Stablezero123ConditioningBatched - ComfyUI Built-in Node Documentation

Complete documentation for the Stablezero123ConditioningBatched node in ComfyUI. Learn its inputs, outputs, parameters and usage.

This node is designed to process conditioning information in a batched manner specifically tailored for the StableZero123 model. It focuses on efficiently handling multiple sets of conditioning data simultaneously, optimizing the workflow for scenarios where batch processing is crucial.

Inputs

Parameter	Data Type	Description
clip_vision	CLIP_VISION	The CLIP vision embeddings that provide visual context for the conditioning process.
init_image	IMAGE	The initial image to be conditioned upon, serving as a starting point for the generation process.
vae	VAE	The variational autoencoder used for encoding and decoding images in the conditioning process.
width	INT	The width of the output image.
height	INT	The height of the output image.
batch_size	INT	The number of conditioning sets to be processed in a single batch.
elevation	FLOAT	The elevation angle for 3D model conditioning, affecting the perspective of the generated image.
azimuth	FLOAT	The azimuth angle for 3D model conditioning, affecting the orientation of the generated image.
elevation_batch_increment	FLOAT	The incremental change in elevation angle across the batch, allowing for varied perspectives.
azimuth_batch_increment	FLOAT	The incremental change in azimuth angle across the batch, allowing for varied orientations.

Outputs

Parameter	Data Type	Description
positive	CONDITIONING	The positive conditioning output, tailored for promoting certain features or aspects in the generated content.
negative	CONDITIONING	The negative conditioning output, tailored for demoting certain features or aspects in the generated content.
latent	LATENT	The latent representation derived from the conditioning process, ready for further processing or generation steps.