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Author SHA1 Message Date
Alexis Rolland
dc413cafca
Merge 0a5f6e15bc into 97f58baaaf 2026-05-01 11:01:57 +08:00
Jedrzej Kosinski
97f58baaaf
Add alexisrolland and rattus128 as code owners (#13648)
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2026-04-30 21:49:31 -04:00
Daxiong (Lin)
e8e8fee224
chore: update workflow templates to v0.9.65 (#13644) 2026-04-30 18:14:28 -07:00
Rainer
e9c311b245
OneTainer ERNIE LoRA support (#13640) 2026-04-30 19:33:41 -04:00
comfyanonymous
e6e0936128
Load other jpeg formats without taking so much memory. (#13642) 2026-04-30 19:33:09 -04:00
Alexander Piskun
b633244635
[Partner Nodes] ByteDance: virtual portrait library for regular images (#13638)
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* feat(api-nodes-bytedance): use the virtual portrait library for regular images

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* fix: include shape in image dedup hash

Signed-off-by: bigcat88 <bigcat88@icloud.com>

---------

Signed-off-by: bigcat88 <bigcat88@icloud.com>
2026-04-30 11:49:08 -07:00
Alexis Rolland
0a5f6e15bc Fix issue blend images with alpha 2026-04-29 17:18:17 +08:00
7 changed files with 50 additions and 9 deletions

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@ -1,2 +1,2 @@
# Admins
* @comfyanonymous @kosinkadink @guill
* @comfyanonymous @kosinkadink @guill @alexisrolland @rattus128

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@ -342,6 +342,12 @@ def model_lora_keys_unet(model, key_map={}):
key_map["base_model.model.{}".format(key_lora)] = k # Official base model loras
key_map["lycoris_{}".format(key_lora.replace(".", "_"))] = k # LyCORIS/LoKR format
if isinstance(model, comfy.model_base.ErnieImage):
for k in sdk:
if k.startswith("diffusion_model.") and k.endswith(".weight"):
key_lora = k[len("diffusion_model."):-len(".weight")]
key_map["transformer.{}".format(key_lora)] = k
return key_map

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@ -290,7 +290,7 @@ class VideoFromFile(VideoInput):
alphas = []
alpha_channel = True
break
if frame.format.name in ("yuvj420p", "rgb24", "rgba", "pal8"):
if frame.format.name in ("yuvj420p", "yuvj422p", "yuvj444p", "rgb24", "rgba", "pal8"):
process_image_format = lambda a: a.float() / 255.0
if alpha_channel:
image_format = 'rgba'

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@ -157,6 +157,11 @@ class SeedanceCreateAssetResponse(BaseModel):
asset_id: str = Field(...)
class SeedanceVirtualLibraryCreateAssetRequest(BaseModel):
url: str = Field(..., description="Publicly accessible URL of the image asset to upload.")
hash: str = Field(..., description="Dedup key. Re-submitting the same hash returns the existing asset id.")
# Dollars per 1K tokens, keyed by (model_id, has_video_input).
SEEDANCE2_PRICE_PER_1K_TOKENS = {
("dreamina-seedance-2-0-260128", False): 0.007,

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@ -1,3 +1,4 @@
import hashlib
import logging
import math
import re
@ -20,6 +21,7 @@ from comfy_api_nodes.apis.bytedance import (
SeedanceCreateAssetResponse,
SeedanceCreateVisualValidateSessionResponse,
SeedanceGetVisualValidateSessionResponse,
SeedanceVirtualLibraryCreateAssetRequest,
Seedream4Options,
Seedream4TaskCreationRequest,
TaskAudioContent,
@ -271,6 +273,30 @@ async def _wait_for_asset_active(cls: type[IO.ComfyNode], asset_id: str, group_i
)
async def _seedance_virtual_library_upload_image_asset(
cls: type[IO.ComfyNode],
image: torch.Tensor,
*,
wait_label: str = "Uploading image",
) -> str:
"""Upload an image into the caller's per-customer Seedance virtual library."""
public_url = await upload_image_to_comfyapi(cls, image, wait_label=wait_label)
normalized = image.detach().cpu().contiguous().to(torch.float32)
digest = hashlib.sha256()
digest.update(str(tuple(normalized.shape)).encode("utf-8"))
digest.update(b"\0")
digest.update(normalized.numpy().tobytes())
image_hash = digest.hexdigest()
create_resp = await sync_op(
cls,
ApiEndpoint(path="/proxy/seedance/virtual-library/assets", method="POST"),
response_model=SeedanceCreateAssetResponse,
data=SeedanceVirtualLibraryCreateAssetRequest(url=public_url, hash=image_hash),
)
await _wait_for_asset_active(cls, create_resp.asset_id, group_id="virtual-library")
return f"asset://{create_resp.asset_id}"
def _seedance2_price_extractor(model_id: str, has_video_input: bool):
"""Returns a price_extractor closure for Seedance 2.0 poll_op."""
rate = SEEDANCE2_PRICE_PER_1K_TOKENS.get((model_id, has_video_input))
@ -1507,7 +1533,9 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
if first_frame_asset_id:
first_frame_url = image_assets[first_frame_asset_id]
else:
first_frame_url = await upload_image_to_comfyapi(cls, first_frame, wait_label="Uploading first frame.")
first_frame_url = await _seedance_virtual_library_upload_image_asset(
cls, first_frame, wait_label="Uploading first frame."
)
content: list[TaskTextContent | TaskImageContent] = [
TaskTextContent(text=model["prompt"]),
@ -1527,7 +1555,9 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
content.append(
TaskImageContent(
image_url=TaskImageContentUrl(
url=await upload_image_to_comfyapi(cls, last_frame, wait_label="Uploading last frame.")
url=await _seedance_virtual_library_upload_image_asset(
cls, last_frame, wait_label="Uploading last frame."
)
),
role="last_frame",
),
@ -1805,9 +1835,9 @@ class ByteDance2ReferenceNode(IO.ComfyNode):
content.append(
TaskImageContent(
image_url=TaskImageContentUrl(
url=await upload_image_to_comfyapi(
url=await _seedance_virtual_library_upload_image_asset(
cls,
image=reference_images[key],
reference_images[key],
wait_label=f"Uploading image {i}",
),
),

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@ -86,6 +86,6 @@ 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
source = torch.nn.functional.pad(source, (0, 1))
source[..., -1] = 1.0
return destination, source

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@ -1,5 +1,5 @@
comfyui-frontend-package==1.42.15
comfyui-workflow-templates==0.9.63
comfyui-workflow-templates==0.9.65
comfyui-embedded-docs==0.4.4
torch
torchsde