remove(isolation): drop internal ply and npz support

comfy_api_sealed_worker/__init__.py

@@ -2,7 +2,7 @@
 
 Drop-in replacement for comfy_api.latest._util type imports in sealed workers
 that do not have torch installed. Contains only data type definitions (TrimeshData,
-PLY, NPZ, etc.) with numpy-only dependencies.
+etc.) with numpy-only dependencies.
 
 Usage in serializers:
     if _IMPORT_TORCH:
@@ -12,7 +12,5 @@ Usage in serializers:
 """
 
 from .trimesh_types import TrimeshData
-from .ply_types import PLY
-from .npz_types import NPZ
 
-__all__ = ["TrimeshData", "PLY", "NPZ"]
+__all__ = ["TrimeshData"]

comfy_api_sealed_worker/npz_types.py

@@ -1,27 +0,0 @@
-from __future__ import annotations
-
-import os
-
-
-class NPZ:
-    """Ordered collection of NPZ file payloads.
-
-    Each entry in ``frames`` is a complete compressed ``.npz`` file stored
-    as raw bytes (produced by ``numpy.savez_compressed`` into a BytesIO).
-    ``save_to`` writes numbered files into a directory.
-    """
-
-    def __init__(self, frames: list[bytes]) -> None:
-        self.frames = frames
-
-    @property
-    def num_frames(self) -> int:
-        return len(self.frames)
-
-    def save_to(self, directory: str, prefix: str = "frame") -> str:
-        os.makedirs(directory, exist_ok=True)
-        for i, frame_bytes in enumerate(self.frames):
-            path = os.path.join(directory, f"{prefix}_{i:06d}.npz")
-            with open(path, "wb") as f:
-                f.write(frame_bytes)
-        return directory

comfy_api_sealed_worker/ply_types.py

@@ -1,97 +0,0 @@
-from __future__ import annotations
-
-import numpy as np
-
-
-class PLY:
-    """Point cloud payload for PLY file output.
-
-    Supports two schemas:
-    - Pointcloud: xyz positions with optional colors, confidence, view_id (ASCII format)
-    - Gaussian: raw binary PLY data built by producer nodes using plyfile (binary format)
-
-    When ``raw_data`` is provided, the object acts as an opaque binary PLY
-    carrier and ``save_to`` writes the bytes directly.
-    """
-
-    def __init__(
-        self,
-        points: np.ndarray | None = None,
-        colors: np.ndarray | None = None,
-        confidence: np.ndarray | None = None,
-        view_id: np.ndarray | None = None,
-        raw_data: bytes | None = None,
-    ) -> None:
-        self.raw_data = raw_data
-        if raw_data is not None:
-            self.points = None
-            self.colors = None
-            self.confidence = None
-            self.view_id = None
-            return
-        if points is None:
-            raise ValueError("Either points or raw_data must be provided")
-        if points.ndim != 2 or points.shape[1] != 3:
-            raise ValueError(f"points must be (N, 3), got {points.shape}")
-        self.points = np.ascontiguousarray(points, dtype=np.float32)
-        self.colors = np.ascontiguousarray(colors, dtype=np.float32) if colors is not None else None
-        self.confidence = np.ascontiguousarray(confidence, dtype=np.float32) if confidence is not None else None
-        self.view_id = np.ascontiguousarray(view_id, dtype=np.int32) if view_id is not None else None
-
-    @property
-    def is_gaussian(self) -> bool:
-        return self.raw_data is not None
-
-    @property
-    def num_points(self) -> int:
-        if self.points is not None:
-            return self.points.shape[0]
-        return 0
-
-    @staticmethod
-    def _to_numpy(arr, dtype):
-        if arr is None:
-            return None
-        if hasattr(arr, "numpy"):
-            arr = arr.cpu().numpy() if hasattr(arr, "cpu") else arr.numpy()
-        return np.ascontiguousarray(arr, dtype=dtype)
-
-    def save_to(self, path: str) -> str:
-        if self.raw_data is not None:
-            with open(path, "wb") as f:
-                f.write(self.raw_data)
-            return path
-        self.points = self._to_numpy(self.points, np.float32)
-        self.colors = self._to_numpy(self.colors, np.float32)
-        self.confidence = self._to_numpy(self.confidence, np.float32)
-        self.view_id = self._to_numpy(self.view_id, np.int32)
-        N = self.num_points
-        header_lines = [
-            "ply",
-            "format ascii 1.0",
-            f"element vertex {N}",
-            "property float x",
-            "property float y",
-            "property float z",
-        ]
-        if self.colors is not None:
-            header_lines += ["property uchar red", "property uchar green", "property uchar blue"]
-        if self.confidence is not None:
-            header_lines.append("property float confidence")
-        if self.view_id is not None:
-            header_lines.append("property int view_id")
-        header_lines.append("end_header")
-
-        with open(path, "w") as f:
-            f.write("\n".join(header_lines) + "\n")
-            for i in range(N):
-                parts = [f"{self.points[i, 0]} {self.points[i, 1]} {self.points[i, 2]}"]
-                if self.colors is not None:
-                    r, g, b = (self.colors[i] * 255).clip(0, 255).astype(np.uint8)
-                    parts.append(f"{r} {g} {b}")
-                if self.confidence is not None:
-                    parts.append(f"{self.confidence[i]}")
-                if self.view_id is not None:
-                    parts.append(f"{int(self.view_id[i])}")
-                f.write(" ".join(parts) + "\n")
-        return path

comfy_extras/nodes_save_npz.py

@@ -1,40 +0,0 @@
-import os
-
-import folder_paths
-from comfy_api.latest import io
-from comfy_api_sealed_worker.npz_types import NPZ
-
-
-class SaveNPZ(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="SaveNPZ",
-            display_name="Save NPZ",
-            category="3d",
-            is_output_node=True,
-            inputs=[
-                io.Npz.Input("npz"),
-                io.String.Input("filename_prefix", default="da3_streaming/ComfyUI"),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, npz: NPZ, filename_prefix: str) -> io.NodeOutput:
-        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
-            filename_prefix, folder_paths.get_output_directory()
-        )
-        batch_dir = os.path.join(full_output_folder, f"{filename}_{counter:05}")
-        os.makedirs(batch_dir, exist_ok=True)
-        filenames = []
-        for i, frame_bytes in enumerate(npz.frames):
-            f = f"frame_{i:06d}.npz"
-            with open(os.path.join(batch_dir, f), "wb") as fh:
-                fh.write(frame_bytes)
-            filenames.append(f)
-        return io.NodeOutput(ui={"npz_files": [{"folder": os.path.join(subfolder, f"{filename}_{counter:05}"), "count": len(filenames), "type": "output"}]})
-
-
-NODE_CLASS_MAPPINGS = {
-    "SaveNPZ": SaveNPZ,
-}

comfy_extras/nodes_save_ply.py

@@ -1,34 +0,0 @@
-import os
-
-import folder_paths
-from comfy_api.latest import io
-from comfy_api_sealed_worker.ply_types import PLY
-
-
-class SavePLY(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="SavePLY",
-            display_name="Save PLY",
-            category="3d",
-            is_output_node=True,
-            inputs=[
-                io.Ply.Input("ply"),
-                io.String.Input("filename_prefix", default="pointcloud/ComfyUI"),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, ply: PLY, filename_prefix: str) -> io.NodeOutput:
-        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(
-            filename_prefix, folder_paths.get_output_directory()
-        )
-        f = f"{filename}_{counter:05}_.ply"
-        ply.save_to(os.path.join(full_output_folder, f))
-        return io.NodeOutput(ui={"pointclouds": [{"filename": f, "subfolder": subfolder, "type": "output"}]})
-
-
-NODE_CLASS_MAPPINGS = {
-    "SavePLY": SavePLY,
-}

nodes.py

@@ -2459,8 +2459,6 @@ async def init_builtin_extra_nodes():
         "nodes_wan.py",
         "nodes_lotus.py",
         "nodes_hunyuan3d.py",
-        "nodes_save_ply.py",
-        "nodes_save_npz.py",
         "nodes_primitive.py",
         "nodes_cfg.py",
         "nodes_optimalsteps.py",