TripoSG — ONNX export (staged graphs)
ONNX re-export of VAST-AI/TripoSG (SIGGRAPH 2025 — MIT code + MIT weights): a 1.5B-parameter rectified-flow diffusion transformer over an SDF VAE, single image → high-fidelity 3D geometry (≈ commercial Tripo 2.0 quality). All credit for the original weights goes to VAST-AI-Research.
Exported as four staged graphs so the flow loop runs in plain host code —
for QtMeshEditor
(qtmesh generate3d --backend triposg, GUI Backend dropdown, MCP backend
arg), local inference via ONNX Runtime + native marching cubes.
The files QtMeshEditor downloads at runtime live in the shared
fernandotonon/QtMeshEditor-modelsrepo undertriposg/. This repo is the standalone model card + mirror.
Files
| file | role |
|---|---|
triposg_image_encoder.onnx | DINOv2-224 image encoder (mean/std baked in; CFG unconditional = zeros) |
triposg_dit_step.onnx + .data | one DiT flow step (fp32, ~5.8 GB external weights) |
triposg_vae_latents.onnx | VAE latent KV-cache graph — run once per generation |
triposg_vae_decoder.onnx | per-point SDF field decoder |
An int8 DiT tier exists in the aggregate repo but is not recommended: even per-channel-quantized, the 1.5B DiT degrades to blobs over the 25-step CFG flow loop, and dynamic-int8 MatMuls are no faster than fp32 on ARM.
Inference contract
- Flow loop (host code):
σᵢ = 1 − i/N, timestep1000·σᵢ, updatex += (σᵢ − σᵢ₊₁)·v— note the sign is opposite of stock diffusersFlowMatchEulerDiscreteScheduler. CFG as two batch-1 calls, guidance 7.0, 25 steps default. - Background removal should composite over white (TripoSG's reference pipeline), not gray.
- The exported field decoder is outside-positive — negate for inside-positive marching cubes at iso 0; query bounds ±1.005.
- Query the decoder in chunks of ≤ 8192 points (cross-attention to 2048 kv tokens; huge chunks OOM). Open/release the sessions per stage to keep peak memory ~1 GB instead of the >4 GB sum.
- Output is already +Y-up.
- Geometry only — TripoSG has no colour decoder. QtMeshEditor bakes colour
by projecting the input photo onto the visible front and filling the rest
from TripoSR's image-conditioned colour field (see
QtMeshEditor-triposr-onnx).
Full measured export contract: docs/TRIPOSG_EXPORT_NOTES.md in the
QtMeshEditor repo.
Reproducing
scripts/export-triposg-onnx.py in the QtMeshEditor repo (one-time, offline).
License
MIT (same as the upstream code and weights). Credit: VAST-AI-Research.