WAI-3976-feedback-fixes

WAI-3976

.github/workflows/publish.yml

@@ -7,17 +7,19 @@ on:
     paths:
       - "pyproject.toml"
 
+permissions:
+  issues: write
+
 jobs:
   publish-node:
     name: Publish Custom Node to registry
     runs-on: ubuntu-latest
-    # if this is a forked repository. Skipping the workflow.
-    if: github.event.repository.fork == false 
+    if: ${{ github.repository_owner == 'Bria-AI' }}
     steps:
       - name: Check out code
         uses: actions/checkout@v4
       - name: Publish Custom Node
-        uses: Comfy-Org/publish-node-action@main
+        uses: Comfy-Org/publish-node-action@v1
         with:
           ## Add your own personal access token to your Github Repository secrets and reference it here.
           personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}

.gitignore

@@ -1 +1,2 @@
-*.pyc
+*.pyc
+.idea

Readme.md

@@ -4,14 +4,22 @@
   <img src="./images/Bria Logo.svg" alt="BRIA Logo" width="200"/>
 </p>
 
-This repository provides custom nodes for ComfyUI, enabling direct access to **BRIA's API endpoints** for image generation workflows. **API documentation** is available [**here**](https://bria-ai-api-docs.redoc.ly/#operation//generation/bria-v2/text-to-image). 
+This repository provides custom nodes for ComfyUI, enabling direct access to **BRIA's API endpoints** for image generation and editing workflows. **API documentation** is available [**here**](https://docs.bria.ai/). 
+
+BRIA's APIs and models are built for commercial use and trained on 100% licensed data and does not contain copyrighted materials, such as fictional characters, logos, trademarks, public figures, harmful content, or privacy-infringing content.
 
 An API token is required to use the nodes in your workflows. Get started quickly here
 <a href="https://bria.ai/api/" style="text-decoration:none; vertical-align:middle;">
   <img src="https://img.shields.io/badge/GET%20YOUR%20TOKEN-1000%20Free%20Calls-blue?style=flat-square" alt="Get Your Token" height="20">
 </a>.
 
+for direct API endpoint use, you can find our APIs through partners like [**fal.ai**](https://fal.ai/models?keywords=bria).  
+For source code and weigths access, go to our [**Hugging Face**](https://huggingface.co/briaai) space.
+
 To load a workflow, import the compatible workflow.json files from this [folder](workflows).  
+<p align="center">
+  <img src="./images/background_workflow.png" width="1200"/>
+</p>
 
 
 <!-- Placeholder image of cool workflows. -->
@@ -19,43 +27,46 @@ To load a workflow, import the compatible workflow.json files from this [folder]
 
  <!-- <img src="./images/bria_api_nodes_workflow_diagram.png" alt="all workflows example" width="400"/> <img src="./images/bria_api_nodes_workflow_diagram_2.png" alt="all workflows example" width="400"/> -->
 
-# Coming soon
-
-- [ ] Video Editing
-
 # Available Nodes
 
 ## Image Generation Nodes
+These nodes create high-quality images from text or image prompts, generating photorealistic or artistic results with support for various aspect ratios.
 
-### **Text2Image Base Node**
-This node generates images from text prompts, serving as the foundation for creating visuals based on descriptive input. [[🤗model card](https://huggingface.co/briaai/BRIA-2.3)]
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **Text2Image Base**    | Generates images from text prompts, serving as the foundation for text-based image creation. |
+| **Text2Image Fast**    | Optimized for speed, this node generates images from text prompts with faster results while maintaining quality. |
+| **Text2Image HD**      | Optimized for high-resolution outputs, this node generates detailed and sharp visuals from text prompts. |
+| **Reimagine**          | Guides image generation using both prompts and an input image. Preserve the original structure and depth while introducing new materials, colors, and textures. |
 
 ## Tailored Generation Nodes
-These nodes use pre-trained tailored models to generate images that faithfully reproduce specific visual IP elements or guidelines. [[API docs](https://bria-ai-api-docs.redoc.ly/tag/Tailored-Generation)].
+These nodes use pre-trained tailored models to generate images that faithfully reproduce specific visual IP elements or guidelines.
 
-### **Tailored Gen**
-This node generates images using a trained tailored model, faithfully reproducing specific visual IP elements or guidelines established during model training.
-
-### **Tailored Model Info**
-This node retrieves the **default settings** and **prompt prefix** of a **trained tailored model**. It provides the necessary information to configure and run the model in the **Tailored Gen node**, ensuring consistency with the model's intended behavior.  
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **Tailored Gen**       | Generates images using a trained tailored model, reproducing specific visual IP elements or guidelines. Use the Tailored Model Info node to load the model's default settings. |
+| **Tailored Model Info**| Retrieves the default settings and prompt prefix of a trained tailored model, which can be used to configure the Tailored Gen node. |
+| **Restyle Portrait**   | Transforms the style of a portrait while preserving the person's facial features. |
 
 ## Image Editing Nodes
-These nodes modify specific parts of images, enabling adjustments, while maintaining the integrity of the rest of the image.[[API docs](https://bria-ai-api-docs.redoc.ly/tag/Image-Editing)]
+These nodes modify specific parts of images, enabling adjustments while maintaining the integrity of the rest of the image.
 
-### **Eraser**
-This node is used to remove specific objects or areas from an image by providing a mask. Powered by BRIA's ControlNet inpainting [[🤗model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Inpainting)] [[🤗HF demo](https://huggingface.co/spaces/briaai/BRIA-Eraser-API)].
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **RMBG 2.0 (Remove Background)** | Removes the background from an image, isolating the foreground subject. |
+| **Replace Background**  | Replaces an image’s background with a new one, guided by either a reference image or a prompt. |
+| **Expand Image**        | Expands the dimensions of an image, generating new content to fill the extended areas. |
+| **Eraser**             | Removes specific objects or areas from an image by providing a mask. |
+| **GenFill**            | Generates objects by prompt in a specific region of an image. |
+| **Erase Foreground**    | Removes the foreground from an image, isolating the background. |
 
-### **GenFill**
-This node is used to generate objects by prompt in a specific region of an image. This functionality is powered by BRIA's ControlNet Generative Fill. [[🤗model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Generative-Fill)] [[🤗HF demo](https://huggingface.co/spaces/briaai/BRIA-Generative-Fill-API)]
+## Product Shot Editing Nodes
+These nodes create high-quality product images for eCommerce workflows.
 
-## Product Shot Generation Nodes
-These nodes create high-quality product images for eCommerce workflows. [[API docs](https://bria-ai-api-docs.redoc.ly/tag/Product-Shots-Generation)]
-
-### **ShotByText**
-This node is used to modify the background in an image by providing a prompt, This functionality is powered by BRIA's ControlNet Background-Generation.[[🤗ContrlNet model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-BG-Gen)] [[🤗HF demo](https://huggingface.co/spaces/briaai/Product-Shot-Generation)].
-
-### **ShotByImage**
-This node is used to modify the background in an image by providing a reference image. This functionality is powered by BRIA's ControlNet Background-Generation and BRIA's Image-Prompt. [[🤗ContrlNet model card](https://huggingface.co/briaai/BRIA-2.3-ControlNet-Inpainting)] [[🤗IP-Adapter model card](https://huggingface.co/briaai/Image-Prompt)] [[🤗HF demo](https://huggingface.co/spaces/briaai/Product-Shot-Generation)].
+| Node                   | Description                                                        |
+|------------------------|--------------------------------------------------------------------|
+| **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. |
 
 # Installation
 There are two methods to install the BRIA ComfyUI API nodes:

__init__.py

@@ -1,14 +1,19 @@
-from .nodes import (EraserNode, GenFillNode, ShotByTextNode, ShotByImageNode, TailoredGenNode,
-                     TailoredModelInfoNode, Text2ImageBaseNode, Text2ImageFastNode, Text2ImageHDNode,
+from .nodes import (EraserNode, GenFillNode, ImageExpansionNode, ReplaceBgNode, RmbgNode, RemoveForegroundNode, ShotByTextNode, ShotByImageNode, TailoredGenNode,
+                     TailoredModelInfoNode, Text2ImageBaseNode, Text2ImageFastNode, Text2ImageHDNode, TailoredPortraitNode,
                      ReimagineNode)
 # Map the node class to a name used internally by ComfyUI
 NODE_CLASS_MAPPINGS = {
     "BriaEraser": EraserNode,  # Return the class, not an instance
     "BriaGenFill": GenFillNode,
+    "ImageExpansionNode": ImageExpansionNode,
+    "ReplaceBgNode": ReplaceBgNode,
+    "RmbgNode": RmbgNode,
+    "RemoveForegroundNode": RemoveForegroundNode,
     "ShotByTextNode": ShotByTextNode,
     "ShotByImageNode": ShotByImageNode,
     "BriaTailoredGen": TailoredGenNode,
     "TailoredModelInfoNode": TailoredModelInfoNode,
+    "TailoredPortraitNode": TailoredPortraitNode,
     "Text2ImageBaseNode": Text2ImageBaseNode,
     "Text2ImageFastNode": Text2ImageFastNode,
     "Text2ImageHDNode": Text2ImageHDNode,
@@ -18,10 +23,15 @@ NODE_CLASS_MAPPINGS = {
 NODE_DISPLAY_NAME_MAPPINGS = {
     "BriaEraser": "Bria Eraser",
     "BriaGenFill": "Bria GenFill",
+    "ImageExpansionNode": "Bria Image Expansion",
+    "ReplaceBgNode": "Bria Replace Background",
+    "RmbgNode": "Bria RMBG",
+    "RemoveForegroundNode": "Bria Remove Foreground",
     "ShotByTextNode": "Bria Shot By Text",
     "ShotByImageNode": "Bria Shot By Image",
     "BriaTailoredGen": "Bria Tailored Gen",
     "TailoredModelInfoNode": "Bria Tailored Model Info",
+    "TailoredPortraitNode": "Bria Restyle Portrait",
     "Text2ImageBaseNode": "Bria Text2Image Base",
     "Text2ImageFastNode": "Bria Text2Image Fast",
     "Text2ImageHDNode": "Bria Text2Image HD",

nodes/__init__.py

@@ -1,9 +1,14 @@
 from .eraser_node import EraserNode
 from .generative_fill_node import GenFillNode
+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

nodes/common.py

@@ -5,6 +5,7 @@ import torch
 import base64
 from torchvision.transforms import ToPILImage
 import requests
+import time
 
 def postprocess_image(image):
     result_image = Image.open(io.BytesIO(image))
@@ -44,7 +45,7 @@ def preprocess_mask(mask):
     return mask
 
 
-def process_request(api_url, image, mask, api_key):
+def process_request(api_url, image, mask, api_key, visual_input_content_moderation, visual_output_content_moderation):
     if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
         raise Exception("Please insert a valid API key.")
 
@@ -58,10 +59,12 @@ def process_request(api_url, image, mask, api_key):
     image_base64 = image_to_base64(image)
     mask_base64 = image_to_base64(mask)
 
-    # Prepare the API request payload
+    # Prepare the API request payload for v2 API
     payload = {
-        "file": f"{image_base64}",
-        "mask_file": f"{mask_base64}"
+        "image": image_base64,
+        "mask": mask_base64,
+        "visual_input_content_moderation":visual_input_content_moderation,
+        "visual_output_content_moderation":visual_output_content_moderation
     }
 
     headers = {
@@ -70,13 +73,23 @@ def process_request(api_url, image, mask, api_key):
     }
 
     try:
-        response = requests.post(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 = requests.post(api_url, json=payload, headers=headers) 
+        if response.status_code == 200 or response.status_code == 202:
+            print('Initial request successful, polling for completion...')
             response_dict = response.json()
-            image_response = requests.get(response_dict['result_url'])
+            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)
+            result_image_url = final_response['result']['image_url']
+            
+            # Download and process the result image
+            image_response = requests.get(result_image_url)
             result_image = Image.open(io.BytesIO(image_response.content))
             result_image = result_image.convert("RGBA")
             result_image = np.array(result_image).astype(np.float32) / 255.0
@@ -84,9 +97,51 @@ def process_request(api_url, image, mask, api_key):
             # image_tensor = image_tensor = ToTensor()(output_image)
             # image_tensor = image_tensor.permute(1, 2, 0) / 255.0  # Shape now becomes [1, 2200, 1548, 3]
             # print(f"output tensor shape is: {image_tensor.shape}")
-            return (result_image,)
+            return (result_image,)  
         else:
-            raise Exception(f"Error: API request failed with status code {response.status_code}")
+            raise Exception(f"Error: API request failed with status code {response.status_code} {response.text}")
 
     except Exception as e:
         raise Exception(f"{e}")
+
+
+def poll_status_until_completed(status_url, api_key, timeout=360, check_interval=2):
+    """
+    Poll a status URL until the status is COMPLETED or timeout is reached.
+    
+    Args:
+        status_url (str): The status URL to poll
+        api_key (str): API token for authentication
+        timeout (int): Maximum time to wait in seconds (default: 360)
+        check_interval (int): Time between checks in seconds (default: 2)
+    
+    Returns:
+        dict: The final response containing the result
+    
+    Raises:
+        Exception: If timeout is reached or API request fails
+    """
+    start_time = time.time()
+    headers = {"api_token": api_key}
+    
+    while time.time() - start_time < timeout:
+        try:
+            response = requests.get(status_url, headers=headers)            
+            if response.status_code == 200 or response.status_code == 202:
+                response_dict = response.json()
+                status = response_dict.get("status", "").upper()
+                
+                if status == "COMPLETED":
+                    return response_dict
+                elif status == "ERROR":
+                    raise Exception(f"Request failed: {response_dict}")
+                else:
+                    print(f"Status: {status}, waiting...")
+                    time.sleep(check_interval)
+            else:
+                raise Exception(f"Status check failed with status code {response.status_code}")
+                
+        except requests.exceptions.RequestException as e:
+            raise Exception(f"Error checking status: {e}")
+    
+    raise Exception(f"Timeout reached after {timeout} seconds")

nodes/eraser_node.py

@@ -8,6 +8,10 @@ class EraserNode():
                 "image": ("IMAGE",),  # Input image from another node
                 "mask": ("MASK",),  # Binary mask input
                 "api_key": ("STRING", {"default": "BRIA_API_TOKEN"})  # API Key input with a default value
+            },
+            "optional": {
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
             }
         }
 
@@ -17,9 +21,9 @@ class EraserNode():
     FUNCTION = "execute"  # This is the method that will be executed
 
     def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/eraser"  # Eraser API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/erase"  # Eraser API URL
 
     # Define the execute method as expected by ComfyUI
-    def execute(self, image, mask, api_key):
-        return process_request(self.api_url, image, mask, api_key)
+    def execute(self, image, mask, api_key, visual_input_content_moderation, visual_output_content_moderation):
+        return process_request(self.api_url, image, mask, api_key, visual_input_content_moderation, visual_output_content_moderation)
     

nodes/generative_fill_node.py

@@ -4,7 +4,7 @@ from PIL import Image
 import io
 import torch
 
-from .common import image_to_base64, preprocess_image, preprocess_mask
+from .common import preprocess_image, preprocess_mask, image_to_base64, poll_status_until_completed
 
 
 class GenFillNode():
@@ -17,6 +17,14 @@ class GenFillNode():
                 "prompt": ("STRING",),
                 "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
             },
+            "optional": {
+                "seed": ("INT", {"default": 123456}),
+                "prompt_content_moderation": ("BOOLEAN", {"default": True}), 
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+
+
+            }
         }
 
     RETURN_TYPES = ("IMAGE",)
@@ -25,10 +33,10 @@ class GenFillNode():
     FUNCTION = "execute"  # This is the method that will be executed
 
     def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/gen_fill"  # Eraser API URL
+        self.api_url = "https://engine.prod.bria-api.com/v2/image/edit/gen_fill"
 
     # Define the execute method as expected by ComfyUI
-    def execute(self, image, mask, prompt, api_key):
+    def execute(self, image, mask, prompt, api_key, seed, prompt_content_moderation, visual_input_content_moderation, visual_output_content_moderation):
         if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
             raise Exception("Please insert a valid API key.")
 
@@ -44,11 +52,14 @@ class GenFillNode():
 
         # Prepare the API request payload
         payload = {
-            "file": f"{image_base64}",
-            "mask_file": f"{mask_base64}",
+            "image": image_base64,
+            "mask": mask_base64,
             "prompt": prompt,
             "negative_prompt": "blurry",
-            "sync": True
+            "seed": seed,
+            "prompt_content_moderation":prompt_content_moderation,
+            "visual_input_content_moderation":visual_input_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation
         }
 
         headers = {
@@ -57,20 +68,30 @@ class GenFillNode():
         }
 
         try:
+            # Send initial request to get status URL
             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
+            
+            if response.status_code == 200 or response.status_code == 202:
+                print('Initial genfill request successful, polling for completion...')
                 response_dict = response.json()
-                image_response = requests.get(response_dict['urls'][0])
+                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)                
+                result_image_url = final_response['result']['image_url']
+                image_response = requests.get(result_image_url)
                 result_image = Image.open(io.BytesIO(image_response.content))
                 result_image = result_image.convert("RGB")
                 result_image = np.array(result_image).astype(np.float32) / 255.0
                 result_image = torch.from_numpy(result_image)[None,]
                 return (result_image,)
             else:
-                raise Exception(f"Error: API request failed with status code {response.status_code}")
+                raise Exception(f"Error: API request failed with status code {response.status_code} {response.text}")
 
         except Exception as e:
             raise Exception(f"{e}")

nodes/image_expansion_node.py

@@ -0,0 +1,135 @@
+import numpy as np
+import requests
+from PIL import Image
+import io
+import torch
+
+from .common import image_to_base64, preprocess_image, poll_status_until_completed
+
+
+class ImageExpansionNode():
+    @classmethod
+    def INPUT_TYPES(self):
+        return {
+            "required": {
+                "image": ("IMAGE",),  # Input image from another node
+                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
+            },
+            
+            "optional": {
+                "original_image_size": ("STRING",),
+                "original_image_location": ("STRING",),
+                "canvas_size": ("STRING", {"default": "1000, 1000"}),
+                "aspect_ratio": (["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9","None"], {"default": "None"}),
+                "prompt": ("STRING", {"default": ""}),
+                "seed": ("INT", {"default": 681794}),
+                "negative_prompt": ("STRING", {"default": "Ugly, mutated"}),
+                "prompt_content_moderation": ("BOOLEAN", {"default": False}),
+                "preserve_alpha": ("BOOLEAN", {"default": True}),
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}),
+                "visual_output_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/v2/image/edit/expand"  # Image Expansion API URL
+
+    # Define the execute method as expected by ComfyUI
+    def execute(self, image, 
+                original_image_size,
+                original_image_location,
+                canvas_size,
+                aspect_ratio,
+                prompt,
+                seed,
+                negative_prompt,
+                prompt_content_moderation,
+                preserve_alpha,
+                visual_input_content_moderation,
+                visual_output_content_moderation,
+                api_key):
+        if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
+            raise Exception("Please insert a valid API key.")
+        original_image_size = [int(x.strip()) for x in original_image_size.split(",")] if original_image_size else ()
+        original_image_location = [int(x.strip()) for x in original_image_location.split(",")] if original_image_location else ()
+        canvas_size = [int(x.strip()) for x in canvas_size.split(",")] if canvas_size else ()
+        
+        if negative_prompt == "":
+            negative_prompt = " " # hack to avoid error in triton which expects non-empty string
+
+        # Check if image and mask are tensors, if so, convert to NumPy arrays
+        if isinstance(image, torch.Tensor):
+            image = preprocess_image(image)
+
+        # Convert the image directly to Base64 string
+        image_base64 = image_to_base64(image)
+        if aspect_ratio and aspect_ratio != "None":
+            payload = {
+            "image": image_base64,
+            "aspect_ratio": aspect_ratio,
+            "prompt": prompt,
+            "negative_prompt": negative_prompt,
+            "seed": seed,
+            "prompt_content_moderation": prompt_content_moderation,
+            "preserve_alpha": preserve_alpha,
+            "visual_input_content_moderation": visual_input_content_moderation,
+            "visual_output_content_moderation": visual_output_content_moderation
+        }
+        else:
+            payload = {
+                "image": image_base64,
+                "original_image_size": original_image_size,
+                "original_image_location": original_image_location,
+                "canvas_size": canvas_size,
+                "prompt": prompt,
+                "negative_prompt": negative_prompt,
+                "seed": seed,
+                "prompt_content_moderation": prompt_content_moderation,
+                "preserve_alpha": preserve_alpha,
+                "visual_input_content_moderation": visual_input_content_moderation,
+                "visual_output_content_moderation": visual_output_content_moderation
+            }
+
+        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 image expansion 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}")
+                
+                # Poll status URL until completion
+                final_response = poll_status_until_completed(status_url, api_key)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                # Download and process the result image
+                image_response = requests.get(result_image_url)
+                result_image = Image.open(io.BytesIO(image_response.content))
+                result_image = result_image.convert("RGB")
+                result_image = np.array(result_image).astype(np.float32) / 255.0
+                result_image = torch.from_numpy(result_image)[None,]
+                
+                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}")

nodes/reimagine_node.py

@@ -20,6 +20,7 @@ class ReimagineNode():
                 "tailored_model_id": ("STRING", ),
                 "tailored_model_influence": ("FLOAT", {"default": 0.5}),
                 "tailored_generation_prefix": ("STRING",), # if used with tailored, possibly get this from the tailored model info node
+                "content_moderation": ("INT", {"default": 0}),
             }
         }
 
@@ -35,8 +36,8 @@ class ReimagineNode():
             self, api_key, prompt, seed, 
             steps_num, fast, structure_ref_influence, structure_image=None,
             tailored_model_id=None, tailored_model_influence=None, tailored_generation_prefix=None,
-        ):
-        fast = bool(fast)
+            content_moderation=0,
+        ):        
         payload = {
             "prompt": tailored_generation_prefix + prompt,
             "num_results": 1,
@@ -44,6 +45,7 @@ class ReimagineNode():
             "seed": seed,
             "steps_num": steps_num,
             "include_generation_prefix": False,
+            "content_moderation": content_moderation,
         }
         if structure_image is not None:
             structure_image = preprocess_image(structure_image)

nodes/remove_foreground_node.py

@@ -0,0 +1,90 @@
+import numpy as np
+import requests
+from PIL import Image
+import io
+import torch
+
+from .common import preprocess_image, image_to_base64, poll_status_until_completed
+
+
+class RemoveForegroundNode():
+    @classmethod
+    def INPUT_TYPES(self):
+        return {
+            "required": {
+                "image": ("IMAGE",),  # Input image from another node
+                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
+            },
+            "optional": {
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+                "preserve_alpha": ("BOOLEAN", {"default": True}), 
+            }
+        }
+
+    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/v2/image/edit/erase_foreground"  # remove foreground API URL
+
+    # Define the execute method as expected by ComfyUI
+    def execute(self, image, visual_input_content_moderation, visual_output_content_moderation, preserve_alpha, 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)
+
+        # Prepare the API request payload
+        # temporary save the image to /tmp
+        # temp_img_path = "/tmp/temp_img.jpeg"
+        # image.save(temp_img_path, format="JPEG")
+        
+#         files=[('file',('temp_img.jpeg', open(temp_img_path, 'rb'),'image/jpeg'))
+#   ]
+        payload = {
+            "image": image_to_base64(image),
+            "visual_input_content_moderation": visual_input_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation,
+            "preserve_alpha": preserve_alpha
+        }
+
+        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 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}")
+                
+                # Poll status URL until completion
+                final_response = poll_status_until_completed(status_url, api_key)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                image_response = requests.get(result_image_url)
+                result_image = Image.open(io.BytesIO(image_response.content))
+                result_image = np.array(result_image).astype(np.float32) / 255.0
+                result_image = torch.from_numpy(result_image)[None,]
+                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}")

nodes/replace_bg_node.py

@@ -0,0 +1,123 @@
+import numpy as np
+import requests
+from PIL import Image
+import io
+import torch
+
+from .common import image_to_base64, preprocess_image, preprocess_mask, poll_status_until_completed
+
+
+class ReplaceBgNode():
+    @classmethod
+    def INPUT_TYPES(self):
+        return {
+            "required": {
+                "image": ("IMAGE",),  # Input image from another node
+                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
+            },
+            "optional": {
+                "mode": (["base", "fast", "high_control"], {"default": "base"}),
+                "prompt": ("STRING",),
+                "ref_images": ("IMAGE",),
+                "refine_prompt": ("BOOLEAN", {"default": True}), 
+                "enhance_ref_images": ("BOOLEAN", {"default": True}), 
+                "original_quality": ("BOOLEAN", {"default": False}), 
+                "negative_prompt": ("STRING", {"default": None}), 
+                "seed": ("INT", {"default": 681794}),
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+                "prompt_content_moderation": ("BOOLEAN", {"default": False}),
+                "force_background_detection": ("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/v2/image/edit/replace_background"  # Replace BG API URL
+
+    # Define the execute method as expected by ComfyUI
+    def execute(self, image, mode,
+                refine_prompt,
+                original_quality,
+                negative_prompt,
+                seed,
+                api_key,
+                visual_output_content_moderation,
+                prompt_content_moderation,
+                enhance_ref_images,
+                force_background_detection,
+                prompt=None,
+                ref_images=None,):
+        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)
+
+        # Convert the image to Base64 string
+        image_base64 = image_to_base64(image)
+        
+        if ref_images is not None:
+            ref_images = preprocess_image(ref_images)
+            ref_images = [image_to_base64(ref_images)]
+        else:
+            ref_images=[]
+
+        # Prepare the API request payload for v2 API
+        payload = {
+            "image": image_base64,
+            "mode": mode,
+            "prompt": prompt,
+            "ref_images":ref_images,
+            "refine_prompt": refine_prompt,
+            "original_quality": original_quality,
+            "negative_prompt": negative_prompt,
+            "seed": seed,
+            "prompt_content_moderation": prompt_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation,
+            "enhance_ref_images":enhance_ref_images,
+            "force_background_detection": force_background_detection        
+        }   
+
+        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 replace background 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}")
+                
+                # Poll status URL until completion
+                final_response = poll_status_until_completed(status_url, api_key)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                # Download and process the result image
+                image_response = requests.get(result_image_url)
+                result_image = Image.open(io.BytesIO(image_response.content))
+                result_image = result_image.convert("RGB")
+                result_image = np.array(result_image).astype(np.float32) / 255.0
+                result_image = torch.from_numpy(result_image)[None,]
+                
+                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}")

nodes/rmbg_node.py

@@ -0,0 +1,87 @@
+import numpy as np
+import requests
+from PIL import Image
+import io
+import torch
+
+from .common import preprocess_image, image_to_base64, poll_status_until_completed
+
+class RmbgNode():
+    @classmethod
+    def INPUT_TYPES(self):
+        return {
+            "required": {
+                "image": ("IMAGE",),  # Input image from another node
+                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
+            },
+            "optional": {
+                "visual_input_content_moderation": ("BOOLEAN", {"default": False}), 
+                "visual_output_content_moderation": ("BOOLEAN", {"default": False}), 
+                "preserve_alpha": ("BOOLEAN", {"default": True}), 
+            
+            }               
+        }
+
+    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/v2/image/edit/remove_background"  # RMBG API URL
+
+    # Define the execute method as expected by ComfyUI
+    def execute(self, image, visual_input_content_moderation, visual_output_content_moderation, preserve_alpha, 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,
+            "visual_input_content_moderation": visual_input_content_moderation,
+            "visual_output_content_moderation":visual_output_content_moderation,
+            "preserve_alpha":preserve_alpha
+        }
+
+        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 RMBG 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)
+                
+                # Get the result image URL
+                result_image_url = final_response['result']['image_url']
+                
+                # Download and process the result image
+                image_response = requests.get(result_image_url)
+                result_image = Image.open(io.BytesIO(image_response.content))
+                result_image = np.array(result_image).astype(np.float32) / 255.0
+                result_image = torch.from_numpy(result_image)[None,]
+                
+                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}")

nodes/shot_by_image_node.py

@@ -12,7 +12,10 @@ class ShotByImageNode():
                 "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",)
@@ -24,7 +27,7 @@ class ShotByImageNode():
         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, ):
+    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.")
 
@@ -45,7 +48,8 @@ class ShotByImageNode():
             "enhance_ref_image": enhance_ref_image,
             "placement_type": "original",
             "original_quality": True, 
-            "sync": True
+            "sync": True,
+            "content_moderation": content_moderation
         }
         headers = {
             "Content-Type": "application/json",

nodes/shot_by_text_node.py

@@ -10,9 +10,12 @@ class ShotByTextNode():
             "required": {
                 "image": ("IMAGE",),  # Input image from another node
                 "scene_description": ("STRING",),
-                "optimize_description": ("INT", {"default": 1}),
+                "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",)
@@ -24,7 +27,7 @@ class ShotByTextNode():
         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, optimize_description, ):
+    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.")
 
@@ -32,15 +35,16 @@ class ShotByTextNode():
         if isinstance(image, torch.Tensor):
             image = preprocess_image(image)
 
-        optimize_description = bool(optimize_description)
         image_base64 = image_to_base64(image)
         payload = {
             "file": image_base64,
             "scene_description": scene_description,
-            "optimize_description": optimize_description,
+            "mode": mode,
             "placement_type": "original",
             "original_quality": True,
-            "sync": True
+            "sync": True,
+            "content_moderation": content_moderation
+
         }
         headers = {
             "Content-Type": "application/json",

nodes/tailored_gen_node.py

@@ -26,6 +26,7 @@ class TailoredGenNode():
                 "guidance_method_2": (["controlnet_canny", "controlnet_depth", "controlnet_recoloring", "controlnet_color_grid"], {"default": "controlnet_canny"}),
                 "guidance_method_2_scale": ("FLOAT", {"default": 1.0}),
                 "guidance_method_2_image": ("IMAGE", ),
+                "content_moderation": ("INT", {"default": 0}),
             }
         }
 
@@ -42,8 +43,8 @@ class TailoredGenNode():
             seed, model_influence, negative_prompt, fast, steps_num,
             guidance_method_1=None, guidance_method_1_scale=None, guidance_method_1_image=None,
             guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
+            content_moderation=0,
         ):
-        fast = bool(fast)
         payload = {
             "prompt": generation_prefix + prompt,
             "num_results": 1,
@@ -55,6 +56,7 @@ class TailoredGenNode():
             "fast": fast,
             "steps_num": steps_num,
             "include_generation_prefix": False,
+            "content_moderation": content_moderation,
         }
         if guidance_method_1_image is not None:
             guidance_method_1_image = preprocess_image(guidance_method_1_image)

nodes/tailored_portrait_node.py

@@ -0,0 +1,75 @@
+import numpy as np
+import requests
+from PIL import Image
+import io
+import torch
+
+from .common import image_to_base64, preprocess_image
+
+class TailoredPortraitNode():
+    @classmethod
+    def INPUT_TYPES(self):
+        return {
+            "required": {
+                "image": ("IMAGE",),  # Input image from another node
+                "tailored_model_id": ("INT",),
+                "api_key": ("STRING", {"default": "BRIA_API_TOKEN"}), # API Key input with a default value
+            },
+            "optional": {
+                "seed": ("INT", {"default": 123456}),
+                "tailored_model_influence": ("FLOAT", {"default": 0.9}),
+                "id_strength": ("FLOAT", {"default": 0.7}),
+            }
+        }
+
+    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/tailored-gen/restyle_portrait"  # Eraser API URL
+
+    # Define the execute method as expected by ComfyUI
+    def execute(self, image, tailored_model_id, api_key, seed, tailored_model_influence, id_strength):
+        if api_key.strip() == "" or api_key.strip() == "BRIA_API_TOKEN":
+            raise Exception("Please insert a valid API key.")
+
+        # Convert the image and mask directly to  if isinstance(image, torch.Tensor):
+        if isinstance(image, torch.Tensor):
+            image = preprocess_image(image)
+            
+        image_base64 = image_to_base64(image)
+
+        # Prepare the API request payload
+        payload = {
+            "id_image_file": f"{image_base64}",
+            "tailored_model_id": tailored_model_id,
+            "tailored_model_influence": tailored_model_influence,
+            "id_strength": id_strength,
+            "seed": seed
+        }
+
+        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['image_res'])
+                result_image = Image.open(io.BytesIO(image_response.content))
+                result_image = result_image.convert("RGB")
+                result_image = np.array(result_image).astype(np.float32) / 255.0
+                result_image = torch.from_numpy(result_image)[None,]
+                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}")

nodes/text_2_image_base_node.py

@@ -28,6 +28,7 @@ class Text2ImageBaseNode():
                 "image_prompt_mode": (["regular", "style_only"], {"default": "regular"}),
                 "image_prompt_image": ("IMAGE", ),
                 "image_prompt_scale": ("FLOAT", {"default": 1.0}),
+                "content_moderation": ("INT", {"default": 0}),
             }
         }
 
@@ -37,7 +38,7 @@ class Text2ImageBaseNode():
     FUNCTION = "execute"  # This is the method that will be executed
 
     def __init__(self):
-        self.api_url = "https://engine.prod.bria-api.com/v1/text-to-image/base/2.3" #"http://0.0.0.0:5000/v1/text-to-image/base/2.3"
+        self.api_url = "https://engine.prod.bria-api.com/v1/text-to-image/base/3.2" 
 
     def execute(
             self, api_key, prompt, aspect_ratio, seed, negative_prompt, 
@@ -45,8 +46,8 @@ class Text2ImageBaseNode():
             guidance_method_1=None, guidance_method_1_scale=None, guidance_method_1_image=None,
             guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
             image_prompt_mode=None, image_prompt_image=None, image_prompt_scale=None,
+            content_moderation=0,
         ):
-        prompt_enhancement = bool(prompt_enhancement)
         payload = {
             "prompt": prompt,
             "num_results": 1,
@@ -57,6 +58,7 @@ class Text2ImageBaseNode():
             "steps_num": steps_num,
             "text_guidance_scale": text_guidance_scale,
             "prompt_enhancement": prompt_enhancement,
+            "content_moderation": content_moderation,
         }
         if medium != "none":
             payload["medium"] = medium

nodes/text_2_image_fast_node.py

@@ -25,6 +25,7 @@ class Text2ImageFastNode():
                 "image_prompt_mode": (["regular", "style_only"], {"default": "regular"}),
                 "image_prompt_image": ("IMAGE", ),
                 "image_prompt_scale": ("FLOAT", {"default": 1.0}),
+                "content_moderation": ("INT", {"default": 0}),
             }
         }
 
@@ -42,8 +43,8 @@ class Text2ImageFastNode():
             guidance_method_1=None, guidance_method_1_scale=None, guidance_method_1_image=None,
             guidance_method_2=None, guidance_method_2_scale=None, guidance_method_2_image=None,
             image_prompt_mode=None, image_prompt_image=None, image_prompt_scale=None,
+            content_moderation=0,
         ):
-        prompt_enhancement = bool(prompt_enhancement)
         payload = {
             "prompt": prompt,
             "num_results": 1,
@@ -52,6 +53,7 @@ class Text2ImageFastNode():
             "seed": seed,
             "steps_num": steps_num,
             "prompt_enhancement": prompt_enhancement,
+            "content_moderation": content_moderation,
         }
         if guidance_method_1_image is not None:
             guidance_method_1_image = preprocess_image(guidance_method_1_image)

nodes/text_2_image_hd_node.py

@@ -19,6 +19,7 @@ class Text2ImageHDNode():
                 "prompt_enhancement": ("INT", {"default": 0}),
                 "text_guidance_scale": ("INT", {"default": 5}),
                 "medium": (["photography", "art", "none"], {"default": "none"}),
+                "content_moderation": ("INT", {"default": 0}),
             }
         }
 
@@ -32,9 +33,8 @@ class Text2ImageHDNode():
 
     def execute(
             self, api_key, prompt, aspect_ratio, seed, negative_prompt, 
-            steps_num, prompt_enhancement, text_guidance_scale, medium,
+            steps_num, prompt_enhancement, text_guidance_scale, medium, content_moderation=0,
         ):
-        prompt_enhancement = bool(prompt_enhancement)
         payload = {
             "prompt": prompt,
             "num_results": 1,
@@ -45,6 +45,7 @@ class Text2ImageHDNode():
             "steps_num": steps_num,
             "text_guidance_scale": text_guidance_scale,
             "prompt_enhancement": prompt_enhancement,
+            "content_moderation": content_moderation,
         }
         if medium != "none":
             payload["medium"] = medium

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-bria-api"
 description = "Custom nodes for ComfyUI using BRIA's API."
-version = "2.0.0"
+version = "2.1.0"
 license = {file = "LICENSE"}
 
 [project.urls]

workflows/background_generation_workflow.json

@@ -0,0 +1 @@
+{"last_node_id":39,"last_link_id":65,"nodes":[{"id":34,"type":"LoadImage","pos":[19.94045066833496,1075.806640625],"size":[315,314],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[61],"slot_index":0,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":null,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["quirky-red-brick-brick-wallpaper.jpg","image"]},{"id":36,"type":"PreviewImage","pos":[468.7108154296875,1210.288818359375],"size":[210,246],"flags":{},"order":5,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":63,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":33,"type":"PreviewImage","pos":[1317.4083251953125,1118.4864501953125],"size":[210,246],"flags":{},"order":8,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":59,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":31,"type":"PreviewImage","pos":[1668.734619140625,796.7755737304688],"size":[210,246],"flags":{},"order":10,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":57,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":29,"type":"PreviewImage","pos":[872.8858032226562,679.9429321289062],"size":[210,246],"flags":{},"order":6,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":55,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":28,"type":"LoadImage","pos":[29.629886627197266,676.8370361328125],"size":[315,314],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[54],"slot_index":0,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":null,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["pexels-photo-1808399.jpeg","image"]},{"id":35,"type":"RemoveForegroundNode","pos":[414.2638854980469,1079.1705322265625],"size":[315,58],"flags":{},"order":3,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":61,"localized_name":"image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[62,63],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"RemoveForegroundNode"},"widgets_values":["BRIA_API_TOKEN"]},{"id":32,"type":"ReplaceBgNode","pos":[834.6115112304688,1063.0406494140625],"size":[315,294],"flags":{},"order":7,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":65,"localized_name":"image"},{"name":"ref_image","type":"IMAGE","link":62,"shape":7,"localized_name":"ref_image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[59,64],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"ReplaceBgNode"},"widgets_values":["BRIA_API_TOKEN",false,"",true,true,true,false,"",1978,"randomize"]},{"id":30,"type":"ImageExpansionNode","pos":[1265.001220703125,798.8323974609375],"size":[315,226],"flags":{},"order":9,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":64,"localized_name":"image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[57],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"ImageExpansionNode"},"widgets_values":["600,760","200, 0","BRIA_API_TOKEN","1200, 800","",1729,"randomize","Ugly, mutated"]},{"id":38,"type":"Note","pos":[436.7110900878906,566.2047119140625],"size":[306.28387451171875,58],"flags":{},"order":2,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["You can get your BRIA API token at:\nhttps://bria.ai/api/"],"color":"#432","bgcolor":"#653"},{"id":27,"type":"RmbgNode","pos":[430.8815002441406,678.7727661132812],"size":[315,58],"flags":{},"order":4,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":54,"localized_name":"image"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[55,65],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"RmbgNode"},"widgets_values":["BRIA_API_TOKEN"]}],"links":[[51,5,0,15,2,"STRING"],[54,28,0,27,0,"IMAGE"],[55,27,0,29,0,"IMAGE"],[57,30,0,31,0,"IMAGE"],[59,32,0,33,0,"IMAGE"],[61,34,0,35,0,"IMAGE"],[62,35,0,32,1,"IMAGE"],[63,35,0,36,0,"IMAGE"],[64,32,0,30,0,"IMAGE"],[65,27,0,32,0,"IMAGE"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.8140274938684037,"offset":[101.53311990208498,-477.0342684311694]},"node_versions":{"comfyui-bria-api":"c72754d15b53a13ee0c0419d70401232c56b7fdb","comfy-core":"v0.3.8-1-gc441048","ComfyUI-Jjk-Nodes":"b3c99bb78a99551776b5eab1a820e1cd58f84f31"}},"version":0.4}

workflows/eraser_genfill_workflow.json

@@ -0,0 +1 @@
+{"last_node_id":41,"last_link_id":62,"nodes":[{"id":14,"type":"Note","pos":[478,444],"size":[396.80859375,61.8046875],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["Right click, and choose \"Open in Mask Editor\" to draw a mask of areas you want to erase."],"color":"#432","bgcolor":"#653"},{"id":15,"type":"Note","pos":[1080.3062744140625,445.9654541015625],"size":[306.28387451171875,58],"flags":{},"order":1,"mode":0,"inputs":[],"outputs":[],"properties":{},"widgets_values":["You can get your BRIA API token at:\nhttps://bria.ai/api/"],"color":"#432","bgcolor":"#653"},{"id":30,"type":"LoadImage","pos":[479,572],"size":[395.7845153808594,352.8512268066406],"flags":{},"order":2,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[56],"slot_index":0,"shape":3,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":[57],"slot_index":1,"shape":3,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["clipspace/clipspace-mask-4068974.800000012.png [input]","image"]},{"id":37,"type":"PreviewImage","pos":[1504.4755859375,568.9967651367188],"size":[438.50262451171875,376.8338317871094],"flags":{},"order":6,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":58,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":33,"type":"PreviewImage","pos":[1502.785888671875,1078.3564453125],"size":[433.29193115234375,357.1255187988281],"flags":{},"order":7,"mode":0,"inputs":[{"name":"images","type":"IMAGE","link":54,"localized_name":"images"}],"outputs":[],"properties":{"Node name for S&R":"PreviewImage"},"widgets_values":[]},{"id":40,"type":"LoadImage","pos":[541.1226806640625,1079.39697265625],"size":[315,314],"flags":{},"order":3,"mode":0,"inputs":[],"outputs":[{"name":"IMAGE","type":"IMAGE","links":[61],"slot_index":0,"localized_name":"IMAGE"},{"name":"MASK","type":"MASK","links":[62],"slot_index":1,"localized_name":"MASK"}],"properties":{"Node name for S&R":"LoadImage"},"widgets_values":["clipspace/clipspace-mask-4411367.100000024.png [input]","image"]},{"id":34,"type":"BriaGenFill","pos":[1032.416748046875,1073.984619140625],"size":[315,102],"flags":{},"order":5,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":61,"localized_name":"image"},{"name":"mask","type":"MASK","link":62,"localized_name":"mask"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[54],"slot_index":0,"shape":3,"localized_name":"output_image"}],"properties":{"Node name for S&R":"BriaGenFill"},"widgets_values":["a blue coffee mug","BRIA_API_TOKEN"]},{"id":36,"type":"BriaEraser","pos":[1068.6063232421875,574.6080322265625],"size":[315,78],"flags":{},"order":4,"mode":0,"inputs":[{"name":"image","type":"IMAGE","link":56,"localized_name":"image"},{"name":"mask","type":"MASK","link":57,"localized_name":"mask"}],"outputs":[{"name":"output_image","type":"IMAGE","links":[58],"slot_index":0,"localized_name":"output_image"}],"properties":{"Node name for S&R":"BriaEraser"},"widgets_values":["BRIA_API_TOKEN"]}],"links":[[54,34,0,33,0,"IMAGE"],[56,30,0,36,0,"IMAGE"],[57,30,1,36,1,"MASK"],[58,36,0,37,0,"IMAGE"],[61,40,0,34,0,"IMAGE"],[62,40,1,34,1,"MASK"]],"groups":[],"config":{},"extra":{"ds":{"scale":0.6727499949325677,"offset":[131.53042816003972,-419.53430403204317]}},"version":0.4}

workflows/eraser_workflow.json

@@ -1,203 +0,0 @@
-{
-  "last_node_id": 28,
-  "last_link_id": 42,
-  "nodes": [
-    {
-      "id": 15,
-      "type": "Note",
-      "pos": {
-        "0": 1021,
-        "1": 280
-      },
-      "size": {
-        "0": 311.8914794921875,
-        "1": 153.69827270507812
-      },
-      "flags": {},
-      "order": 0,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "The default BRIA API key for ComfyUI (BRIA_ComfyUI_Key) offers 10,000 API calls for the entire community. \n\nGet your own token at:\nhttps://bria.ai/api/"
-      ],
-      "color": "#432",
-      "bgcolor": "#653"
-    },
-    {
-      "id": 13,
-      "type": "PreviewImage",
-      "pos": {
-        "0": 1410,
-        "1": 160
-      },
-      "size": {
-        "0": 474.7605895996094,
-        "1": 303.117919921875
-      },
-      "flags": {},
-      "order": 4,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "link": 42
-        }
-      ],
-      "outputs": [],
-      "properties": {
-        "Node name for S&R": "PreviewImage"
-      }
-    },
-    {
-      "id": 21,
-      "type": "LoadImage",
-      "pos": {
-        "0": 477,
-        "1": 156
-      },
-      "size": {
-        "0": 408.4602355957031,
-        "1": 333.19830322265625
-      },
-      "flags": {},
-      "order": 1,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            40
-          ],
-          "slot_index": 0,
-          "shape": 3
-        },
-        {
-          "name": "MASK",
-          "type": "MASK",
-          "links": [
-            41
-          ],
-          "slot_index": 1,
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "LoadImage"
-      },
-      "widgets_values": [
-        "clipspace/clipspace-mask-82245.69999998808.png [input]",
-        "image"
-      ]
-    },
-    {
-      "id": 28,
-      "type": "BriaEraser",
-      "pos": {
-        "0": 1022,
-        "1": 159
-      },
-      "size": {
-        "0": 315,
-        "1": 78
-      },
-      "flags": {},
-      "order": 3,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 40
-        },
-        {
-          "name": "mask",
-          "type": "MASK",
-          "link": 41
-        }
-      ],
-      "outputs": [
-        {
-          "name": "output_image",
-          "type": "IMAGE",
-          "links": [
-            42
-          ],
-          "slot_index": 0,
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "BriaEraser"
-      },
-      "widgets_values": [
-        "BRIA_ComfyUI_Key"
-      ]
-    },
-    {
-      "id": 14,
-      "type": "Note",
-      "pos": {
-        "0": 483,
-        "1": 39
-      },
-      "size": [
-        396.80859375,
-        61.8046875
-      ],
-      "flags": {},
-      "order": 2,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "Right click, and choose \"Open in Mask Editor\" to draw a mask of areas you want animated more. "
-      ],
-      "color": "#432",
-      "bgcolor": "#653"
-    }
-  ],
-  "links": [
-    [
-      40,
-      21,
-      0,
-      28,
-      0,
-      "IMAGE"
-    ],
-    [
-      41,
-      21,
-      1,
-      28,
-      1,
-      "MASK"
-    ],
-    [
-      42,
-      28,
-      0,
-      13,
-      0,
-      "IMAGE"
-    ]
-  ],
-  "groups": [],
-  "config": {},
-  "extra": {
-    "ds": {
-      "scale": 1,
-      "offset": [
-        -293.75,
-        167.65625
-      ]
-    }
-  },
-  "version": 0.4
-}

workflows/genfill_workflow.json

@@ -1,204 +0,0 @@
-{
-  "last_node_id": 35,
-  "last_link_id": 55,
-  "nodes": [
-    {
-      "id": 33,
-      "type": "PreviewImage",
-      "pos": {
-        "0": 1420,
-        "1": 574
-      },
-      "size": {
-        "0": 433.29193115234375,
-        "1": 357.1255187988281
-      },
-      "flags": {},
-      "order": 4,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "link": 54
-        }
-      ],
-      "outputs": [],
-      "properties": {
-        "Node name for S&R": "PreviewImage"
-      }
-    },
-    {
-      "id": 30,
-      "type": "LoadImage",
-      "pos": {
-        "0": 479,
-        "1": 572
-      },
-      "size": {
-        "0": 395.7845153808594,
-        "1": 352.8512268066406
-      },
-      "flags": {},
-      "order": 0,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            53
-          ],
-          "slot_index": 0,
-          "shape": 3
-        },
-        {
-          "name": "MASK",
-          "type": "MASK",
-          "links": [
-            55
-          ],
-          "slot_index": 1,
-          "shape": 3
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "LoadImage"
-      },
-      "widgets_values": [
-        "clipspace/clipspace-mask-1438488.400000006.png [input]",
-        "image"
-      ]
-    },
-    {
-      "id": 14,
-      "type": "Note",
-      "pos": {
-        "0": 478,
-        "1": 444
-      },
-      "size": {
-        "0": 396.80859375,
-        "1": 61.8046875
-      },
-      "flags": {},
-      "order": 1,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "Right click, and choose \"Open in Mask Editor\" to draw a mask of areas you want to erase."
-      ],
-      "color": "#432",
-      "bgcolor": "#653"
-    },
-    {
-      "id": 15,
-      "type": "Note",
-      "pos": {
-        "0": 983,
-        "1": 440
-      },
-      "size": {
-        "0": 306.28387451171875,
-        "1": 58
-      },
-      "flags": {},
-      "order": 2,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "You can get your BRIA API token at:\nhttps://bria.ai/api/"
-      ],
-      "color": "#432",
-      "bgcolor": "#653"
-    },
-    {
-      "id": 34,
-      "type": "BriaGenFill",
-      "pos": {
-        "0": 992,
-        "1": 572
-      },
-      "size": {
-        "0": 315,
-        "1": 102
-      },
-      "flags": {},
-      "order": 3,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 53
-        },
-        {
-          "name": "mask",
-          "type": "MASK",
-          "link": 55
-        }
-      ],
-      "outputs": [
-        {
-          "name": "output_image",
-          "type": "IMAGE",
-          "links": [
-            54
-          ],
-          "shape": 3,
-          "slot_index": 0
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "BriaGenFill"
-      },
-      "widgets_values": [
-        "a beautiful paint brush",
-        "BRIA_API_TOKEN"
-      ]
-    }
-  ],
-  "links": [
-    [
-      53,
-      30,
-      0,
-      34,
-      0,
-      "IMAGE"
-    ],
-    [
-      54,
-      34,
-      0,
-      33,
-      0,
-      "IMAGE"
-    ],
-    [
-      55,
-      30,
-      1,
-      34,
-      1,
-      "MASK"
-    ]
-  ],
-  "groups": [],
-  "config": {},
-  "extra": {
-    "ds": {
-      "scale": 0.8264462809917364,
-      "offset": [
-        -266.96526103236687,
-        114.47857424738714
-      ]
-    }
-  },
-  "version": 0.4
-}

workflows/product shot generation_workflow.json

@@ -293,4 +293,4 @@
     }
   },
   "version": 0.4
-}
+}

workflows/text_to_image_workflow.json

@@ -0,0 +1,169 @@
+{
+  "last_node_id": 13,
+  "last_link_id": 11,
+  "nodes": [
+    {
+      "id": 12,
+      "type": "LoadImage",
+      "pos": [
+        669.7035522460938,
+        136.97129821777344
+      ],
+      "size": [
+        315,
+        314
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            10
+          ],
+          "slot_index": 0
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "pexels-photo-3246665.png",
+        "image"
+      ]
+    },
+    {
+      "id": 11,
+      "type": "PreviewImage",
+      "pos": [
+        1587.27001953125,
+        97.39167022705078
+      ],
+      "size": [
+        210,
+        246
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 11
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 10,
+      "type": "Text2ImageFastNode",
+      "pos": [
+        1058.320556640625,
+        96.64427185058594
+      ],
+      "size": [
+        438.71258544921875,
+        394.27716064453125
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "guidance_method_1_image",
+          "type": "IMAGE",
+          "link": null,
+          "shape": 7
+        },
+        {
+          "name": "guidance_method_2_image",
+          "type": "IMAGE",
+          "link": null,
+          "shape": 7
+        },
+        {
+          "name": "image_prompt_image",
+          "type": "IMAGE",
+          "link": 10,
+          "shape": 7
+        }
+      ],
+      "outputs": [
+        {
+          "name": "output_image",
+          "type": "IMAGE",
+          "links": [
+            11
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "Text2ImageFastNode"
+      },
+      "widgets_values": [
+        "BRIA_API_TOKEN",
+        "A drawing of a lion on a table.\t",
+        "4:3",
+        990,
+        "randomize",
+        8,
+        0,
+        "controlnet_canny",
+        1,
+        "controlnet_canny",
+        1,
+        "regular",
+        1
+      ]
+    }
+  ],
+  "links": [
+    [
+      10,
+      12,
+      0,
+      10,
+      2,
+      "IMAGE"
+    ],
+    [
+      11,
+      10,
+      0,
+      11,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.7513148009015777,
+      "offset": [
+        11.112206386364164,
+        66.47311795454547
+      ]
+    },
+    "node_versions": {
+      "comfy-core": "v0.3.10-42-gff83865",
+      "comfyui-bria-api": "499ec5d104cc5110407eafce468ce1d47ac168b3"
+    },
+    "VHS_latentpreview": false,
+    "VHS_latentpreviewrate": 0
+  },
+  "version": 0.4
+}