asset before relying on its geometry.

Use a clear image with one main subject, visible boundaries and limited obstruction. Avoid extreme perspective, busy backgrounds and reflections that hide the object shape. A well-framed reference gives the model a better basis than a small object inside a complex scene.

Some endpoints support multiview inputs and others use one image. Check the image count, expected ordering and supported fields. Provide consistent pictures of the same object; contradictory designs or changing proportions can make reconstruction less reliable.

A single picture does not show the back or hidden surfaces, so the model infers them. Use additional consistent views where supported, or refine the mesh afterward. For important unseen details, provide a suitable reference workflow rather than relying on a front view alone.

You can test a supported image-to-3D model with a clear character design. Inspect anatomy, separated limbs, clothing and hidden surfaces. If animation is required, check topology and use a separate rigging workflow unless the endpoint explicitly provides that capability.

Texture behavior depends on the selected model and settings. Check which maps or embedded materials the endpoint returns. Download all required files and inspect UV alignment, seams and material channels in your editor rather than assuming the preview represents a complete portable asset.

Use the export files documented for the selected endpoint. Confirm compatibility with your target viewer, Blender project or game engine, including texture packaging. Mesh conversion may be needed when the downstream application requires a format that the generation endpoint does not return.

Generative reconstruction is not the same as measured CAD or a dimensionally verified scan. It is useful for visual concepts and asset drafts. If precise tolerances, dimensions or physical fit matter, use measurement and engineering validation in a suitable downstream workflow.

Submit the chosen model and supported image references through PoYo generation. Save task_id and obtain the completed output through status polling or a supported callback_url. Preserve mesh and texture files together and verify the downloaded asset before delivering it to your users.

Read the current model tiers for generation mode, texture options and reference processing. Single-image and multiview operations may use different settings or prices. Estimate the complete selected workflow, including any separately priced refinement steps.

Start with sharper references and simplify the scene around the object. Use consistent views where supported, then inspect whether the problem is geometry, UVs or texture detail. Model changes or downstream mesh and texture repair may be more effective than repeatedly submitting the same unsuitable image.

Test representative products or characters, download the actual output files and import them into the target application. Check scale, orientation, silhouette, material links and processing cost. The model page and llms.txt resource provide current request fields and examples for integration.