Inputs
| Parameter | Description | Data Type |
|---|---|---|
clip_vision | The CLIP vision embeddings that provide visual context for the conditioning process. | CLIP_VISION |
init_image | The initial image to be conditioned upon, serving as a starting point for the generation process. | IMAGE |
vae | The variational autoencoder used for encoding and decoding images in the conditioning process. | VAE |
width | The width of the output image. | INT |
height | The height of the output image. | INT |
batch_size | The number of conditioning sets to be processed in a single batch. | INT |
elevation | The elevation angle for 3D model conditioning, affecting the perspective of the generated image. | FLOAT |
azimuth | The azimuth angle for 3D model conditioning, affecting the orientation of the generated image. | FLOAT |
elevation_batch_increment | The incremental change in elevation angle across the batch, allowing for varied perspectives. | FLOAT |
azimuth_batch_increment | The incremental change in azimuth angle across the batch, allowing for varied orientations. | FLOAT |
Outputs
| Parameter | Description | Data Type |
|---|---|---|
positive | The positive conditioning output, tailored for promoting certain features or aspects in the generated content. | CONDITIONING |
negative | The negative conditioning output, tailored for demoting certain features or aspects in the generated content. | CONDITIONING |
latent | The latent representation derived from the conditioning process, ready for further processing or generation steps. | LATENT |
This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHub