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https://github.com/comfyanonymous/ComfyUI.git
synced 2026-04-16 05:22:30 +08:00
remove(isolation): drop internal ply and npz support
This commit is contained in:
John Pollock
parent
b1bcaaf8fe
commit
3b0fc0ab87
@ -2,7 +2,7 @@
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Drop-in replacement for comfy_api.latest._util type imports in sealed workers
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that do not have torch installed. Contains only data type definitions (TrimeshData,
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PLY, NPZ, etc.) with numpy-only dependencies.
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etc.) with numpy-only dependencies.
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Usage in serializers:
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if _IMPORT_TORCH:
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@ -12,7 +12,5 @@ Usage in serializers:
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"""
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from .trimesh_types import TrimeshData
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from .ply_types import PLY
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from .npz_types import NPZ
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__all__ = ["TrimeshData", "PLY", "NPZ"]
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__all__ = ["TrimeshData"]
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@ -1,27 +0,0 @@
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from __future__ import annotations
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import os
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class NPZ:
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"""Ordered collection of NPZ file payloads.
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Each entry in ``frames`` is a complete compressed ``.npz`` file stored
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as raw bytes (produced by ``numpy.savez_compressed`` into a BytesIO).
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``save_to`` writes numbered files into a directory.
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"""
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def __init__(self, frames: list[bytes]) -> None:
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self.frames = frames
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@property
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def num_frames(self) -> int:
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return len(self.frames)
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def save_to(self, directory: str, prefix: str = "frame") -> str:
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os.makedirs(directory, exist_ok=True)
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for i, frame_bytes in enumerate(self.frames):
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path = os.path.join(directory, f"{prefix}_{i:06d}.npz")
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with open(path, "wb") as f:
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f.write(frame_bytes)
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return directory
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@ -1,97 +0,0 @@
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from __future__ import annotations
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import numpy as np
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class PLY:
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"""Point cloud payload for PLY file output.
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Supports two schemas:
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- Pointcloud: xyz positions with optional colors, confidence, view_id (ASCII format)
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- Gaussian: raw binary PLY data built by producer nodes using plyfile (binary format)
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When ``raw_data`` is provided, the object acts as an opaque binary PLY
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carrier and ``save_to`` writes the bytes directly.
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"""
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def __init__(
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self,
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points: np.ndarray | None = None,
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colors: np.ndarray | None = None,
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confidence: np.ndarray | None = None,
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view_id: np.ndarray | None = None,
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raw_data: bytes | None = None,
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) -> None:
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self.raw_data = raw_data
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if raw_data is not None:
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self.points = None
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self.colors = None
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self.confidence = None
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self.view_id = None
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return
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if points is None:
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raise ValueError("Either points or raw_data must be provided")
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if points.ndim != 2 or points.shape[1] != 3:
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raise ValueError(f"points must be (N, 3), got {points.shape}")
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self.points = np.ascontiguousarray(points, dtype=np.float32)
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self.colors = np.ascontiguousarray(colors, dtype=np.float32) if colors is not None else None
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self.confidence = np.ascontiguousarray(confidence, dtype=np.float32) if confidence is not None else None
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self.view_id = np.ascontiguousarray(view_id, dtype=np.int32) if view_id is not None else None
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@property
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def is_gaussian(self) -> bool:
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return self.raw_data is not None
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@property
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def num_points(self) -> int:
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if self.points is not None:
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return self.points.shape[0]
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return 0
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@staticmethod
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def _to_numpy(arr, dtype):
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if arr is None:
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return None
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if hasattr(arr, "numpy"):
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arr = arr.cpu().numpy() if hasattr(arr, "cpu") else arr.numpy()
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return np.ascontiguousarray(arr, dtype=dtype)
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def save_to(self, path: str) -> str:
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if self.raw_data is not None:
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with open(path, "wb") as f:
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f.write(self.raw_data)
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return path
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self.points = self._to_numpy(self.points, np.float32)
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self.colors = self._to_numpy(self.colors, np.float32)
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self.confidence = self._to_numpy(self.confidence, np.float32)
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self.view_id = self._to_numpy(self.view_id, np.int32)
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N = self.num_points
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header_lines = [
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"ply",
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"format ascii 1.0",
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f"element vertex {N}",
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"property float x",
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"property float y",
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"property float z",
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]
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if self.colors is not None:
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header_lines += ["property uchar red", "property uchar green", "property uchar blue"]
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if self.confidence is not None:
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header_lines.append("property float confidence")
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if self.view_id is not None:
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header_lines.append("property int view_id")
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header_lines.append("end_header")
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with open(path, "w") as f:
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f.write("\n".join(header_lines) + "\n")
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for i in range(N):
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parts = [f"{self.points[i, 0]} {self.points[i, 1]} {self.points[i, 2]}"]
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if self.colors is not None:
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r, g, b = (self.colors[i] * 255).clip(0, 255).astype(np.uint8)
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parts.append(f"{r} {g} {b}")
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if self.confidence is not None:
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parts.append(f"{self.confidence[i]}")
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if self.view_id is not None:
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parts.append(f"{int(self.view_id[i])}")
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f.write(" ".join(parts) + "\n")
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return path
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@ -1,40 +0,0 @@
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import os
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import folder_paths
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from comfy_api.latest import io
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from comfy_api_sealed_worker.npz_types import NPZ
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class SaveNPZ(io.ComfyNode):
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@classmethod
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def define_schema(cls):
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return io.Schema(
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node_id="SaveNPZ",
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display_name="Save NPZ",
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category="3d",
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is_output_node=True,
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inputs=[
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io.Npz.Input("npz"),
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io.String.Input("filename_prefix", default="da3_streaming/ComfyUI"),
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],
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)
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@classmethod
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def execute(cls, npz: NPZ, filename_prefix: str) -> io.NodeOutput:
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full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
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filename_prefix, folder_paths.get_output_directory()
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)
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batch_dir = os.path.join(full_output_folder, f"{filename}_{counter:05}")
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os.makedirs(batch_dir, exist_ok=True)
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filenames = []
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for i, frame_bytes in enumerate(npz.frames):
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f = f"frame_{i:06d}.npz"
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with open(os.path.join(batch_dir, f), "wb") as fh:
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fh.write(frame_bytes)
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filenames.append(f)
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return io.NodeOutput(ui={"npz_files": [{"folder": os.path.join(subfolder, f"{filename}_{counter:05}"), "count": len(filenames), "type": "output"}]})
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NODE_CLASS_MAPPINGS = {
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"SaveNPZ": SaveNPZ,
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}
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@ -1,34 +0,0 @@
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import os
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import folder_paths
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from comfy_api.latest import io
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from comfy_api_sealed_worker.ply_types import PLY
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class SavePLY(io.ComfyNode):
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@classmethod
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def define_schema(cls):
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return io.Schema(
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node_id="SavePLY",
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display_name="Save PLY",
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category="3d",
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is_output_node=True,
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inputs=[
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io.Ply.Input("ply"),
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io.String.Input("filename_prefix", default="pointcloud/ComfyUI"),
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],
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)
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@classmethod
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def execute(cls, ply: PLY, filename_prefix: str) -> io.NodeOutput:
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full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
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filename_prefix, folder_paths.get_output_directory()
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)
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f = f"{filename}_{counter:05}_.ply"
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ply.save_to(os.path.join(full_output_folder, f))
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return io.NodeOutput(ui={"pointclouds": [{"filename": f, "subfolder": subfolder, "type": "output"}]})
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NODE_CLASS_MAPPINGS = {
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"SavePLY": SavePLY,
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}
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