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import base64
import hashlib
import json
import os
import shlex
import shutil
import subprocess
from dataclasses import dataclass
from pathlib import Path
from typing import Sequence
import torch
from huggingface_hub import hf_hub_download
from src.demo.infer_single_image import (
filter_final_gaussian_floaters,
load_demo_config,
load_demo_encoder,
load_demo_image_bundle,
patch_supersplat_html_auto_rotate,
patch_supersplat_html_viewer_bridge,
run_single_image_inference,
)
from src.model.encoder import Encoder
from src.utils.gaussians import Gaussians3D, save_ply
MODEL_REPO_ID = "PLUS-WAVE/InfiniSplat"
RGB_CHECKPOINT_FILE = "checkpoints/infinisplat_rgb.ckpt"
LOCAL_RGB_CHECKPOINT = Path(__file__).resolve().parents[2] / RGB_CHECKPOINT_FILE
RGB_EXPERIMENT = "infinisplat_hypersim_rgb"
SPLAT_TRANSFORM_PACKAGE = "@playcanvas/splat-transform@3.1.6"
VIEWER_SETTINGS = Path(__file__).resolve().parents[2] / "config" / "viewer_settings.json"
ARTIFACT_VERSION = 1
VIEWER_ASSET_FILENAMES = ("index.js", "index.css", "settings.json")
@dataclass(frozen=True)
class GaussianArtifact:
"""CPU-resident Gaussian tensors and camera metadata for one request."""
gaussians: Gaussians3D
focal_length_px: float
image_shape: tuple[int, int]
@dataclass(frozen=True)
class ExportedArtifacts:
"""Public output files generated for one request."""
scene_ply: Path
scene_sog: Path
viewer_html: Path
standalone_html: Path
@dataclass(frozen=True)
class BrowserViewerArtifacts:
"""Browser viewer files generated before standalone HTML bundling."""
scene_sog: Path
viewer_html: Path
@dataclass(frozen=True)
class ViewerTemplate:
"""Prebuilt viewer shell and content-addressed static assets."""
viewer_html: Path
viewer_assets_dir: Path
def _gaussians_to_dict(gaussians: Gaussians3D) -> dict[str, torch.Tensor | None]:
return {
"mean_vectors": gaussians.mean_vectors.detach().cpu(),
"singular_values": gaussians.singular_values.detach().cpu(),
"quaternions": gaussians.quaternions.detach().cpu(),
"colors": gaussians.colors.detach().cpu(),
"opacities": gaussians.opacities.detach().cpu(),
"covariances": None if gaussians.covariances is None else gaussians.covariances.detach().cpu(),
}
def save_gaussian_artifact(artifact: GaussianArtifact, path: Path) -> Path:
"""Serialize one request artifact using the safe torch data subset."""
path.parent.mkdir(parents=True, exist_ok=True)
torch.save(
{
"version": ARTIFACT_VERSION,
"gaussians": _gaussians_to_dict(artifact.gaussians),
"focal_length_px": artifact.focal_length_px,
"image_shape": list(artifact.image_shape),
},
path,
)
return path
def load_gaussian_artifact(path: Path) -> GaussianArtifact:
"""Load an internal request artifact without permitting arbitrary objects."""
payload = torch.load(path, map_location="cpu", weights_only=True)
if payload["version"] != ARTIFACT_VERSION:
raise ValueError(f"Unsupported Gaussian artifact version: {payload['version']}")
tensors = payload["gaussians"]
gaussians = Gaussians3D(
mean_vectors=tensors["mean_vectors"],
singular_values=tensors["singular_values"],
quaternions=tensors["quaternions"],
colors=tensors["colors"],
opacities=tensors["opacities"],
covariances=tensors["covariances"],
)
return GaussianArtifact(
gaussians=gaussians,
focal_length_px=float(payload["focal_length_px"]),
image_shape=tuple(int(value) for value in payload["image_shape"]),
)
def _default_splat_transform_prefix() -> list[str]:
override = os.environ.get("SPLAT_TRANSFORM")
if override:
return shlex.split(override)
return ["npx", "--yes", "--prefer-offline", SPLAT_TRANSFORM_PACKAGE]
def build_splat_transform_command(
scene_ply: Path,
output_sog: Path,
command_prefix: Sequence[str] | None = None,
) -> list[str]:
"""Build the fixed, non-interactive SOG conversion command."""
prefix = list(command_prefix) if command_prefix is not None else _default_splat_transform_prefix()
return [
*prefix,
"--quiet",
"--overwrite",
str(scene_ply),
"--filter-harmonics",
"0",
str(output_sog),
]
def build_viewer_template_command(
scene_ply: Path,
output_html: Path,
viewer_settings: Path = VIEWER_SETTINGS,
command_prefix: Sequence[str] | None = None,
) -> list[str]:
"""Build the one-time command that emits the SuperSplat viewer shell."""
prefix = list(command_prefix) if command_prefix is not None else _default_splat_transform_prefix()
return [
*prefix,
"--quiet",
"--overwrite",
"--unbundled",
"--viewer-settings",
str(viewer_settings),
str(scene_ply),
"--filter-harmonics",
"0",
str(output_html),
]
def _replace_once(source: str, old: str, new: str, description: str) -> str:
if source.count(old) != 1:
raise RuntimeError(
f"Could not bundle SuperSplat {description}; the viewer template changed."
)
return source.replace(old, new, 1)
def build_standalone_viewer(
viewer_html: Path,
viewer_assets_dir: Path,
output_html: Path,
) -> Path:
"""Bundle a shared-asset SuperSplat viewer for single-file download."""
scene_sog = viewer_html.with_suffix(".sog")
source = viewer_html.read_text(encoding="utf-8")
css = (viewer_assets_dir / "index.css").read_text(encoding="utf-8")
javascript = (viewer_assets_dir / "index.js").read_text(encoding="utf-8")
settings = json.loads((viewer_assets_dir / "settings.json").read_text(encoding="utf-8"))
encoded_scene = base64.b64encode(scene_sog.read_bytes()).decode("ascii")
shared_prefix = Path(os.path.relpath(viewer_assets_dir, viewer_html.parent)).as_posix()
source = _replace_once(
source,
f'<link rel="stylesheet" href="{shared_prefix}/index.css">',
f"<style>\n{css}\n </style>",
"stylesheet",
)
source = _replace_once(
source,
f"import {{ main }} from '{shared_prefix}/index.js';",
javascript,
"script",
)
source = _replace_once(
source,
"settings: fetch(settingsUrl).then(response => response.json())",
f"settings: {json.dumps(settings, separators=(',', ':'), ensure_ascii=False)}",
"settings",
)
source = _replace_once(
source,
f'fetch("{scene_sog.name}")',
f'fetch("data:application/octet-stream;base64,{encoded_scene}")',
"scene data",
)
output_html.write_text(source, encoding="utf-8")
return output_html
def install_shared_viewer_assets(viewer_html: Path) -> Path:
"""Point an unbundled viewer at content-addressed shared static assets."""
asset_paths = [viewer_html.parent / name for name in VIEWER_ASSET_FILENAMES]
hasher = hashlib.sha256()
for asset_path in asset_paths:
hasher.update(asset_path.name.encode("utf-8"))
hasher.update(asset_path.read_bytes())
digest = hasher.hexdigest()[:16]
shared_dir = viewer_html.parent.parent / "_viewer_assets" / digest
shared_dir.mkdir(parents=True, exist_ok=True)
for asset_path in asset_paths:
destination = shared_dir / asset_path.name
if not destination.exists():
shutil.copyfile(asset_path, destination)
shared_prefix = f"../_viewer_assets/{digest}"
source = viewer_html.read_text(encoding="utf-8")
source = _replace_once(
source,
"./index.css",
f"{shared_prefix}/index.css",
"shared stylesheet path",
)
source = _replace_once(
source,
"./index.js",
f"{shared_prefix}/index.js",
"shared script path",
)
source = _replace_once(
source,
"./settings.json",
f"{shared_prefix}/settings.json",
"shared settings path",
)
viewer_html.write_text(source, encoding="utf-8")
return shared_dir
def _viewer_bootstrap_gaussians() -> Gaussians3D:
"""Create one tiny Gaussian used only to build the shared viewer shell."""
return Gaussians3D(
mean_vectors=torch.tensor([[[0.0, 0.0, 1.0]]]),
singular_values=torch.tensor([[[0.001, 0.001, 0.001]]]),
quaternions=torch.tensor([[[1.0, 0.0, 0.0, 0.0]]]),
colors=torch.tensor([[[0.5, 0.5, 0.5]]]),
opacities=torch.tensor([[0.01]]),
)
def prepare_viewer_template(
output_root: Path,
command_prefix: Sequence[str] | None = None,
) -> ViewerTemplate:
"""Generate and cache the viewer shell before the first user request."""
template_dir = output_root / "_viewer_template"
template_dir.mkdir(parents=True, exist_ok=True)
bootstrap_ply = template_dir / "template.ply"
viewer_html = template_dir / "template.html"
save_ply(
gaussians=_viewer_bootstrap_gaussians(),
f_px=1.0,
image_shape=(1, 1),
path=bootstrap_ply,
)
converter_environment = os.environ.copy()
xdg_runtime_dir = template_dir / ".xdg-runtime"
xdg_runtime_dir.mkdir(mode=0o700, exist_ok=True)
converter_environment["XDG_RUNTIME_DIR"] = str(xdg_runtime_dir)
subprocess.run(
build_viewer_template_command(
scene_ply=bootstrap_ply,
output_html=viewer_html,
command_prefix=command_prefix,
),
check=True,
env=converter_environment,
)
patch_supersplat_html_auto_rotate(viewer_html)
patch_supersplat_html_viewer_bridge(
viewer_html,
viewer_script_path=template_dir / "index.js",
)
viewer_assets_dir = install_shared_viewer_assets(viewer_html)
return ViewerTemplate(
viewer_html=viewer_html,
viewer_assets_dir=viewer_assets_dir,
)
def create_request_viewer(
viewer_template: ViewerTemplate,
scene_sog: Path,
viewer_html: Path,
) -> Path:
"""Create a small request page that reuses the prebuilt viewer shell."""
template_scene = viewer_template.viewer_html.with_suffix(".sog")
source = viewer_template.viewer_html.read_text(encoding="utf-8")
source = _replace_once(
source,
f'fetch("{template_scene.name}")',
f'fetch("{scene_sog.name}")',
"scene data path",
)
viewer_html.write_text(source, encoding="utf-8")
return viewer_html
def export_filtered_gaussian_ply(
artifact_path: Path,
output_dir: Path,
) -> Path:
"""Filter spatial outliers and export the resulting Gaussian PLY."""
artifact = load_gaussian_artifact(artifact_path)
gaussians = filter_final_gaussian_floaters(artifact.gaussians)
output_dir.mkdir(parents=True, exist_ok=True)
scene_ply = output_dir / "scene.ply"
save_ply(
gaussians=gaussians,
f_px=artifact.focal_length_px,
image_shape=artifact.image_shape,
path=scene_ply,
)
return scene_ply
def export_browser_viewer(
scene_ply: Path,
viewer_template: ViewerTemplate,
command_prefix: Sequence[str] | None = None,
) -> BrowserViewerArtifacts:
"""Convert one PLY into the optimized browser viewer files."""
output_dir = scene_ply.parent
scene_sog = output_dir / "viewer.sog"
viewer_html = output_dir / "viewer.html"
converter_environment = os.environ.copy()
xdg_runtime_dir = output_dir / ".xdg-runtime"
xdg_runtime_dir.mkdir(mode=0o700, exist_ok=True)
converter_environment["XDG_RUNTIME_DIR"] = str(xdg_runtime_dir)
subprocess.run(
build_splat_transform_command(
scene_ply=scene_ply,
output_sog=scene_sog,
command_prefix=command_prefix,
),
check=True,
env=converter_environment,
)
create_request_viewer(
viewer_template=viewer_template,
scene_sog=scene_sog,
viewer_html=viewer_html,
)
return BrowserViewerArtifacts(
scene_sog=scene_sog,
viewer_html=viewer_html,
)
def export_standalone_viewer(
viewer_html: Path,
viewer_template: ViewerTemplate,
) -> Path:
"""Bundle one browser viewer into a directly downloadable HTML file."""
return build_standalone_viewer(
viewer_html=viewer_html,
viewer_assets_dir=viewer_template.viewer_assets_dir,
output_html=viewer_html.with_name("scene.html"),
)
def export_gaussian_artifact(
artifact_path: Path,
output_dir: Path,
viewer_template: ViewerTemplate,
command_prefix: Sequence[str] | None = None,
) -> ExportedArtifacts:
"""Export filtered Gaussians and both viewer formats."""
scene_ply = export_filtered_gaussian_ply(
artifact_path=artifact_path,
output_dir=output_dir,
)
browser_viewer = export_browser_viewer(
scene_ply=scene_ply,
viewer_template=viewer_template,
command_prefix=command_prefix,
)
standalone_html = export_standalone_viewer(
viewer_html=browser_viewer.viewer_html,
viewer_template=viewer_template,
)
return ExportedArtifacts(
scene_ply=scene_ply,
scene_sog=browser_viewer.scene_sog,
viewer_html=browser_viewer.viewer_html,
standalone_html=standalone_html,
)
def resolve_rgb_checkpoint() -> Path:
"""Resolve an override, reuse a repository checkpoint, or download it."""
local_checkpoint = os.environ.get("INFINISPLAT_CHECKPOINT")
if local_checkpoint:
checkpoint_path = Path(local_checkpoint)
if not checkpoint_path.is_file():
raise FileNotFoundError(f"Checkpoint not found: {checkpoint_path}")
return checkpoint_path
if LOCAL_RGB_CHECKPOINT.is_file():
return LOCAL_RGB_CHECKPOINT
return Path(
hf_hub_download(
repo_id=os.environ.get("INFINISPLAT_MODEL_REPO", MODEL_REPO_ID),
filename=RGB_CHECKPOINT_FILE,
revision=os.environ.get("INFINISPLAT_MODEL_REVISION", "main"),
)
)
class InfiniSplatRuntime:
"""One process-wide RGB encoder reused by all web requests."""
def __init__(self, encoder: Encoder, device: torch.device) -> None:
self.encoder = encoder
self.device = device
@classmethod
def load(
cls,
checkpoint_path: Path | None = None,
device: str | torch.device | None = None,
) -> "InfiniSplatRuntime":
resolved_device = torch.device(
device or ("cuda" if torch.cuda.is_available() else "cpu")
)
cfg = load_demo_config(RGB_EXPERIMENT)
encoder = load_demo_encoder(
cfg=cfg,
checkpoint_path=checkpoint_path or resolve_rgb_checkpoint(),
device=resolved_device,
)
return cls(encoder=encoder, device=resolved_device)
@torch.inference_mode()
def infer_to_artifact(self, image_path: Path, artifact_path: Path) -> Path:
"""Run one RGB reconstruction and persist CPU tensors for post-processing."""
image_bundle = load_demo_image_bundle(image_path=image_path)
encoder_output = run_single_image_inference(
encoder=self.encoder,
image=image_bundle.inference_image,
intrinsics_px=image_bundle.inference_intrinsics.intrinsics_px,
device=self.device,
)
_, height, width = image_bundle.inference_image.shape
artifact = GaussianArtifact(
gaussians=encoder_output["gaussians"].to("cpu"),
focal_length_px=image_bundle.inference_intrinsics.focal_length_px,
image_shape=(height, width),
)
return save_gaussian_artifact(artifact, artifact_path)
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