ComfyUI-TacoNodes

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`.

Example · 1 salida

TacoAnimatedLoader

No hay una descripción breve disponible para este nodo.

0 entradas · 1 parámetro · 1 salida

TacoGifMaker

Takes an input of IMAGE and will combine the input into a gif at the desired frame rate, see the above examples for Gif Maker usage.

1 entrada · 2 parámetros · 0 salidas

TacoImg2ImgAnimatedLoader

Allows you to take a single image and generate a batch of images to be processed for gif creation, I like to use this to spice up a still.

0 entradas · 2 parámetros · 2 salidas

TacoImg2ImgAnimatedProcessor

Allows you to pass in an existing image Tensor and batch it by frames for further processing. I first generate an image with KSampler, then decode that image and feed it into the processor, then process that batch.

1 entrada · 1 parámetro · 1 salida

TacoLatent

No hay una descripción breve disponible para este nodo.

1 salida