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Lizayaro 8585ab54e8 Delete workflows/Product_shot_placements.json 2025-10-23 15:05:32 +03:00
Lizayaro b38d15efe4 Add files via upload 2025-10-23 14:59:49 +03:00
Yazan Numoor 513fec79b5 Merge pull request #26 from Bria-AI/WAI-4049
WAI-4049
2025-10-23 09:48:24 +03:00
Yazan Numoor ddbf7d0695 Update pyproject.toml 2025-10-22 20:38:36 +03:00
Ubuntu 3befc0a2ac update automatic nodes to return 7 results 2025-10-16 08:15:20 +00:00
Ubuntu af6ef2a829 fix Gabi Feedback 2025-10-15 10:39:44 +00:00
Ubuntu bc5dacb9ef Merge branch 'main' of https://github.com/Bria-AI/ComfyUI-BRIA-API into WAI-4049 2025-09-29 13:44:10 +00:00
Ubuntu fc8aa8b6a7 WAI-4049 2025-09-29 13:39:47 +00:00
Yazan Numoor 9960a93044 Merge pull request #25 from Bria-AI/WAI-4011
WAI-4011
2025-09-29 15:47:10 +03:00
Ubuntu 8d3eef85ca update version 2025-09-29 12:44:46 +00:00
Ubuntu bb4108b6c4 WAI-4049 2025-09-29 11:48:24 +00:00
mabualrob1997 18a5ffbcca Update Readme.md 2025-09-29 12:45:46 +03:00
Ubuntu 4f3b7fb77a WAI-4011 2025-09-23 06:49:12 +00:00
Yazan Numoor c3b5fea335 Update pyproject.toml 2025-09-18 19:31:00 +03:00
Yazan Numoor b8e40e90bc Merge pull request #24 from Bria-AI/WAI-3976-feedback-fixes
WAI-3976-feedback-fixes
2025-09-18 19:30:33 +03:00
19 changed files with 1098 additions and 287 deletions
+9
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@@ -68,6 +68,15 @@ These nodes create high-quality product images for eCommerce workflows.
| **ShotByText** | Modifies an image's background by providing a text prompt. Powered by BRIA's ControlNet Background-Generation. |
| **ShotByImage** | Modifies an image's background by providing a reference image. Uses BRIA's ControlNet Background-Generation and Image-Prompt. |
## Attribution Node
| Node | Description |
|-------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **Attribution By Image Node** | This node shares generated images via API for Bria to pay attribution to the data owners who contributed to the generation. Once the images are shared with Bria, Bria calculates the attribution, completes the payment on behalf of the user, and erases the images immediately. This node should be included in any workflow using nodes of Bria’s Models (not necessary for Bria’s API nodes). You can also refer to the [**API documentation**]( https://docs.bria.ai/bria-attribution-service/other/postattributionbyimage) |
# Installation
There are two methods to install the BRIA ComfyUI API nodes:
+55 -7
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@@ -1,6 +1,32 @@
from .nodes import (EraserNode, GenFillNode, ImageExpansionNode, ReplaceBgNode, RmbgNode, RemoveForegroundNode, ShotByTextNode, ShotByImageNode, TailoredGenNode,
TailoredModelInfoNode, Text2ImageBaseNode, Text2ImageFastNode, Text2ImageHDNode, TailoredPortraitNode,
ReimagineNode)
from .nodes import (
EraserNode,
GenFillNode,
ImageExpansionNode,
ReplaceBgNode,
RmbgNode,
RemoveForegroundNode,
ShotByTextOriginalNode,
ShotByImageOriginalNode,
TailoredGenNode,
TailoredModelInfoNode,
Text2ImageBaseNode,
Text2ImageFastNode,
Text2ImageHDNode,
TailoredPortraitNode,
ReimagineNode,
ShotByTextAutomaticNode,
ShotByImageManualPaddingNode,
ShotByImageAutomaticAspectRatioNode,
ShotByImageCustomCoordinatesNode,
ShotByImageManualPlacementNode,
ShotByImageAutomaticNode,
ShotByTextAutomaticAspectRatioNode,
ShotByTextManualPlacementNode,
ShotByTextManualPaddingNode,
ShotByTextCustomCoordinatesNode,
AttributionByImageNode
)
# Map the node class to a name used internally by ComfyUI
NODE_CLASS_MAPPINGS = {
"BriaEraser": EraserNode, # Return the class, not an instance
@@ -9,8 +35,18 @@ NODE_CLASS_MAPPINGS = {
"ReplaceBgNode": ReplaceBgNode,
"RmbgNode": RmbgNode,
"RemoveForegroundNode": RemoveForegroundNode,
"ShotByTextNode": ShotByTextNode,
"ShotByImageNode": ShotByImageNode,
"ShotByTextOriginal": ShotByTextOriginalNode,
"ShotByImageOriginal": ShotByImageOriginalNode,
"ShotByTextAutomatic": ShotByTextAutomaticNode,
"ShotByTextManualPlacement": ShotByTextManualPlacementNode,
"ShotByTextCustomCoordinates": ShotByTextCustomCoordinatesNode,
"ShotByTextManualPadding": ShotByTextManualPaddingNode,
"ShotByTextAutomaticAspectRatio": ShotByTextAutomaticAspectRatioNode,
"ShotByImageAutomatic": ShotByImageAutomaticNode,
"ShotByImageManualPlacement": ShotByImageManualPlacementNode,
"ShotByImageCustomCoordinates": ShotByImageCustomCoordinatesNode,
"ShotByImageManualPadding": ShotByImageManualPaddingNode,
"ShotByImageAutomaticAspectRatio": ShotByImageAutomaticAspectRatioNode,
"BriaTailoredGen": TailoredGenNode,
"TailoredModelInfoNode": TailoredModelInfoNode,
"TailoredPortraitNode": TailoredPortraitNode,
@@ -18,6 +54,7 @@ NODE_CLASS_MAPPINGS = {
"Text2ImageFastNode": Text2ImageFastNode,
"Text2ImageHDNode": Text2ImageHDNode,
"ReimagineNode": ReimagineNode,
"AttributionByImageNode":AttributionByImageNode
}
# Map the node display name to the one shown in the ComfyUI node interface
NODE_DISPLAY_NAME_MAPPINGS = {
@@ -27,8 +64,18 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"ReplaceBgNode": "Bria Replace Background",
"RmbgNode": "Bria RMBG",
"RemoveForegroundNode": "Bria Remove Foreground",
"ShotByTextNode": "Bria Shot By Text",
"ShotByImageNode": "Bria Shot By Image",
"ShotByTextOriginal": "Shot by Text - Original",
"ShotByImageOriginal": "Shot by Image - Original",
"ShotByTextAutomatic": "Shot by Text - Automatic",
"ShotByTextManualPlacement": "Shot by Text - Manual Placement",
"ShotByTextCustomCoordinates": "Shot by Text - Custom Coordinates",
"ShotByTextManualPadding": "Shot by Text - Manual Padding",
"ShotByTextAutomaticAspectRatio": "Shot by Text - Automatic Aspect Ratio",
"ShotByImageAutomatic": "Shot by Image - Automatic",
"ShotByImageManualPlacement": "Shot by Image - Manual Placement",
"ShotByImageCustomCoordinates": "Shot by Image - Custom Coordinates",
"ShotByImageManualPadding": "Shot by Image - Manual Padding",
"ShotByImageAutomaticAspectRatio": "Shot by Image - Automatic Aspect Ratio",
"BriaTailoredGen": "Bria Tailored Gen",
"TailoredModelInfoNode": "Bria Tailored Model Info",
"TailoredPortraitNode": "Bria Restyle Portrait",
@@ -36,4 +83,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"Text2ImageFastNode": "Bria Text2Image Fast",
"Text2ImageHDNode": "Bria Text2Image HD",
"ReimagineNode": "Bria Reimagine",
"AttributionByImageNode":"Attribution By Image Node"
}
+16 -3
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@@ -4,12 +4,25 @@ from .image_expansion_node import ImageExpansionNode
from .replace_bg_node import ReplaceBgNode
from .rmbg_node import RmbgNode
from .remove_foreground_node import RemoveForegroundNode
from .shot_by_text_node import ShotByTextNode
from .shot_by_image_node import ShotByImageNode
from .tailored_gen_node import TailoredGenNode
from .tailored_model_info_node import TailoredModelInfoNode
from .tailored_portrait_node import TailoredPortraitNode
from .text_2_image_base_node import Text2ImageBaseNode
from .text_2_image_fast_node import Text2ImageFastNode
from .text_2_image_hd_node import Text2ImageHDNode
from .reimagine_node import ReimagineNode
from .reimagine_node import ReimagineNode
from .shot_by_text_node import ShotByTextOriginalNode
from .shot_by_text_automatic_aspect_ratio_node import ShotByTextAutomaticAspectRatioNode
from .shot_by_text_automatic_node import ShotByTextAutomaticNode
from .shot_by_text_custom_coordinates_node import ShotByTextCustomCoordinatesNode
from .shot_by_text_manual_placement_node import ShotByTextManualPlacementNode
from .shot_by_text_manual_padding_node import ShotByTextManualPaddingNode
from .shot_by_image_automatic_aspect_ratio_node import (
ShotByImageAutomaticAspectRatioNode,
)
from .shot_by_image_automatic_node import ShotByImageAutomaticNode
from .shot_by_image_custom_coordinates_node import ShotByImageCustomCoordinatesNode
from .shot_by_image_node import ShotByImageOriginalNode
from .shot_by_image_manual_placement_node import ShotByImageManualPlacementNode
from .shot_by_image_manual_padding_node import ShotByImageManualPaddingNode
from .attribution_by_image_node import AttributionByImageNode
+66
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@@ -0,0 +1,66 @@
import requests
import torch
from .common import preprocess_image, image_to_base64, poll_status_until_completed
class AttributionByImageNode():
@classmethod
def INPUT_TYPES(self):
return {
"required": {
"image": ("IMAGE",),
"model_version": (["2.3", "3.0","3.2"], {"default": "2.3"}),
"api_key": ("STRING", {"default": "BRIA_API_TOKEN"}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("api_response",)
CATEGORY = "API Nodes"
FUNCTION = "execute" # This is the method that will be executed
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v2/image/attribution/by_image"
# Define the execute method as expected by ComfyUI
def execute(self, image, model_version, api_key):
if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API key.")
# Check if image is tensor, if so, convert to NumPy array
if isinstance(image, torch.Tensor):
image = preprocess_image(image)
# Convert image to base64 for the new API format
image_base64 = image_to_base64(image)
payload = {
"image": image_base64,
"model_version": model_version,
}
headers = {
"Content-Type": "application/json",
"api_token": f"{api_key}"
}
try:
response = requests.post(self.api_url, json=payload, headers=headers)
if response.status_code == 200 or response.status_code == 202:
print('Initial Attribution via Images API request successful, polling for completion...')
response_dict = response.json()
status_url = response_dict.get('status_url')
request_id = response_dict.get('request_id')
if not status_url:
raise Exception("No status_url returned from API")
print(f"Request ID: {request_id}, Status URL: {status_url}")
final_response = poll_status_until_completed(status_url, api_key)
return (str(final_response.get("result",{}).get("content")),)
else:
raise Exception(f"Error: API request failed with status code {response.status_code} {response.text}")
except Exception as e:
raise Exception(f"{e}")
@@ -0,0 +1,46 @@
from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
class ShotByImageAutomaticAspectRatioNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_image_input_types()
input_types["required"]["aspect_ratio"] = (
["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"],
{"default": "1:1"},
)
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_image_api_url
def execute(
self,
image,
ref_image,
aspect_ratio,
api_key,
sync=False,
enhance_ref_image=True,
ref_image_influence=1.0,
force_rmbg=False,
content_moderation=False,
):
payload = create_image_payload(
image,
ref_image,
api_key,
PlacementType.AUTOMATIC_ASPECT_RATIO.value,
aspect_ratio=aspect_ratio,
sync=sync,
enhance_ref_image=enhance_ref_image,
ref_image_influence=ref_image_influence,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
+51
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@@ -0,0 +1,51 @@
from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
class ShotByImageAutomaticNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_image_input_types()
input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
return input_types
RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE")
RETURN_NAMES = (
"output_image_1",
"output_image_2",
"output_image_3",
"output_image_4",
"output_image_5",
"output_image_6",
"output_image_7",
)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_image_api_url
def execute(
self,
image,
ref_image,
shot_size,
api_key,
sync=False,
enhance_ref_image=True,
ref_image_influence=1.0,
force_rmbg=False,
content_moderation=False,
):
payload = create_image_payload(
image,
ref_image,
api_key,
PlacementType.AUTOMATIC.value,
shot_size=shot_size,
sync=sync,
enhance_ref_image=enhance_ref_image,
ref_image_influence=ref_image_influence,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key, Placement_type = PlacementType.AUTOMATIC.value)
@@ -0,0 +1,55 @@
from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
class ShotByImageCustomCoordinatesNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_image_input_types()
input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
input_types["required"]["foreground_image_size"] = (
"STRING",
{"default": "500,500"},
)
input_types["required"]["foreground_image_location"] = (
"STRING",
{"default": "0, 0"},
)
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_image_api_url
def execute(
self,
image,
ref_image,
shot_size,
foreground_image_size,
foreground_image_location,
api_key,
sync=False,
enhance_ref_image=True,
ref_image_influence=1.0,
force_rmbg=False,
content_moderation=False,
):
payload = create_image_payload(
image,
ref_image,
api_key,
PlacementType.CUSTOM_COORDINATES.value,
shot_size=shot_size,
foreground_image_size=foreground_image_size,
foreground_image_location=foreground_image_location,
sync=sync,
enhance_ref_image=enhance_ref_image,
ref_image_influence=ref_image_influence,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,44 @@
from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
class ShotByImageManualPaddingNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_image_input_types()
input_types["required"]["padding_values"] = ("STRING", {"default": "0,0,0,0"})
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_image_api_url
def execute(
self,
image,
ref_image,
padding_values,
api_key,
sync=False,
enhance_ref_image=True,
ref_image_influence=1.0,
force_rmbg=False,
content_moderation=False,
):
payload = create_image_payload(
image,
ref_image,
api_key,
PlacementType.MANUAL_PADDING.value,
padding_values=padding_values,
sync=sync,
enhance_ref_image=enhance_ref_image,
ref_image_influence=ref_image_influence,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,59 @@
from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
class ShotByImageManualPlacementNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_image_input_types()
input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
input_types["required"]["manual_placement_selection"] = (
[
"upper_left",
"upper_right",
"bottom_left",
"bottom_right",
"right_center",
"left_center",
"upper_center",
"bottom_center",
"center_vertical",
"center_horizontal",
],
{"default": "upper_left"},
)
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_image_api_url
def execute(
self,
image,
ref_image,
shot_size,
manual_placement_selection,
api_key,
sync=False,
enhance_ref_image=True,
ref_image_influence=1.0,
force_rmbg=False,
content_moderation=False,
):
payload = create_image_payload(
image,
ref_image,
api_key,
PlacementType.MANUAL_PLACEMENT.value,
shot_size=shot_size,
manual_placement_selection=manual_placement_selection,
sync=sync,
enhance_ref_image=enhance_ref_image,
ref_image_influence=ref_image_influence,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
+41 -72
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@@ -1,72 +1,41 @@
import requests
import torch
from .common import postprocess_image, preprocess_image, image_to_base64
class ShotByImageNode():
@classmethod
def INPUT_TYPES(self):
return {
"required": {
"image": ("IMAGE",), # Input image from another node
"ref_image": ("IMAGE",), # ref image from another node
"enhance_ref_image": ("INT", {"default": 1}),
"api_key": ("STRING", {"default": "BRIA_API_TOKEN"}) # API Key input with a default value
},
"optional": {
"content_moderation": ("BOOLEAN", {"default": False}),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute" # This is the method that will be executed
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_image" # Eraser API URL
# Define the execute method as expected by ComfyUI
def execute(self, image, ref_image, api_key, enhance_ref_image, content_moderation):
if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API key.")
# Check if image and mask are tensors, if so, convert to NumPy arrays
if isinstance(image, torch.Tensor):
image = preprocess_image(image)
if isinstance(ref_image, torch.Tensor):
ref_image = preprocess_image(ref_image)
# Convert the image and mask directly to Base64 strings
image_base64 = image_to_base64(image)
ref_image_base64 = image_to_base64(ref_image)
enhance_ref_image = bool(enhance_ref_image)
payload = {
"file": image_base64,
"ref_image_file": ref_image_base64,
"enhance_ref_image": enhance_ref_image,
"placement_type": "original",
"original_quality": True,
"sync": True,
"content_moderation": content_moderation
}
headers = {
"Content-Type": "application/json",
"api_token": f"{api_key}"
}
try:
response = requests.post(self.api_url, json=payload, headers=headers)
# Check for successful response
if response.status_code == 200:
print('response is 200')
# Process the output image from API response
response_dict = response.json()
image_response = requests.get(response_dict['result'][0][0])
result_image = postprocess_image(image_response.content)
return (result_image,)
else:
raise Exception(f"Error: API request failed with status code {response.status_code}")
except Exception as e:
raise Exception(f"{e}")
from .utils.shot_utils import get_image_input_types, create_image_payload, make_api_request, shot_by_image_api_url, PlacementType
class ShotByImageOriginalNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_image_input_types()
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_image_api_url
def execute(
self,
image,
ref_image,
api_key,
sync=True,
enhance_ref_image=True,
ref_image_influence=1.0,
force_rmbg=False,
content_moderation=False,
):
payload = create_image_payload(
image,
ref_image,
api_key,
PlacementType.ORIGINAL.value,
original_quality=True,
sync=sync,
enhance_ref_image=enhance_ref_image,
ref_image_influence=ref_image_influence,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,48 @@
from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
class ShotByTextAutomaticAspectRatioNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_text_input_types()
input_types["required"]["aspect_ratio"] = (
["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9"],
{"default": "1:1"},
)
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_text_api_url
def execute(
self,
image,
scene_description,
mode,
aspect_ratio,
api_key,
sync=False,
optimize_description=True,
exclude_elements="",
force_rmbg=False,
content_moderation=False,
):
payload = create_text_payload(
image,
api_key,
scene_description,
mode,
PlacementType.AUTOMATIC_ASPECT_RATIO.value,
aspect_ratio=aspect_ratio,
sync=sync,
optimize_description=optimize_description,
exclude_elements=exclude_elements,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
+53
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@@ -0,0 +1,53 @@
from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
class ShotByTextAutomaticNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_text_input_types()
input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
return input_types
RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE", "IMAGE")
RETURN_NAMES = (
"output_image_1",
"output_image_2",
"output_image_3",
"output_image_4",
"output_image_5",
"output_image_6",
"output_image_7",
)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_text_api_url
def execute(
self,
image,
scene_description,
mode,
shot_size,
api_key,
sync=False,
optimize_description=True,
exclude_elements="",
force_rmbg=False,
content_moderation=False,
):
payload = create_text_payload(
image,
api_key,
scene_description,
mode,
PlacementType.AUTOMATIC.value,
shot_size=shot_size,
sync=sync,
optimize_description=optimize_description,
exclude_elements=exclude_elements,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key, Placement_type= PlacementType.AUTOMATIC.value)
@@ -0,0 +1,57 @@
from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
class ShotByTextCustomCoordinatesNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_text_input_types()
input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
input_types["required"]["foreground_image_size"] = (
"STRING",
{"default": "500,500"},
)
input_types["required"]["foreground_image_location"] = (
"STRING",
{"default": "0, 0"},
)
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_text_api_url
def execute(
self,
image,
scene_description,
mode,
shot_size,
foreground_image_size,
foreground_image_location,
api_key,
sync=False,
optimize_description=True,
exclude_elements="",
force_rmbg=False,
content_moderation=False,
):
payload = create_text_payload(
image,
api_key,
scene_description,
mode,
PlacementType.CUSTOM_COORDINATES.value,
shot_size=shot_size,
foreground_image_size=foreground_image_size,
foreground_image_location=foreground_image_location,
sync=sync,
optimize_description=optimize_description,
exclude_elements=exclude_elements,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
+45
View File
@@ -0,0 +1,45 @@
from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
class ShotByTextManualPaddingNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_text_input_types()
input_types["required"]["padding_values"] = ("STRING", {"default": "0,0,0,0"})
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_text_api_url
def execute(
self,
image,
scene_description,
mode,
padding_values,
api_key,
sync=False,
optimize_description=True,
exclude_elements="",
force_rmbg=False,
content_moderation=False,
):
payload = create_text_payload(
image,
api_key,
scene_description,
mode,
PlacementType.MANUAL_PADDING.value,
padding_values=padding_values,
sync=sync,
optimize_description=optimize_description,
exclude_elements=exclude_elements,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
@@ -0,0 +1,62 @@
from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
class ShotByTextManualPlacementNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_text_input_types()
input_types["required"]["shot_size"] = ("STRING", {"default": "1000, 1000"})
input_types["required"]["manual_placement_selection"] = (
[
"upper_left",
"upper_right",
"bottom_left",
"bottom_right",
"right_center",
"left_center",
"upper_center",
"bottom_center",
"center_vertical",
"center_horizontal",
],
{"default": "upper_left"},
)
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_text_api_url
def execute(
self,
image,
scene_description,
mode,
shot_size,
manual_placement_selection,
api_key,
sync=False,
optimize_description=True,
exclude_elements="",
force_rmbg=False,
content_moderation=False,
):
payload = create_text_payload(
image,
api_key,
scene_description,
mode,
PlacementType.MANUAL_PLACEMENT.value,
shot_size=shot_size,
manual_placement_selection=manual_placement_selection,
sync=sync,
optimize_description=optimize_description,
exclude_elements=exclude_elements,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
+42 -68
View File
@@ -1,68 +1,42 @@
import requests
import torch
from .common import postprocess_image, preprocess_image, image_to_base64
class ShotByTextNode():
@classmethod
def INPUT_TYPES(self):
return {
"required": {
"image": ("IMAGE",), # Input image from another node
"scene_description": ("STRING",),
"mode": (["base", "fast", "high_control"], {"default": "high_control"}),
"api_key": ("STRING", {"default": "BRIA_API_TOKEN"}) # API Key input with a default value
},
"optional": {
"content_moderation": ("BOOLEAN", {"default": False}),
}
}
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute" # This is the method that will be executed
def __init__(self):
self.api_url = "https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_text" # Eraser API URL
# Define the execute method as expected by ComfyUI
def execute(self, image, api_key, scene_description, mode, content_moderation):
if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API key.")
# Check if image and mask are tensors, if so, convert to NumPy arrays
if isinstance(image, torch.Tensor):
image = preprocess_image(image)
image_base64 = image_to_base64(image)
payload = {
"file": image_base64,
"scene_description": scene_description,
"mode": mode,
"placement_type": "original",
"original_quality": True,
"sync": True,
"content_moderation": content_moderation
}
headers = {
"Content-Type": "application/json",
"api_token": f"{api_key}"
}
try:
response = requests.post(self.api_url, json=payload, headers=headers)
# Check for successful response
if response.status_code == 200:
print('response is 200')
# Process the output image from API response
response_dict = response.json()
image_response = requests.get(response_dict['result'][0][0])
result_image = postprocess_image(image_response.content)
return (result_image,)
else:
raise Exception(f"Error: API request failed with status code {response.status_code}")
except Exception as e:
raise Exception(f"{e}")
from .utils.shot_utils import get_text_input_types, create_text_payload, make_api_request, shot_by_text_api_url, PlacementType
class ShotByTextOriginalNode:
@classmethod
def INPUT_TYPES(self):
input_types = get_text_input_types()
return input_types
RETURN_TYPES = ("IMAGE",)
RETURN_NAMES = ("output_image",)
CATEGORY = "API Nodes"
FUNCTION = "execute"
def __init__(self):
self.api_url = shot_by_text_api_url
def execute(
self,
image,
scene_description,
mode,
api_key,
sync=True,
optimize_description=True,
exclude_elements="",
force_rmbg=False,
content_moderation=False,
):
payload = create_text_payload(
image,
api_key,
scene_description,
mode,
PlacementType.ORIGINAL.value,
original_quality=True,
sync=sync,
optimize_description=optimize_description,
exclude_elements=exclude_elements,
force_rmbg=force_rmbg,
content_moderation=content_moderation,
)
return make_api_request(self.api_url, payload, api_key)
+204
View File
@@ -0,0 +1,204 @@
import requests
import torch
from ..common import postprocess_image, preprocess_image, image_to_base64
shot_by_text_api_url = (
"https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_text"
)
shot_by_image_api_url = (
"https://engine.prod.bria-api.com/v1/product/lifestyle_shot_by_image"
)
from enum import Enum
class PlacementType(str, Enum):
ORIGINAL = "original"
AUTOMATIC = "automatic"
MANUAL_PLACEMENT = "manual_placement"
MANUAL_PADDING = "manual_padding"
CUSTOM_COORDINATES = "custom_coordinates"
AUTOMATIC_ASPECT_RATIO = "automatic_aspect_ratio"
def validate_api_key(api_key):
"""Validate API key input"""
if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
raise Exception("Please insert a valid API key.")
def update_payload_for_placement(placement_type, payload, **kwargs):
if placement_type == PlacementType.AUTOMATIC.value:
payload["shot_size"] = [
int(x.strip()) for x in kwargs.get("shot_size").split(",")
]
elif placement_type == PlacementType.MANUAL_PLACEMENT.value:
payload["shot_size"] = [
int(x.strip()) for x in kwargs.get("shot_size").split(",")
]
payload["manual_placement_selection"] = [
kwargs.get("manual_placement_selection", "upper_left")
]
elif placement_type == PlacementType.CUSTOM_COORDINATES.value:
payload["shot_size"] = [
int(x.strip()) for x in kwargs.get("shot_size").split(",")
]
payload["foreground_image_size"] = [
int(x.strip()) for x in kwargs.get("foreground_image_size").split(",")
]
payload["foreground_image_location"] = [
int(x.strip()) for x in kwargs.get("foreground_image_location").split(",")
]
elif placement_type == PlacementType.MANUAL_PADDING.value:
payload["padding_values"] = [
int(x.strip()) for x in kwargs.get("padding_values").split(",")
]
elif placement_type == PlacementType.AUTOMATIC_ASPECT_RATIO.value:
payload["aspect_ratio"] = kwargs.get("aspect_ratio", "1:1")
elif placement_type == PlacementType.ORIGINAL.value:
payload["original_quality"] = kwargs.get("original_quality", True)
return payload
def create_text_payload(
image, api_key, scene_description, mode, placement_type, **kwargs
):
validate_api_key(api_key)
# Process image
if isinstance(image, torch.Tensor):
image = preprocess_image(image)
image_base64 = image_to_base64(image)
payload = {
"file": image_base64,
"placement_type": placement_type,
"sync": True,
"num_results": 1,
"force_rmbg": kwargs.get("force_rmbg", False),
"content_moderation": kwargs.get("content_moderation", False),
"scene_description": scene_description,
"mode": mode,
"optimize_description": kwargs.get("optimize_description", True),
}
if kwargs.get("exclude_elements", "").strip():
payload["exclude_elements"] = kwargs["exclude_elements"]
payload = update_payload_for_placement(placement_type, payload, **kwargs)
return payload
def create_image_payload(image, ref_image, api_key, placement_type, **kwargs):
"""Create payload for image-based shot nodes"""
validate_api_key(api_key)
if isinstance(image, torch.Tensor):
image = preprocess_image(image)
if isinstance(ref_image, torch.Tensor):
ref_image = preprocess_image(ref_image)
image_base64 = image_to_base64(image)
ref_image_base64 = image_to_base64(ref_image)
# Base payload
payload = {
"file": image_base64,
"ref_image_file": ref_image_base64,
"enhance_ref_image": kwargs.get("enhance_ref_image", True),
"ref_image_influence": kwargs.get("ref_image_influence", 1.0),
"placement_type": placement_type,
"sync": True,
"num_results": 1,
"force_rmbg": kwargs.get("force_rmbg", False),
"content_moderation": kwargs.get("content_moderation", False),
}
payload = update_payload_for_placement(placement_type, payload, **kwargs)
return payload
def make_api_request(api_url, payload, api_key, Placement_type = None):
"""Make API request and return processed image"""
headers = {"Content-Type": "application/json", "api_token": f"{api_key}"}
try:
response = requests.post(api_url, json=payload, headers=headers)
if response.status_code == 200:
print("response is 200")
response_dict = response.json()
if Placement_type == PlacementType.AUTOMATIC.value:
result_images = []
for i, result in enumerate(response_dict.get("result", [])[:7]):
image_url = result[0]
image_response = requests.get(image_url)
processed = postprocess_image(image_response.content)
result_images.append(processed)
# If less than 7 images, pad with None to match ComfyUI return structure
while len(result_images) < 7:
result_images.append(None)
print(result_images)
return tuple(result_images)
image_response = requests.get(response_dict["result"][0][0])
result_image = postprocess_image(image_response.content)
return (result_image,)
else:
raise Exception(
f"Error: API request failed with status code {response.status_code}{response.text}"
)
except Exception as e:
raise Exception(f"{e}")
def get_common_input_types():
"""Get common input types for all nodes"""
return {
"required": {"api_key": ("STRING", {"default": "BRIA_API_TOKEN"})},
"optional": {
"force_rmbg": ("BOOLEAN", {"default": False}),
"content_moderation": ("BOOLEAN", {"default": False}),
},
}
def get_text_input_types():
"""Get text-specific input types"""
common = get_common_input_types()
common["required"].update(
{
"image": ("IMAGE",),
"scene_description": ("STRING",),
"mode": (["base", "fast", "high_control"], {"default": "fast"}),
}
)
common["optional"].update(
{
"optimize_description": ("BOOLEAN", {"default": True}),
"exclude_elements": ("STRING", {"default": ""}),
}
)
return common
def get_image_input_types():
"""Get image-specific input types"""
common = get_common_input_types()
common["required"].update({"image": ("IMAGE",), "ref_image": ("IMAGE",)})
common["optional"].update(
{
"enhance_ref_image": ("BOOLEAN", {"default": True}),
"ref_image_influence": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0}),
}
)
return common
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "comfyui-bria-api"
description = "Custom nodes for ComfyUI using BRIA's API."
version = "2.1.0"
version = "2.1.3"
license = {file = "LICENSE"}
[project.urls]
@@ -1,18 +1,47 @@
{
"last_node_id": 42,
"last_link_id": 65,
"id": "1cdd7d4c-58b5-4047-947b-1977ad36d364",
"revision": 0,
"last_node_id": 14,
"last_link_id": 11,
"nodes": [
{
"id": 42,
"id": 6,
"type": "PreviewImage",
"pos": [
1351.83154296875,
26.696861267089844
],
"size": [
399.811279296875,
246
],
"flags": {},
"order": 5,
"mode": 0,
"inputs": [
{
"name": "images",
"type": "IMAGE",
"link": 5
}
],
"outputs": [],
"properties": {
"Node name for S&R": "PreviewImage"
},
"widgets_values": []
},
{
"id": 1,
"type": "LoadImage",
"pos": {
"0": 591,
"1": 593
},
"size": {
"0": 315,
"1": 314
},
"pos": [
383.92852783203125,
38.40964889526367
],
"size": [
397.5969543457031,
314
],
"flags": {},
"order": 0,
"mode": 0,
@@ -22,10 +51,9 @@
"name": "IMAGE",
"type": "IMAGE",
"links": [
64,
65
],
"slot_index": 0
1,
3
]
},
{
"name": "MASK",
@@ -37,21 +65,21 @@
"Node name for S&R": "LoadImage"
},
"widgets_values": [
"A_bottle_of_perfume.png",
"CAR.png",
"image"
]
},
{
"id": 39,
"id": 2,
"type": "LoadImage",
"pos": {
"0": 600,
"1": 988
},
"size": {
"0": 315,
"1": 314
},
"pos": [
369.0213623046875,
415.34893798828125
],
"size": [
450.83685302734375,
314.0000305175781
],
"flags": {},
"order": 1,
"mode": 0,
@@ -61,9 +89,8 @@
"name": "IMAGE",
"type": "IMAGE",
"links": [
59
],
"slot_index": 0
4
]
},
{
"name": "MASK",
@@ -75,21 +102,21 @@
"Node name for S&R": "LoadImage"
},
"widgets_values": [
"A_red_studio_with_a_shelf__close_up.png",
"seed_713360865.png",
"image"
]
},
{
"id": 15,
"id": 5,
"type": "Note",
"pos": {
"0": 995.4524536132812,
"1": 601.5353393554688
},
"size": {
"0": 306.28387451171875,
"1": 58
},
"pos": [
951.4669189453125,
5.085720062255859
],
"size": [
210,
88
],
"flags": {},
"order": 2,
"mode": 0,
@@ -103,40 +130,14 @@
"bgcolor": "#653"
},
{
"id": 40,
"id": 7,
"type": "PreviewImage",
"pos": {
"0": 1408,
"1": 623
},
"size": [
210,
246
"pos": [
1368.5450439453125,
340.4889221191406
],
"flags": {},
"order": 5,
"mode": 0,
"inputs": [
{
"name": "images",
"type": "IMAGE",
"link": 62
}
],
"outputs": [],
"properties": {
"Node name for S&R": "PreviewImage"
}
},
{
"id": 41,
"type": "PreviewImage",
"pos": {
"0": 1408,
"1": 951
},
"size": [
210,
387.0335693359375,
246
],
"flags": {},
@@ -146,25 +147,26 @@
{
"name": "images",
"type": "IMAGE",
"link": 63
"link": 6
}
],
"outputs": [],
"properties": {
"Node name for S&R": "PreviewImage"
}
},
"widgets_values": []
},
{
"id": 36,
"type": "ShotByTextNode",
"pos": {
"0": 996,
"1": 736
},
"size": {
"0": 315,
"1": 106
},
"id": 3,
"type": "ShotByTextOriginal",
"pos": [
941.8839111328125,
149.14889526367188
],
"size": [
273.388671875,
202
],
"flags": {},
"order": 3,
"mode": 0,
@@ -172,7 +174,7 @@
{
"name": "image",
"type": "IMAGE",
"link": 64
"link": 1
}
],
"outputs": [
@@ -180,31 +182,34 @@
"name": "output_image",
"type": "IMAGE",
"links": [
62
],
"slot_index": 0
5
]
}
],
"properties": {
"Node name for S&R": "ShotByTextNode"
"Node name for S&R": "ShotByTextOriginal"
},
"widgets_values": [
"a beautiful sunset",
1,
"BRIA_API_TOKEN",
"sea",
"fast",
false,
false,
true,
""
]
},
{
"id": 37,
"type": "ShotByImageNode",
"pos": {
"0": 999,
"1": 932
},
"size": {
"0": 315,
"1": 102
},
"id": 4,
"type": "ShotByImageOriginal",
"pos": [
945.0781860351562,
441.9688415527344
],
"size": [
272.0703125,
174
],
"flags": {},
"order": 4,
"mode": 0,
@@ -212,12 +217,12 @@
{
"name": "image",
"type": "IMAGE",
"link": 65
"link": 3
},
{
"name": "ref_image",
"type": "IMAGE",
"link": 59
"link": 4
}
],
"outputs": [
@@ -225,58 +230,60 @@
"name": "output_image",
"type": "IMAGE",
"links": [
63
],
"slot_index": 0
6
]
}
],
"properties": {
"Node name for S&R": "ShotByImageNode"
"Node name for S&R": "ShotByImageOriginal"
},
"widgets_values": [
0,
""
"BRIA_API_TOKEN",
false,
false,
true,
1
]
}
],
"links": [
[
59,
39,
1,
1,
0,
37,
3,
0,
"IMAGE"
],
[
3,
1,
0,
4,
0,
"IMAGE"
],
[
4,
2,
0,
4,
1,
"IMAGE"
],
[
62,
36,
5,
3,
0,
40,
6,
0,
"IMAGE"
],
[
63,
37,
6,
4,
0,
41,
0,
"IMAGE"
],
[
64,
42,
0,
36,
0,
"IMAGE"
],
[
65,
42,
0,
37,
7,
0,
"IMAGE"
]
@@ -285,12 +292,13 @@
"config": {},
"extra": {
"ds": {
"scale": 0.9849732675807669,
"scale": 0.7513148009015777,
"offset": [
-339.6686422794803,
-496.4354678014682
11.112206386364164,
66.47311795454547
]
}
},
"frontendVersion": "1.25.11"
},
"version": 0.4
}
}