94 lines
4.9 KiB
Python
94 lines
4.9 KiB
Python
class VisualAreaPrompt:
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"""
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A example node
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Class methods
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-------------
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INPUT_TYPES (dict):
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Tell the main program input parameters of nodes.
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IS_CHANGED:
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optional method to control when the node is re executed.
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Attributes
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----------
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RETURN_TYPES (`tuple`):
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The type of each element in the output tuple.
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RETURN_NAMES (`tuple`):
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Optional: The name of each output in the output tuple.
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FUNCTION (`str`):
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The name of the entry-point method. For example, if `FUNCTION = "execute"` then it will run Example().execute()
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OUTPUT_NODE ([`bool`]):
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If this node is an output node that outputs a result/image from the graph. The SaveImage node is an example.
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The backend iterates on these output nodes and tries to execute all their parents if their parent graph is properly connected.
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Assumed to be False if not present.
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CATEGORY (`str`):
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The category the node should appear in the UI.
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DEPRECATED (`bool`):
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Indicates whether the node is deprecated. Deprecated nodes are hidden by default in the UI, but remain
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functional in existing workflows that use them.
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EXPERIMENTAL (`bool`):
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Indicates whether the node is experimental. Experimental nodes are marked as such in the UI and may be subject to
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significant changes or removal in future versions. Use with caution in production workflows.
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execute(s) -> tuple || None:
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The entry point method. The name of this method must be the same as the value of property `FUNCTION`.
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For example, if `FUNCTION = "execute"` then this method's name must be `execute`, if `FUNCTION = "foo"` then it must be `foo`.
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"""
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def __init__(self) -> None:
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pass
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@classmethod
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def INPUT_TYPES(s):
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"""
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Return a dictionary which contains config for all input fields.
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Some types (string): "MODEL", "VAE", "CLIP", "CONDITIONING", "LATENT", "IMAGE", "INT", "STRING", "FLOAT".
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Input types "INT", "STRING" or "FLOAT" are special values for fields on the node.
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The type can be a list for selection.
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Returns: `dict`:
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- Key input_fields_group (`string`): Can be either required, hidden or optional. A node class must have property `required`
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- Value input_fields (`dict`): Contains input fields config:
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* Key field_name (`string`): Name of a entry-point method's argument
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* Value field_config (`tuple`):
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+ First value is a string indicate the type of field or a list for selection.
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+ Second value is a config for type "INT", "STRING" or "FLOAT".
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"""
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return {
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"required": {
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"global_conditioning": ("CONDITIONING", { "tooltip": "Base conditioning. Will be applied to the whole image." }),
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# "conditioning0": ("CONDITIONING", { "tooltip": "Input conditioning. (Connecting a conditioning will create a new input.)" }),
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# "id": ("INT", { "default": 0, "min": 0, "max": 10, "step": 1, "tooltip": "The id of the conditioning settings to change." }),
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# "x": ("FLOAT", { "default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The x position of the conditioning (of id)." }),
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# "y": ("FLOAT", { "default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The y position of the conditioning (of id)." }),
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# "width": ("FLOAT", { "default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The width of the conditioning (of id)." }),
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# "height": ("FLOAT", { "default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "The height of the conditioning (of id)." }),
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# "weight": ("FLOAT", { "default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01, "tooltip": "The weight applied to the conditioning (of id)." }),
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},
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}
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OUTPUT_TOOLTIPS = ("Area conditioning","Combined conditioning")
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RETURN_TYPES = ("CONDITIONING","CONDITIONING")
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RETURN_NAMES = ("area_conditioning","combined_conditioning")
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FUNCTION = "run"
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#OUTPUT_NODE = False
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CATEGORY = "RegionalPrompt"
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def run(self, **kwargs):
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return (None, None)
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"""
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The node will always be re executed if any of the inputs change but
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this method can be used to force the node to execute again even when the inputs don't change.
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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
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executed, if it is different the node will be executed again.
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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
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changes between executions the LoadImage node is executed again.
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"""
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#@classmethod
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#def IS_CHANGED(s, image, string_field, int_field, float_field, print_to_screen):
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# return ""
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