Upload example_node.py.example

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.
+
+    Attributes
+    ----------
+    RETURN_TYPES (`tuple`): 
+        The type of each element in the output tulple.
+    RETURN_NAMES (`tuple`):
+        Optional: The name of each output in the output tulple.
+    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.
+    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.
+                        + Secound 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
+                }),
+                "float_field": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
+                "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!"
+                }),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    #RETURN_NAMES = ("image_output_name",)
+
+    FUNCTION = "test"
+
+    #OUTPUT_NODE = False
+
+    CATEGORY = "Example"
+
+    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,)
+
+
+# A dictionary that contains all nodes you want to export with their names
+# NOTE: names should be globally unique
+NODE_CLASS_MAPPINGS = {
+    "Example": Example
+}