ComfyUI/node_helpers.py
Kohaku-Blueleaf 88d9168df0
Sync (#1)
* Allow disabling pe in flux code for some other models.

* Initial Hunyuan3Dv2 implementation.

Supports the multiview, mini, turbo models and VAEs.

* Fix orientation of hunyuan 3d model.

* A few fixes for the hunyuan3d models.

* Update frontend to 1.13 (#7331)

* Add backend primitive nodes (#7328)

* Add backend primitive nodes

* Add control after generate to int primitive

* Nodes to convert images to YUV and back.

Can be used to convert an image to black and white.

* Update frontend to 1.14 (#7343)

* Native LotusD Implementation (#7125)

* draft pass at a native comfy implementation of Lotus-D depth and normal est

* fix model_sampling kludges

* fix ruff

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Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>

* Automatically set the right sampling type for lotus.

* support output normal and lineart once (#7290)

* [nit] Format error strings (#7345)

* ComfyUI version v0.3.27

* Fallback to pytorch attention if sage attention fails.

* Add model merging node for WAN 2.1

* Add Hunyuan3D to readme.

* Support more float8 types.

* Add CFGZeroStar node.

Works on all models that use a negative prompt but is meant for rectified
flow models.

* Support the WAN 2.1 fun control models.

Use the new WanFunControlToVideo node.

* Add WanFunInpaintToVideo node for the Wan fun inpaint models.

* Update frontend to 1.14.6 (#7416)

Cherry-pick the fix: https://github.com/Comfy-Org/ComfyUI_frontend/pull/3252

* Don't error if wan concat image has extra channels.

* ltxv: fix preprocessing exception when compression is 0. (#7431)

* Remove useless code.

* Fix latent composite node not working when source has alpha.

* Fix alpha channel mismatch on destination in ImageCompositeMasked

* Add option to store TE in bf16 (#7461)

* User missing (#7439)

* Ensuring a 401 error is returned when user data is not found in multi-user context.

* Returning a 401 error when provided comfy-user does not exists on server side.

* Fix comment.

This function does not support quads.

* MLU memory optimization (#7470)

Co-authored-by: huzhan <huzhan@cambricon.com>

* Fix alpha image issue in more nodes.

* Fix problem.

* Disable partial offloading of audio VAE.

* Add activations_shape info in UNet models (#7482)

* Add activations_shape info in UNet models

* activations_shape should be a list

* Support 512 siglip model.

* Show a proper error to the user when a vision model file is invalid.

* Support the wan fun reward loras.

---------

Co-authored-by: comfyanonymous <comfyanonymous@protonmail.com>
Co-authored-by: Chenlei Hu <hcl@comfy.org>
Co-authored-by: thot experiment <94414189+thot-experiment@users.noreply.github.com>
Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Co-authored-by: Terry Jia <terryjia88@gmail.com>
Co-authored-by: Michael Kupchick <michael@lightricks.com>
Co-authored-by: BVH <82035780+bvhari@users.noreply.github.com>
Co-authored-by: Laurent Erignoux <lerignoux@gmail.com>
Co-authored-by: BiologicalExplosion <49753622+BiologicalExplosion@users.noreply.github.com>
Co-authored-by: huzhan <huzhan@cambricon.com>
Co-authored-by: Raphael Walker <slickytail.mc@gmail.com>
2025-04-08 18:38:44 +08:00

55 lines
1.5 KiB
Python

import hashlib
import torch
from comfy.cli_args import args
from PIL import ImageFile, UnidentifiedImageError
def conditioning_set_values(conditioning, values={}):
c = []
for t in conditioning:
n = [t[0], t[1].copy()]
for k in values:
n[1][k] = values[k]
c.append(n)
return c
def pillow(fn, arg):
prev_value = None
try:
x = fn(arg)
except (OSError, UnidentifiedImageError, ValueError): #PIL issues #4472 and #2445, also fixes ComfyUI issue #3416
prev_value = ImageFile.LOAD_TRUNCATED_IMAGES
ImageFile.LOAD_TRUNCATED_IMAGES = True
x = fn(arg)
finally:
if prev_value is not None:
ImageFile.LOAD_TRUNCATED_IMAGES = prev_value
return x
def hasher():
hashfuncs = {
"md5": hashlib.md5,
"sha1": hashlib.sha1,
"sha256": hashlib.sha256,
"sha512": hashlib.sha512
}
return hashfuncs[args.default_hashing_function]
def string_to_torch_dtype(string):
if string == "fp32":
return torch.float32
if string == "fp16":
return torch.float16
if string == "bf16":
return torch.bfloat16
def image_alpha_fix(destination, source):
if destination.shape[-1] < source.shape[-1]:
source = source[...,:destination.shape[-1]]
elif destination.shape[-1] > source.shape[-1]:
destination = torch.nn.functional.pad(destination, (0, 1))
destination[..., -1] = 1.0
return destination, source