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[Partner Nodes] feat(Bria): add GenFill, Eraser, Expand and Increase Resolution nodes (#15572) 

Signed-off-by: Alexander Piskun <bigcat88@icloud.com>
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Alexander Piskun 2026-08-13 19:18:12 +03:00 committed by GitHub
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commit e535e59e13
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95
comfy_api_nodes/apis/bria.py
View File

@ -57,6 +57,81 @@ class BriaRemoveBackgroundRequest(BaseModel):
seed: int = Field(...)
class BriaGenFillRequest(BaseModel):
image: str = Field(...)
mask: str = Field(
...,
description="Binary mask defining the region to fill: white (255) pixels are generated, "
"black (0) pixels are preserved. Must have the same aspect ratio as the image.",
)
prompt: str = Field(...)
negative_prompt: str | None = Field(None)
refine_prompt: bool = Field(True)
seed: int = Field(...)
prompt_content_moderation: bool = Field(False, description="If true, returns 422 on prompt moderation failure.")
visual_input_content_moderation: bool = Field(
False, description="If true, returns 422 on image or mask moderation failure."
)
visual_output_content_moderation: bool = Field(
False, description="If true, returns 422 on visual output moderation failure."
)
class BriaEraseRequest(BaseModel):
image: str = Field(...)
mask: str = Field(
...,
description="Binary mask defining the region to erase: white (255) pixels are removed, "
"black (0) pixels are preserved. Must have the same aspect ratio as the image.",
)
mask_type: str = Field("manual", description="'manual' for hand-drawn masks, 'automatic' for segmentation masks.")
visual_input_content_moderation: bool = Field(
False, description="If true, returns 422 on image or mask moderation failure."
)
visual_output_content_moderation: bool = Field(
False, description="If true, returns 422 on visual output moderation failure."
)
class BriaExpandRequest(BaseModel):
image: str = Field(...)
aspect_ratio: str | float | None = Field(
None,
description="Target ratio: a preset string (1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9) "
"or a float between 0.5 and 3.0. When set, the canvas/placement fields are ignored.",
)
canvas_size: list[int] | None = Field(None, description="Output canvas [width, height]; area up to 5000x5000.")
original_image_size: list[int] | None = Field(
None, description="Size [width, height] of the original image inside the canvas."
)
original_image_location: list[int] | None = Field(
None,
description="Top-left corner [x, y] of the original image inside the canvas; "
"values may fall outside the canvas, cropping the image.",
)
prompt: str | None = Field(None, description="If omitted, Bria auto-generates a prompt from the image.")
negative_prompt: str | None = Field(None)
seed: int = Field(...)
prompt_content_moderation: bool = Field(False, description="If true, returns 422 on prompt moderation failure.")
visual_input_content_moderation: bool = Field(
False, description="If true, returns 422 on image moderation failure."
)
visual_output_content_moderation: bool = Field(
False, description="If true, returns 422 on visual output moderation failure."
)
class BriaIncreaseResolutionRequest(BaseModel):
image: str = Field(...)
desired_increase: int = Field(..., description="Resolution multiplier, 2 or 4.")
visual_input_content_moderation: bool = Field(
False, description="If true, returns 422 on image moderation failure."
)
visual_output_content_moderation: bool = Field(
False, description="If true, returns 422 on visual output moderation failure."
)
class BriaStatusResponse(BaseModel):
request_id: str = Field(...)
status_url: str = Field(...)
@ -72,6 +147,26 @@ class BriaRemoveBackgroundResponse(BaseModel):
result: BriaRemoveBackgroundResult | None = Field(None)
class BriaImageResult(BaseModel):
image_url: str = Field(...)
class BriaImageResultResponse(BaseModel):
status: str = Field(...)
result: BriaImageResult | None = Field(None)
class BriaExpandResult(BaseModel):
image_url: str = Field(...)
prompt: str | None = Field(None)
seed: int | None = Field(None)
class BriaExpandResponse(BaseModel):
status: str = Field(...)
result: BriaExpandResult | None = Field(None)
class BriaImageEditResult(BaseModel):
structured_prompt: str = Field(...)
image_url: str = Field(...)

524
comfy_api_nodes/nodes_bria.py
View File

@ -6,7 +6,13 @@ from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension, Input
from comfy_api_nodes.apis.bria import (
BriaEditImageRequest,
BriaEraseRequest,
BriaExpandRequest,
BriaExpandResponse,
BriaGenFillRequest,
BriaImageEditResponse,
BriaImageResultResponse,
BriaIncreaseResolutionRequest,
BriaRemoveBackgroundRequest,
BriaRemoveBackgroundResponse,
BriaRemoveVideoBackgroundRequest,
@ -21,13 +27,30 @@ from comfy_api_nodes.util import (
convert_mask_to_image,
download_url_to_image_tensor,
download_url_to_video_output,
downscale_image_tensor_by_max_side,
get_image_dimensions,
poll_op,
sync_op,
upload_image_to_comfyapi,
upload_video_to_comfyapi,
validate_string,
validate_video_duration,
)
BRIA_MAX_OUTPUT_SIDE = 8192
BRIA_MIN_RATIO = 0.5
BRIA_MAX_RATIO = 3.0
BRIA_MIN_SHORT_SIDE = 224
def _upscaled_output_side(height: int, width: int, multiplier: int) -> int:
prescale = max(1.0, BRIA_MIN_SHORT_SIDE / min(height, width))
return round(max(height, width) * prescale * multiplier)
def _smallest_output_side(height: int, width: int, multiplier: int) -> int:
return round(max(height, width) / min(height, width) * BRIA_MIN_SHORT_SIDE * multiplier)
class BriaImageEditNode(IO.ComfyNode):
@ -243,6 +266,503 @@ class BriaRemoveImageBackground(IO.ComfyNode):
return IO.NodeOutput(await download_url_to_image_tensor(response.result.image_url))
def _mask_to_binary_image(mask: Input.Image, action: str) -> torch.Tensor:
binary = (mask > 0.5).float()
if not binary.any():
raise ValueError(
f"The mask is empty, so there is nothing to {action}. Masks are binarized at 50%: "
f"areas painted at less than half opacity are ignored."
)
return convert_mask_to_image(binary)
def _validate_mask_aspect_ratio(image: Input.Image, mask: Input.Image) -> None:
ih, iw = image.shape[1], image.shape[2]
mh, mw = mask.shape[-2], mask.shape[-1]
if abs(iw * mh - ih * mw) > 0.01 * ih * mw:
raise ValueError(f"Mask must have the same aspect ratio as the image: image is {iw}x{ih}, mask is {mw}x{mh}.")
class BriaGenFill(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="BriaGenFill",
display_name="Bria Generative Fill",
category="partner/image/Bria",
description="Generate objects or scenery inside a masked region of an image using Bria.",
inputs=[
IO.Image.Input("image"),
IO.Mask.Input(
"mask",
tooltip="White areas are filled with generated content, black areas are preserved. "
"The mask is binarized before sending, so partially painted areas count as white. "
"Must have the same aspect ratio as the image.",
),
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Description of what to generate inside the masked region.",
),
IO.String.Input("negative_prompt", multiline=True, default=""),
IO.Boolean.Input(
"refine_prompt",
default=True,
tooltip="Automatically adjust the prompt for better results; "
"disable to use the prompt exactly as written.",
),
IO.Int.Input(
"seed",
default=42,
min=1,
max=2147483647,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
),
IO.DynamicCombo.Input(
"moderation",
options=[
IO.DynamicCombo.Option("false", []),
IO.DynamicCombo.Option(
"true",
[
IO.Boolean.Input("prompt_content_moderation", default=False),
IO.Boolean.Input("visual_input_moderation", default=False),
IO.Boolean.Input("visual_output_moderation", default=False),
],
),
],
tooltip="Moderation settings",
),
],
outputs=[IO.Image.Output()],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
expr="""{"type":"usd","usd":0.0429}""",
),
)
@classmethod
async def execute(
cls,
image: Input.Image,
mask: Input.Image,
prompt: str,
negative_prompt: str,
refine_prompt: bool,
seed: int,
moderation: InputModerationSettings,
) -> IO.NodeOutput:
validate_string(prompt, min_length=1)
_validate_mask_aspect_ratio(image, mask)
mask_image = _mask_to_binary_image(mask, "fill")
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/bria/v2/image/edit/gen_fill", method="POST"),
data=BriaGenFillRequest(
image=await upload_image_to_comfyapi(cls, image, total_pixels=None, wait_label="Uploading image"),
mask=await upload_image_to_comfyapi(
cls, mask_image, total_pixels=None, wait_label="Uploading mask"
),
prompt=prompt,
negative_prompt=negative_prompt if negative_prompt else None,
refine_prompt=refine_prompt,
seed=seed,
prompt_content_moderation=moderation.get("prompt_content_moderation", False),
visual_input_content_moderation=moderation.get("visual_input_moderation", False),
visual_output_content_moderation=moderation.get("visual_output_moderation", False),
),
response_model=BriaStatusResponse,
)
response = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/bria/v2/status/{response.request_id}"),
status_extractor=lambda r: r.status,
response_model=BriaImageResultResponse,
)
return IO.NodeOutput(await download_url_to_image_tensor(response.result.image_url))
class BriaEraser(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="BriaEraser",
display_name="Bria Eraser",
category="partner/image/Bria",
description="Remove objects or areas outlined by a mask from an image using Bria.",
inputs=[
IO.Image.Input("image"),
IO.Mask.Input(
"mask",
tooltip="White areas are erased, black areas are preserved. "
"The mask is binarized before sending, so partially painted areas count as white. "
"Must have the same aspect ratio as the image.",
),
IO.Combo.Input(
"mask_type",
options=["manual", "automatic"],
tooltip="manual for hand-drawn or brush masks, "
"automatic for masks produced by segmentation models such as SAM.",
),
IO.DynamicCombo.Input(
"moderation",
options=[
IO.DynamicCombo.Option("false", []),
IO.DynamicCombo.Option(
"true",
[
IO.Boolean.Input("visual_input_moderation", default=False),
IO.Boolean.Input("visual_output_moderation", default=False),
],
),
],
tooltip="Moderation settings",
),
],
outputs=[IO.Image.Output()],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
expr="""{"type":"usd","usd":0.0286}""",
),
)
@classmethod
async def execute(
cls,
image: Input.Image,
mask: Input.Image,
mask_type: str,
moderation: dict,
) -> IO.NodeOutput:
_validate_mask_aspect_ratio(image, mask)
mask_image = _mask_to_binary_image(mask, "erase")
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/bria/v2/image/edit/erase", method="POST"),
data=BriaEraseRequest(
image=await upload_image_to_comfyapi(cls, image, total_pixels=None, wait_label="Uploading image"),
mask=await upload_image_to_comfyapi(
cls, mask_image, total_pixels=None, wait_label="Uploading mask"
),
mask_type=mask_type,
visual_input_content_moderation=moderation.get("visual_input_moderation", False),
visual_output_content_moderation=moderation.get("visual_output_moderation", False),
),
response_model=BriaStatusResponse,
)
response = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/bria/v2/status/{response.request_id}"),
status_extractor=lambda r: r.status,
response_model=BriaImageResultResponse,
)
return IO.NodeOutput(await download_url_to_image_tensor(response.result.image_url))
class BriaExpandImage(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="BriaExpandImage",
display_name="Bria Expand Image",
category="partner/image/Bria",
description="Expand an image beyond its borders with generated content using Bria.",
inputs=[
IO.Image.Input("image"),
IO.DynamicCombo.Input(
"expand_mode",
options=[
*[IO.DynamicCombo.Option(ratio, []) for ratio in
["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"]],
IO.DynamicCombo.Option(
"custom_ratio",
[
IO.Int.Input(
"ratio_width",
default=21,
min=1,
max=100,
tooltip="Width side of the target ratio: 21 and 9 give 21:9.",
),
IO.Int.Input(
"ratio_height",
default=9,
min=1,
max=100,
tooltip="Height side of the target ratio: 21 and 9 give 21:9. "
f"Bria only accepts width/height between {BRIA_MIN_RATIO} and "
f"{BRIA_MAX_RATIO}, so anything taller than 1:2 needs the manual mode.",
),
],
),
IO.DynamicCombo.Option(
"manual",
[
IO.Int.Input("canvas_width", default=1000, min=64, max=5000),
IO.Int.Input("canvas_height", default=1000, min=64, max=5000),
IO.Int.Input(
"image_width",
default=500,
min=1,
max=5000,
tooltip="Width of the original image inside the canvas.",
),
IO.Int.Input(
"image_height",
default=500,
min=1,
max=5000,
tooltip="Height of the original image inside the canvas.",
),
IO.Int.Input(
"image_x",
default=250,
min=-5000,
max=5000,
tooltip="X position of the image's top-left corner inside the canvas; "
"may fall outside the canvas, cropping the image.",
),
IO.Int.Input(
"image_y",
default=250,
min=-5000,
max=5000,
tooltip="Y position of the image's top-left corner inside the canvas; "
"may fall outside the canvas, cropping the image.",
),
],
),
],
tooltip="Target shape of the expanded image: a preset aspect ratio, a custom ratio, "
"or manual placement of the original image on a canvas. "
"Manual is the only mode that can reach a canvas taller than 1:2.",
),
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Optional description of the expanded scene; "
"when empty, Bria generates one from the image.",
),
IO.String.Input("negative_prompt", multiline=True, default=""),
IO.Int.Input(
"seed",
default=42,
min=1,
max=2147483647,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
),
IO.DynamicCombo.Input(
"moderation",
options=[
IO.DynamicCombo.Option("false", []),
IO.DynamicCombo.Option(
"true",
[
IO.Boolean.Input("prompt_content_moderation", default=False),
IO.Boolean.Input("visual_input_moderation", default=False),
IO.Boolean.Input("visual_output_moderation", default=False),
],
),
],
tooltip="Moderation settings",
),
],
outputs=[
IO.Image.Output(),
IO.String.Output(display_name="prompt", tooltip="The prompt used for the expansion; "
"auto-generated by Bria when the prompt input is empty."),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
expr="""{"type":"usd","usd":0.0286}""",
),
)
@classmethod
async def execute(
cls,
image: Input.Image,
expand_mode: dict,
prompt: str,
negative_prompt: str,
seed: int,
moderation: InputModerationSettings,
) -> IO.NodeOutput:
mode = expand_mode["expand_mode"]
aspect_ratio = canvas_size = original_image_size = original_image_location = None
if mode == "manual":
canvas_size = [expand_mode["canvas_width"], expand_mode["canvas_height"]]
original_image_size = [expand_mode["image_width"], expand_mode["image_height"]]
original_image_location = [expand_mode["image_x"], expand_mode["image_y"]]
elif mode == "custom_ratio":
ratio_width, ratio_height = expand_mode["ratio_width"], expand_mode["ratio_height"]
aspect_ratio = ratio_width / ratio_height
if not BRIA_MIN_RATIO <= aspect_ratio <= BRIA_MAX_RATIO:
raise ValueError(
f"Bria accepts a width-to-height ratio between {BRIA_MIN_RATIO} and {BRIA_MAX_RATIO}: "
f"{ratio_width}:{ratio_height} is {aspect_ratio:.4f}. "
f"Use the manual expand mode to reach a canvas of any shape."
)
else:
aspect_ratio = mode
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/bria/v2/image/edit/expand", method="POST"),
data=BriaExpandRequest(
image=await upload_image_to_comfyapi(cls, image, total_pixels=None, wait_label="Uploading image"),
aspect_ratio=aspect_ratio,
canvas_size=canvas_size,
original_image_size=original_image_size,
original_image_location=original_image_location,
prompt=prompt if prompt else None,
negative_prompt=negative_prompt if negative_prompt else None,
seed=seed,
prompt_content_moderation=moderation.get("prompt_content_moderation", False),
visual_input_content_moderation=moderation.get("visual_input_moderation", False),
visual_output_content_moderation=moderation.get("visual_output_moderation", False),
),
response_model=BriaStatusResponse,
)
response = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/bria/v2/status/{response.request_id}"),
status_extractor=lambda r: r.status,
response_model=BriaExpandResponse,
)
return IO.NodeOutput(
await download_url_to_image_tensor(response.result.image_url),
response.result.prompt or "",
)
class BriaIncreaseResolution(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="BriaIncreaseResolution",
display_name="Bria Increase Resolution",
category="partner/image/Bria",
description="Upscale an image by 2x or 4x using Bria, preserving the original content.",
inputs=[
IO.Image.Input("image"),
IO.Combo.Input(
"desired_increase",
options=["2", "4"],
tooltip="Resolution multiplier. The output must fit within 8192 pixels on each side.",
),
IO.Boolean.Input(
"auto_downscale",
default=False,
tooltip="Automatically lower the multiplier, and downscale the input image if that is "
"still not enough, when the output would exceed the limit.",
),
IO.DynamicCombo.Input(
"moderation",
options=[
IO.DynamicCombo.Option("false", []),
IO.DynamicCombo.Option(
"true",
[
IO.Boolean.Input("visual_input_moderation", default=False),
IO.Boolean.Input("visual_output_moderation", default=False),
],
),
],
tooltip="Moderation settings",
),
],
outputs=[IO.Image.Output()],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
expr="""{"type":"usd","usd":0.0286}""",
),
)
@classmethod
async def execute(
cls,
image: Input.Image,
desired_increase: str,
auto_downscale: bool,
moderation: dict,
) -> IO.NodeOutput:
multiplier = int(desired_increase)
height, width = get_image_dimensions(image)
if _upscaled_output_side(height, width, multiplier) > BRIA_MAX_OUTPUT_SIDE:
candidates = [c for c in (4, 2) if c <= multiplier]
if not auto_downscale:
predicted = _upscaled_output_side(height, width, multiplier)
raise ValueError(
f"Bria can upscale up to a maximum output dimension of {BRIA_MAX_OUTPUT_SIDE} pixels: "
f"input is {width}x{height}, x{multiplier} would be {predicted} pixels on the long side. "
f"Enable auto_downscale, or use a smaller input image or a lower multiplier."
)
fitted = next(
(c for c in candidates if _upscaled_output_side(height, width, c) <= BRIA_MAX_OUTPUT_SIDE), None
)
if fitted is not None:
multiplier = fitted
else:
shrinkable = next((c for c in sorted(candidates) if _smallest_output_side(height, width, c)
<= BRIA_MAX_OUTPUT_SIDE), None)
if shrinkable is None:
raise ValueError(
f"This image cannot be upscaled by Bria at any multiplier: it is {width}x{height}, and "
f"Bria first enlarges the short side to {BRIA_MIN_SHORT_SIDE} pixels, which pushes the "
f"long side past the {BRIA_MAX_OUTPUT_SIDE} pixel limit. Crop it to a squarer shape first."
)
multiplier = shrinkable
image = downscale_image_tensor_by_max_side(image, max_side=BRIA_MAX_OUTPUT_SIDE // multiplier)
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/bria/v2/image/edit/increase_resolution", method="POST"),
data=BriaIncreaseResolutionRequest(
image=await upload_image_to_comfyapi(cls, image, total_pixels=None, wait_label="Uploading image"),
desired_increase=multiplier,
visual_input_content_moderation=moderation.get("visual_input_moderation", False),
visual_output_content_moderation=moderation.get("visual_output_moderation", False),
),
response_model=BriaStatusResponse,
)
response = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/bria/v2/status/{response.request_id}"),
status_extractor=lambda r: r.status,
response_model=BriaImageResultResponse,
)
return IO.NodeOutput(await download_url_to_image_tensor(response.result.image_url))
class BriaRemoveVideoBackground(IO.ComfyNode):
@classmethod
@ -572,6 +1092,10 @@ class BriaExtension(ComfyExtension):
return [
BriaImageEditNode,
BriaRemoveImageBackground,
BriaGenFill,
BriaEraser,
BriaExpandImage,
BriaIncreaseResolution,
BriaRemoveVideoBackground,
BriaVideoGreenScreen,
BriaVideoReplaceBackground,