Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,72 @@
+---
+license: mit
+tags:
+  - onnx
+  - image-to-3d
+  - 3d-generation
+  - rectified-flow
+  - diffusion-transformer
+  - qtmesheditor
+library_name: onnx
+pipeline_tag: image-to-3d
+---
+
+# TripoSG — ONNX export (staged graphs)
+
+**ONNX re-export of [VAST-AI/TripoSG](https://huggingface.co/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](https://github.com/fernandotonon/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-models`](https://huggingface.co/fernandotonon/QtMeshEditor-models)
+> repo under `triposg/`. 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`, timestep `1000·σᵢ`, update
+  `x += (σᵢ − σᵢ₊₁)·v` — note the sign is **opposite** of stock diffusers
+  `FlowMatchEulerDiscreteScheduler`. 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`](https://huggingface.co/fernandotonon/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.