chore: auto-commit (5 archivos)

- CMakeLists.txt
- app.md
- appicon.ico
- backend/
- main.cpp

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

backend/backends/_iface.py

@@ -0,0 +1,17 @@
+"""Interfaz comun para backends image-to-3D.
+
+Cada backend (triposr, hunyuan3d_2, trellis) expone:
+  load() -> Handle
+  donde Handle tiene metodo infer(image: PIL.Image, cfg: dict) -> bytes (GLB).
+
+`cfg` recibe: seed, mc_resolution, foreground_ratio, texture.
+"""
+from __future__ import annotations
+
+from typing import Protocol, Any, Dict
+from PIL import Image
+
+
+class BackendHandle(Protocol):
+    def infer(self, image: Image.Image, cfg: Dict[str, Any]) -> bytes: ...
+    def close(self) -> None: ...

backend/backends/hunyuan3d_2.py

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+"""Backend Hunyuan3D-2 (Tencent, Community License).
+
+STUB. Para implementar: clonar github.com/Tencent/Hunyuan3D-2 a sources/,
+instalar deps, cargar pipeline shape + texture.
+"""
+from __future__ import annotations
+
+from typing import Any, Dict
+from PIL import Image
+
+
+class Handle:
+    def infer(self, image: Image.Image, cfg: Dict[str, Any]) -> bytes:
+        raise NotImplementedError(
+            "hunyuan3d-2 backend pendiente. Ver notebook 03_smoke_hunyuan3d.ipynb"
+        )
+
+    def close(self) -> None:  # pragma: no cover
+        return
+
+
+def load() -> Handle:
+    return Handle()

backend/backends/trellis.py

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+"""Backend Trellis (Microsoft, MIT code).
+
+STUB. Para implementar: clonar github.com/microsoft/TRELLIS a sources/,
+instalar deps (kaolin + custom CUDA), cargar pipeline structured latents.
+"""
+from __future__ import annotations
+
+from typing import Any, Dict
+from PIL import Image
+
+
+class Handle:
+    def infer(self, image: Image.Image, cfg: Dict[str, Any]) -> bytes:
+        raise NotImplementedError(
+            "trellis backend pendiente. Ver notebook 04_smoke_trellis.ipynb"
+        )
+
+    def close(self) -> None:  # pragma: no cover
+        return
+
+
+def load() -> Handle:
+    return Handle()

backend/backends/triposr.py

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+"""Backend TripoSR (Stability + Tripo, MIT).
+
+Asume que `sources/TripoSR` esta clonado en el registry. Importa `tsr.system.TSR`.
+Descarga checkpoint desde HF en la primera carga (~1.2 GB).
+"""
+from __future__ import annotations
+
+import io
+import os
+import pathlib
+import sys
+from dataclasses import dataclass
+from typing import Any, Dict
+
+import numpy as np
+import torch
+import trimesh
+from PIL import Image
+
+
+def _ensure_sources_on_path() -> pathlib.Path:
+    root = pathlib.Path(os.environ.get("FN_REGISTRY_ROOT", "/home/lucas/fn_registry"))
+    src  = root / "sources" / "TripoSR"
+    if not src.exists():
+        raise RuntimeError(
+            f"TripoSR no clonado en {src}. "
+            "git clone --depth=1 https://github.com/VAST-AI-Research/TripoSR.git "
+            f"{src}"
+        )
+    if str(src) not in sys.path:
+        sys.path.insert(0, str(src))
+    return src
+
+
+@dataclass
+class Handle:
+    model: Any
+    rembg_session: Any
+    device: str
+
+    def infer(self, image: Image.Image, cfg: Dict[str, Any]) -> bytes:
+        from tsr.utils import remove_background, resize_foreground
+
+        fg_ratio = float(cfg.get("foreground_ratio", 0.85))
+        mc_res   = int(cfg.get("mc_resolution", 256))
+
+        fg = remove_background(image, self.rembg_session)
+        fg = resize_foreground(fg, fg_ratio)
+
+        # Composite RGBA -> RGB sobre gris 0.5 (preprocesado canonico TripoSR
+        # run.py). Sin esto el tokenizer DINO recibe 4 canales y peta:
+        # "The size of tensor a (4) must match tensor b (3) at dim 2".
+        arr = np.asarray(fg).astype(np.float32) / 255.0
+        if arr.shape[-1] == 4:
+            arr = arr[:, :, :3] * arr[:, :, 3:4] + (1.0 - arr[:, :, 3:4]) * 0.5
+            fg = Image.fromarray((arr * 255.0).astype(np.uint8))
+
+        with torch.no_grad():
+            scene_codes = self.model([fg], device=self.device)
+            meshes = self.model.extract_mesh(
+                scene_codes, has_vertex_color=False, resolution=mc_res
+            )
+        m = meshes[0]
+        tm = trimesh.Trimesh(
+            vertices=np.asarray(m.vertices),
+            faces=np.asarray(m.faces),
+            process=True,
+        )
+        buf = io.BytesIO()
+        tm.export(buf, file_type="glb")
+        return buf.getvalue()
+
+    def close(self) -> None:
+        del self.model
+        del self.rembg_session
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+
+
+def load() -> Handle:
+    _ensure_sources_on_path()
+    from tsr.system import TSR
+    from rembg import new_session
+
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model = TSR.from_pretrained(
+        "stabilityai/TripoSR",
+        config_name="config.yaml",
+        weight_name="model.ckpt",
+    )
+    model.renderer.set_chunk_size(8192)
+    model.to(device)
+    return Handle(model=model, rembg_session=new_session(), device=device)