Delete custom_nodes

custom_nodes/comfyui-reactor-node

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-Subproject commit c8f585414f25f315076b6e953561088f0d01bf10

custom_nodes/example_node.py.example

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-class Example:
-    """
-    A example node
-
-    Class methods
-    -------------
-    INPUT_TYPES (dict):
-        Tell the main program input parameters of nodes.
-    IS_CHANGED:
-        optional method to control when the node is re executed.
-
-    Attributes
-    ----------
-    RETURN_TYPES (`tuple`):
-        The type of each element in the output tuple.
-    RETURN_NAMES (`tuple`):
-        Optional: The name of each output in the output tuple.
-    FUNCTION (`str`):
-        The name of the entry-point method. For example, if `FUNCTION = "execute"` then it will run Example().execute()
-    OUTPUT_NODE ([`bool`]):
-        If this node is an output node that outputs a result/image from the graph. The SaveImage node is an example.
-        The backend iterates on these output nodes and tries to execute all their parents if their parent graph is properly connected.
-        Assumed to be False if not present.
-    CATEGORY (`str`):
-        The category the node should appear in the UI.
-    DEPRECATED (`bool`):
-        Indicates whether the node is deprecated. Deprecated nodes are hidden by default in the UI, but remain
-        functional in existing workflows that use them.
-    EXPERIMENTAL (`bool`):
-        Indicates whether the node is experimental. Experimental nodes are marked as such in the UI and may be subject to
-        significant changes or removal in future versions. Use with caution in production workflows.
-    execute(s) -> tuple || None:
-        The entry point method. The name of this method must be the same as the value of property `FUNCTION`.
-        For example, if `FUNCTION = "execute"` then this method's name must be `execute`, if `FUNCTION = "foo"` then it must be `foo`.
-    """
-    def __init__(self):
-        pass
-
-    @classmethod
-    def INPUT_TYPES(s):
-        """
-            Return a dictionary which contains config for all input fields.
-            Some types (string): "MODEL", "VAE", "CLIP", "CONDITIONING", "LATENT", "IMAGE", "INT", "STRING", "FLOAT".
-            Input types "INT", "STRING" or "FLOAT" are special values for fields on the node.
-            The type can be a list for selection.
-
-            Returns: `dict`:
-                - Key input_fields_group (`string`): Can be either required, hidden or optional. A node class must have property `required`
-                - Value input_fields (`dict`): Contains input fields config:
-                    * Key field_name (`string`): Name of a entry-point method's argument
-                    * Value field_config (`tuple`):
-                        + First value is a string indicate the type of field or a list for selection.
-                        + Second value is a config for type "INT", "STRING" or "FLOAT".
-        """
-        return {
-            "required": {
-                "image": ("IMAGE",),
-                "int_field": ("INT", {
-                    "default": 0, 
-                    "min": 0, #Minimum value
-                    "max": 4096, #Maximum value
-                    "step": 64, #Slider's step
-                    "display": "number", # Cosmetic only: display as "number" or "slider"
-                    "lazy": True # Will only be evaluated if check_lazy_status requires it
-                }),
-                "float_field": ("FLOAT", {
-                    "default": 1.0,
-                    "min": 0.0,
-                    "max": 10.0,
-                    "step": 0.01,
-                    "round": 0.001, #The value representing the precision to round to, will be set to the step value by default. Can be set to False to disable rounding.
-                    "display": "number",
-                    "lazy": True
-                }),
-                "print_to_screen": (["enable", "disable"],),
-                "string_field": ("STRING", {
-                    "multiline": False, #True if you want the field to look like the one on the ClipTextEncode node
-                    "default": "Hello World!",
-                    "lazy": True
-                }),
-            },
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    #RETURN_NAMES = ("image_output_name",)
-
-    FUNCTION = "test"
-
-    #OUTPUT_NODE = False
-
-    CATEGORY = "Example"
-
-    def check_lazy_status(self, image, string_field, int_field, float_field, print_to_screen):
-        """
-            Return a list of input names that need to be evaluated.
-
-            This function will be called if there are any lazy inputs which have not yet been
-            evaluated. As long as you return at least one field which has not yet been evaluated
-            (and more exist), this function will be called again once the value of the requested
-            field is available.
-
-            Any evaluated inputs will be passed as arguments to this function. Any unevaluated
-            inputs will have the value None.
-        """
-        if print_to_screen == "enable":
-            return ["int_field", "float_field", "string_field"]
-        else:
-            return []
-
-    def test(self, image, string_field, int_field, float_field, print_to_screen):
-        if print_to_screen == "enable":
-            print(f"""Your input contains:
-                string_field aka input text: {string_field}
-                int_field: {int_field}
-                float_field: {float_field}
-            """)
-        #do some processing on the image, in this example I just invert it
-        image = 1.0 - image
-        return (image,)
-
-    """
-        The node will always be re executed if any of the inputs change but
-        this method can be used to force the node to execute again even when the inputs don't change.
-        You can make this node return a number or a string. This value will be compared to the one returned the last time the node was
-        executed, if it is different the node will be executed again.
-        This method is used in the core repo for the LoadImage node where they return the image hash as a string, if the image hash
-        changes between executions the LoadImage node is executed again.
-    """
-    #@classmethod
-    #def IS_CHANGED(s, image, string_field, int_field, float_field, print_to_screen):
-    #    return ""
-
-# Set the web directory, any .js file in that directory will be loaded by the frontend as a frontend extension
-# WEB_DIRECTORY = "./somejs"
-
-
-# Add custom API routes, using router
-from aiohttp import web
-from server import PromptServer
-
-@PromptServer.instance.routes.get("/hello")
-async def get_hello(request):
-    return web.json_response("hello")
-
-
-# A dictionary that contains all nodes you want to export with their names
-# NOTE: names should be globally unique
-NODE_CLASS_MAPPINGS = {
-    "Example": Example
-}
-
-# A dictionary that contains the friendly/humanly readable titles for the nodes
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "Example": "Example Node"
-}

custom_nodes/websocket_image_save.py

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-from PIL import Image
-import numpy as np
-import comfy.utils
-import time
-
-#You can use this node to save full size images through the websocket, the
-#images will be sent in exactly the same format as the image previews: as
-#binary images on the websocket with a 8 byte header indicating the type
-#of binary message (first 4 bytes) and the image format (next 4 bytes).
-
-#Note that no metadata will be put in the images saved with this node.
-
-class SaveImageWebsocket:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {"required":
-                    {"images": ("IMAGE", ),}
-                }
-
-    RETURN_TYPES = ()
-    FUNCTION = "save_images"
-
-    OUTPUT_NODE = True
-
-    CATEGORY = "api/image"
-
-    def save_images(self, images):
-        pbar = comfy.utils.ProgressBar(images.shape[0])
-        step = 0
-        for image in images:
-            i = 255. * image.cpu().numpy()
-            img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
-            pbar.update_absolute(step, images.shape[0], ("PNG", img, None))
-            step += 1
-
-        return {}
-
-    @classmethod
-    def IS_CHANGED(s, images):
-        return time.time()
-
-NODE_CLASS_MAPPINGS = {
-    "SaveImageWebsocket": SaveImageWebsocket,
-}