QtMeshEditor-triposr-onnx

fernandotonon/QtMeshEditor-triposr-onnx

QtMeshEditor-triposr-onnx is a image-to-3d model from fernandotonon. Use it for the image-to-3d task on the model card, and read the license before you ship it in a product. It is set up for onnx. The card lists the license as mit.

ONNX re-export of stabilityai/TripoSR (Tripo AI + Stability AI — MIT code + MIT weights): single-image → 3D reconstruction via a triplane radiance field. All credit for the original weights goes to Tripo AI and Stabil…

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Public

Updated Jul 10, 2026

Repo size

2.1 GB

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Public

Hugging Face

Repo makeup

Click a slice to open those files.

.onnx2.1 GB · 100%

At a glance

Task: Image-to-3D
Library: onnx
License: mit
Access: Public
Created: Jul 10, 2026
Updated: Jul 10, 2026
SHA: 01b2f1ad

Model card

From the Hugging Face model README

TripoSR — ONNX export

ONNX re-export of stabilityai/TripoSR (Tripo AI + Stability AI — MIT code + MIT weights): single-image → 3D reconstruction via a triplane radiance field. All credit for the original weights goes to Tripo AI and Stability AI.

Exported for QtMeshEditor (epic #764), powering qtmesh generate3d, the Inspector's AI: Image → 3D section, and the generate_mesh_from_image MCP tool — local inference via ONNX Runtime, with surface extraction done by a native marching-cubes implementation (upstream's torchmcubes is torch/GPU-only).

The files QtMeshEditor downloads at runtime live in the shared fernandotonon/QtMeshEditor-models repo under triposr/. This repo is the standalone model card + mirror.

Files

file	role
`triposr_encoder.onnx`	fp32 encoder (best quality, ~1.7 GB): `image [1,3,512,512]` → `scene_codes [1,3,40,64,64]` (triplane)
`triposr_encoder_int8.onnx`	int8 encoder tier (~430 MB, slight quality loss)
`triposr_decoder.onnx`	per-point field decoder: `scene_codes` + `points [1,P,3]` → `density [1,P,1]`, `color [1,P,3]`

An fp16 tier is deliberately absent: TripoSR's attention has a hardcoded Cast-to-float32 that the ONNX fp16 converters cannot rewrite.

Inference contract

Input image: 512×512 RGB in [0,1], subject isolated (upstream composites over gray-128 and re-pads the foreground to a 0.85 ratio; QtMeshEditor uses U²-Net for background removal first).
Query the decoder in chunks — generating the full res³ grid up front OOMs at high resolutions.
Surface = marching cubes on density − threshold at iso 0, threshold 25.0, within radius 0.87. The field is inside-positive; emit flipped winding (v0,v2,v1) to keep faces outward.
Output is not +Y-up: bake −90°X then +90°Y to stand the model upright facing forward.
The decoder's colour output can also be used as an image-conditioned colour field for texture baking (per-texel queries after a UV unwrap).

Reproducing

scripts/export-triposr-onnx.py in the QtMeshEditor repo (one-time, offline; transformers==4.35.0, torchmcubes stubbed, frozen ViT positional encoding; emits the int8 variant unless --no-quant).

License

MIT (same as the upstream code and weights). Credit: Tripo AI + Stability AI.

Task: Image-to-3D
Library: onnx
License: mit
Created: Jul 10, 2026
Updated: Jul 10, 2026