mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-02-11 14:02:37 +08:00
0ef5557d6a
bugfix: fix typo in apply_directory for custom_nodes_directory
allow for PATH style ';' delimited custom_node directories.
change delimiter type for seperate folders per platform.
feat(API-nodes): move Rodin3D nodes to new client; removed old api client.py (#10645)
Fix qwen controlnet regression. (#10657)
Enable pinned memory by default on Nvidia. (#10656)
Removed the --fast pinned_memory flag.
You can use --disable-pinned-memory to disable it. Please report if it
causes any issues.
Pinned mem also seems to work on AMD. (#10658)
Remove environment variable.
Removed environment variable fallback for custom nodes directory.
Update documentation for custom nodes directory
Clarified documentation on custom nodes directory argument, removed documentation on environment variable
Clarify release cycle. (#10667)
Tell users they need to upload their logs in bug reports. (#10671)
mm: guard against double pin and unpin explicitly (#10672)
As commented, if you let cuda be the one to detect double pin/unpinning
it actually creates an asyc GPU error.
Only unpin tensor if it was pinned by ComfyUI (#10677)
Make ScaleROPE node work on Flux. (#10686)
Add logging for model unloading. (#10692)
Unload weights if vram usage goes up between runs. (#10690)
ops: Put weight cast on the offload stream (#10697)
This needs to be on the offload stream. This reproduced a black screen
with low resolution images on a slow bus when using FP8.
Update CI workflow to remove dead macOS runner. (#10704)
* Update CI workflow to remove dead macOS runner.
* revert
* revert
Don't pin tensor if not a torch.nn.parameter.Parameter (#10718)
Update README.md for Intel Arc GPU installation, remove IPEX (#10729)
IPEX is no longer needed for Intel Arc GPUs. Removing instruction to setup ipex.
mm/mp: always unload re-used but modified models (#10724)
The partial unloader path in model re-use flow skips straight to the
actual unload without any check of the patching UUID. This means that
if you do an upscale flow with a model patch on an existing model, it
will not apply your patchings.
Fix by delaying the partial_unload until after the uuid checks. This
is done by making partial_unload a model of partial_load where extra_mem
is -ve.
qwen: reduce VRAM usage (#10725)
Clean up a bunch of stacked and no-longer-needed tensors on the QWEN
VRAM peak (currently FFN).
With this I go from OOMing at B=37x1328x1328 to being able to
succesfully run B=47 (RTX5090).
Update Python 3.14 compatibility notes in README (#10730)
Quantized Ops fixes (#10715)
* offload support, bug fixes, remove mixins
* add readme
add PR template for API-Nodes (#10736)
feat: add create_time dict to prompt field in /history and /queue (#10741)
flux: reduce VRAM usage (#10737)
Cleanup a bunch of stack tensors on Flux. This take me from B=19 to B=22
for 1600x1600 on RTX5090.
Better instructions for the portable. (#10743)
Use same code for chroma and flux blocks so that optimizations are shared. (#10746)
Fix custom nodes import error. (#10747)
This should fix the import errors but will break if the custom nodes actually try to use the class.
revert import reordering
revert imports pt 2
Add left padding support to tokenizers. (#10753)
chore(api-nodes): mark OpenAIDalle2 and OpenAIDalle3 nodes as deprecated (#10757)
Revert "chore(api-nodes): mark OpenAIDalle2 and OpenAIDalle3 nodes as deprecated (#10757)" (#10759)
This reverts commit 9a02382568.
Change ROCm nightly install command to 7.1 (#10764)
521 lines
16 KiB
Python
521 lines
16 KiB
Python
"""
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ComfyUI X Rodin3D(Deemos) API Nodes
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Rodin API docs: https://developer.hyper3d.ai/
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"""
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from inspect import cleandoc
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import folder_paths as comfy_paths
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import os
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import logging
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import math
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from typing import Optional
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from io import BytesIO
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from typing_extensions import override
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from PIL import Image
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from comfy_api_nodes.apis.rodin_api import (
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Rodin3DGenerateRequest,
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Rodin3DGenerateResponse,
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Rodin3DCheckStatusRequest,
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Rodin3DCheckStatusResponse,
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Rodin3DDownloadRequest,
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Rodin3DDownloadResponse,
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JobStatus,
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)
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from comfy_api_nodes.util import (
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sync_op,
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poll_op,
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ApiEndpoint,
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download_url_to_bytesio,
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)
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from comfy_api.latest import ComfyExtension, IO
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COMMON_PARAMETERS = [
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IO.Int.Input(
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"Seed",
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default=0,
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min=0,
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max=65535,
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display_mode=IO.NumberDisplay.number,
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optional=True,
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),
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IO.Combo.Input("Material_Type", options=["PBR", "Shaded"], default="PBR", optional=True),
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IO.Combo.Input(
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"Polygon_count",
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options=["4K-Quad", "8K-Quad", "18K-Quad", "50K-Quad", "200K-Triangle"],
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default="18K-Quad",
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optional=True,
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),
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]
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def get_quality_mode(poly_count):
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polycount = poly_count.split("-")
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poly = polycount[1]
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count = polycount[0]
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if poly == "Triangle":
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mesh_mode = "Raw"
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elif poly == "Quad":
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mesh_mode = "Quad"
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else:
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mesh_mode = "Quad"
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if count == "4K":
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quality_override = 4000
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elif count == "8K":
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quality_override = 8000
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elif count == "18K":
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quality_override = 18000
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elif count == "50K":
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quality_override = 50000
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elif count == "2K":
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quality_override = 2000
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elif count == "20K":
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quality_override = 20000
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elif count == "150K":
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quality_override = 150000
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elif count == "500K":
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quality_override = 500000
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else:
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quality_override = 18000
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return mesh_mode, quality_override
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def tensor_to_filelike(tensor, max_pixels: int = 2048*2048):
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"""
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Converts a PyTorch tensor to a file-like object.
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Args:
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- tensor (torch.Tensor): A tensor representing an image of shape (H, W, C)
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where C is the number of channels (3 for RGB), H is height, and W is width.
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Returns:
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- io.BytesIO: A file-like object containing the image data.
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"""
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array = tensor.cpu().numpy()
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array = (array * 255).astype('uint8')
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image = Image.fromarray(array, 'RGB')
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original_width, original_height = image.size
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original_pixels = original_width * original_height
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if original_pixels > max_pixels:
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scale = math.sqrt(max_pixels / original_pixels)
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new_width = int(original_width * scale)
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new_height = int(original_height * scale)
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else:
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new_width, new_height = original_width, original_height
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if new_width != original_width or new_height != original_height:
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image = image.resize((new_width, new_height), Image.Resampling.LANCZOS)
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img_byte_arr = BytesIO()
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image.save(img_byte_arr, format='PNG') # PNG is used for lossless compression
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img_byte_arr.seek(0)
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return img_byte_arr
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async def create_generate_task(
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cls: type[IO.ComfyNode],
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images=None,
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seed=1,
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material="PBR",
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quality_override=18000,
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tier="Regular",
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mesh_mode="Quad",
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ta_pose: bool = False,
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):
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if images is None:
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raise Exception("Rodin 3D generate requires at least 1 image.")
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if len(images) > 5:
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raise Exception("Rodin 3D generate requires up to 5 image.")
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response = await sync_op(
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cls,
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ApiEndpoint(path="/proxy/rodin/api/v2/rodin", method="POST"),
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response_model=Rodin3DGenerateResponse,
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data=Rodin3DGenerateRequest(
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seed=seed,
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tier=tier,
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material=material,
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quality_override=quality_override,
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mesh_mode=mesh_mode,
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TAPose=ta_pose,
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),
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files=[
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(
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"images",
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open(image, "rb") if isinstance(image, str) else tensor_to_filelike(image)
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)
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for image in images if image is not None
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],
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content_type="multipart/form-data",
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)
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if hasattr(response, "error"):
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error_message = f"Rodin3D Create 3D generate Task Failed. Message: {response.message}, error: {response.error}"
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logging.error(error_message)
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raise Exception(error_message)
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logging.info("[ Rodin3D API - Submit Jobs ] Submit Generate Task Success!")
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subscription_key = response.jobs.subscription_key
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task_uuid = response.uuid
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logging.info("[ Rodin3D API - Submit Jobs ] UUID: %s", task_uuid)
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return task_uuid, subscription_key
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def check_rodin_status(response: Rodin3DCheckStatusResponse) -> str:
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all_done = all(job.status == JobStatus.Done for job in response.jobs)
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status_list = [str(job.status) for job in response.jobs]
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logging.info("[ Rodin3D API - CheckStatus ] Generate Status: %s", status_list)
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if any(job.status == JobStatus.Failed for job in response.jobs):
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logging.error("[ Rodin3D API - CheckStatus ] Generate Failed: %s, Please try again.", status_list)
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raise Exception("[ Rodin3D API ] Generate Failed, Please Try again.")
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if all_done:
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return "DONE"
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return "Generating"
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def extract_progress(response: Rodin3DCheckStatusResponse) -> Optional[int]:
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if not response.jobs:
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return None
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completed_count = sum(1 for job in response.jobs if job.status == JobStatus.Done)
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return int((completed_count / len(response.jobs)) * 100)
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async def poll_for_task_status(subscription_key: str, cls: type[IO.ComfyNode]) -> Rodin3DCheckStatusResponse:
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logging.info("[ Rodin3D API - CheckStatus ] Generate Start!")
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return await poll_op(
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cls,
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ApiEndpoint(path="/proxy/rodin/api/v2/status", method="POST"),
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response_model=Rodin3DCheckStatusResponse,
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data=Rodin3DCheckStatusRequest(subscription_key=subscription_key),
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status_extractor=check_rodin_status,
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progress_extractor=extract_progress,
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)
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async def get_rodin_download_list(uuid: str, cls: type[IO.ComfyNode]) -> Rodin3DDownloadResponse:
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logging.info("[ Rodin3D API - Downloading ] Generate Successfully!")
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return await sync_op(
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cls,
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ApiEndpoint(path="/proxy/rodin/api/v2/download", method="POST"),
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response_model=Rodin3DDownloadResponse,
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data=Rodin3DDownloadRequest(task_uuid=uuid),
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monitor_progress=False,
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)
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async def download_files(url_list, task_uuid: str):
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result_folder_name = f"Rodin3D_{task_uuid}"
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save_path = os.path.join(comfy_paths.get_output_directory(), result_folder_name)
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os.makedirs(save_path, exist_ok=True)
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model_file_path = None
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for i in url_list.list:
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file_path = os.path.join(save_path, i.name)
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if file_path.endswith(".glb"):
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model_file_path = os.path.join(result_folder_name, i.name)
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await download_url_to_bytesio(i.url, file_path)
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return model_file_path
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class Rodin3D_Regular(IO.ComfyNode):
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"""Generate 3D Assets using Rodin API"""
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@classmethod
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def define_schema(cls) -> IO.Schema:
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return IO.Schema(
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node_id="Rodin3D_Regular",
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display_name="Rodin 3D Generate - Regular Generate",
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category="api node/3d/Rodin",
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description=cleandoc(cls.__doc__ or ""),
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inputs=[
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IO.Image.Input("Images"),
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*COMMON_PARAMETERS,
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],
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outputs=[IO.String.Output(display_name="3D Model Path")],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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)
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@classmethod
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async def execute(
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cls,
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Images,
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Seed,
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Material_Type,
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Polygon_count,
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) -> IO.NodeOutput:
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tier = "Regular"
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num_images = Images.shape[0]
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m_images = []
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for i in range(num_images):
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m_images.append(Images[i])
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mesh_mode, quality_override = get_quality_mode(Polygon_count)
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task_uuid, subscription_key = await create_generate_task(
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cls,
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images=m_images,
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seed=Seed,
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material=Material_Type,
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quality_override=quality_override,
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tier=tier,
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mesh_mode=mesh_mode,
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)
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await poll_for_task_status(subscription_key, cls)
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download_list = await get_rodin_download_list(task_uuid, cls)
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model = await download_files(download_list, task_uuid)
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return IO.NodeOutput(model)
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class Rodin3D_Detail(IO.ComfyNode):
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"""Generate 3D Assets using Rodin API"""
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@classmethod
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def define_schema(cls) -> IO.Schema:
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return IO.Schema(
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node_id="Rodin3D_Detail",
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display_name="Rodin 3D Generate - Detail Generate",
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category="api node/3d/Rodin",
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description=cleandoc(cls.__doc__ or ""),
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inputs=[
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IO.Image.Input("Images"),
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*COMMON_PARAMETERS,
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],
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outputs=[IO.String.Output(display_name="3D Model Path")],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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)
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@classmethod
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async def execute(
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cls,
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Images,
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Seed,
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Material_Type,
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Polygon_count,
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) -> IO.NodeOutput:
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tier = "Detail"
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num_images = Images.shape[0]
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m_images = []
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for i in range(num_images):
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m_images.append(Images[i])
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mesh_mode, quality_override = get_quality_mode(Polygon_count)
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task_uuid, subscription_key = await create_generate_task(
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cls,
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images=m_images,
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seed=Seed,
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material=Material_Type,
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quality_override=quality_override,
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tier=tier,
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mesh_mode=mesh_mode,
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)
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await poll_for_task_status(subscription_key, cls)
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download_list = await get_rodin_download_list(task_uuid, cls)
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model = await download_files(download_list, task_uuid)
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return IO.NodeOutput(model)
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class Rodin3D_Smooth(IO.ComfyNode):
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"""Generate 3D Assets using Rodin API"""
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@classmethod
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def define_schema(cls) -> IO.Schema:
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return IO.Schema(
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node_id="Rodin3D_Smooth",
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display_name="Rodin 3D Generate - Smooth Generate",
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category="api node/3d/Rodin",
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description=cleandoc(cls.__doc__ or ""),
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inputs=[
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IO.Image.Input("Images"),
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*COMMON_PARAMETERS,
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],
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outputs=[IO.String.Output(display_name="3D Model Path")],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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)
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@classmethod
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async def execute(
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cls,
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Images,
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Seed,
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Material_Type,
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Polygon_count,
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) -> IO.NodeOutput:
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num_images = Images.shape[0]
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m_images = []
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for i in range(num_images):
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m_images.append(Images[i])
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mesh_mode, quality_override = get_quality_mode(Polygon_count)
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task_uuid, subscription_key = await create_generate_task(
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cls,
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images=m_images,
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seed=Seed,
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material=Material_Type,
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quality_override=quality_override,
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tier="Smooth",
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mesh_mode=mesh_mode,
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)
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await poll_for_task_status(subscription_key, cls)
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download_list = await get_rodin_download_list(task_uuid, cls)
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model = await download_files(download_list, task_uuid)
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return IO.NodeOutput(model)
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class Rodin3D_Sketch(IO.ComfyNode):
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"""Generate 3D Assets using Rodin API"""
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@classmethod
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def define_schema(cls) -> IO.Schema:
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return IO.Schema(
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node_id="Rodin3D_Sketch",
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display_name="Rodin 3D Generate - Sketch Generate",
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category="api node/3d/Rodin",
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description=cleandoc(cls.__doc__ or ""),
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inputs=[
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IO.Image.Input("Images"),
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IO.Int.Input(
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"Seed",
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default=0,
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min=0,
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max=65535,
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display_mode=IO.NumberDisplay.number,
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optional=True,
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),
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],
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outputs=[IO.String.Output(display_name="3D Model Path")],
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hidden=[
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IO.Hidden.auth_token_comfy_org,
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IO.Hidden.api_key_comfy_org,
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IO.Hidden.unique_id,
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],
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is_api_node=True,
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)
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@classmethod
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async def execute(
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cls,
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Images,
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Seed,
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) -> IO.NodeOutput:
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num_images = Images.shape[0]
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m_images = []
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for i in range(num_images):
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m_images.append(Images[i])
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task_uuid, subscription_key = await create_generate_task(
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cls,
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images=m_images,
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seed=Seed,
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material="PBR",
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quality_override=18000,
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tier="Sketch",
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mesh_mode="Quad",
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)
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await poll_for_task_status(subscription_key, cls)
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download_list = await get_rodin_download_list(task_uuid, cls)
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model = await download_files(download_list, task_uuid)
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return IO.NodeOutput(model)
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|
|
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class Rodin3D_Gen2(IO.ComfyNode):
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"""Generate 3D Assets using Rodin API"""
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@classmethod
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def define_schema(cls) -> IO.Schema:
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return IO.Schema(
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node_id="Rodin3D_Gen2",
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display_name="Rodin 3D Generate - Gen-2 Generate",
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category="api node/3d/Rodin",
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description=cleandoc(cls.__doc__ or ""),
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inputs=[
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IO.Image.Input("Images"),
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IO.Int.Input(
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"Seed",
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default=0,
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min=0,
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max=65535,
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display_mode=IO.NumberDisplay.number,
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optional=True,
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),
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|
IO.Combo.Input("Material_Type", options=["PBR", "Shaded"], default="PBR", optional=True),
|
|
IO.Combo.Input(
|
|
"Polygon_count",
|
|
options=["4K-Quad", "8K-Quad", "18K-Quad", "50K-Quad", "2K-Triangle", "20K-Triangle", "150K-Triangle", "500K-Triangle"],
|
|
default="500K-Triangle",
|
|
optional=True,
|
|
),
|
|
IO.Boolean.Input("TAPose", default=False),
|
|
],
|
|
outputs=[IO.String.Output(display_name="3D Model Path")],
|
|
hidden=[
|
|
IO.Hidden.auth_token_comfy_org,
|
|
IO.Hidden.api_key_comfy_org,
|
|
IO.Hidden.unique_id,
|
|
],
|
|
is_api_node=True,
|
|
)
|
|
|
|
@classmethod
|
|
async def execute(
|
|
cls,
|
|
Images,
|
|
Seed,
|
|
Material_Type,
|
|
Polygon_count,
|
|
TAPose,
|
|
) -> IO.NodeOutput:
|
|
tier = "Gen-2"
|
|
num_images = Images.shape[0]
|
|
m_images = []
|
|
for i in range(num_images):
|
|
m_images.append(Images[i])
|
|
mesh_mode, quality_override = get_quality_mode(Polygon_count)
|
|
task_uuid, subscription_key = await create_generate_task(
|
|
cls,
|
|
images=m_images,
|
|
seed=Seed,
|
|
material=Material_Type,
|
|
quality_override=quality_override,
|
|
tier=tier,
|
|
mesh_mode=mesh_mode,
|
|
ta_pose=TAPose,
|
|
)
|
|
await poll_for_task_status(subscription_key, cls)
|
|
download_list = await get_rodin_download_list(task_uuid, cls)
|
|
model = await download_files(download_list, task_uuid)
|
|
|
|
return IO.NodeOutput(model)
|
|
|
|
|
|
class Rodin3DExtension(ComfyExtension):
|
|
@override
|
|
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
|
return [
|
|
Rodin3D_Regular,
|
|
Rodin3D_Detail,
|
|
Rodin3D_Smooth,
|
|
Rodin3D_Sketch,
|
|
Rodin3D_Gen2,
|
|
]
|
|
|
|
|
|
async def comfy_entrypoint() -> Rodin3DExtension:
|
|
return Rodin3DExtension()
|