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SD_4XUpscale_Conditioning

conditioning/upscale_diffusion
SD_4XUpscale_Conditioning

Example

JSON Example
{
  "class_type": "SD_4XUpscale_Conditioning",
  "inputs": {
    "images": [
      "node_id",
      0
    ],
    "positive": [
      "node_id",
      0
    ],
    "negative": [
      "node_id",
      0
    ],
    "scale_ratio": 4,
    "noise_augmentation": 0
  }
}

This example shows required inputs only. Connection values like ["node_id", 0] should reference actual node IDs from your workflow.

Inputs

NameTypeStatusConstraintsDefault
imagesIMAGErequired--
positiveCONDITIONINGrequired--
negativeCONDITIONINGrequired--
scale_ratioFLOATrequiredmin: 0, max: 10, step: 0.014
noise_augmentationFLOATrequiredmin: 0, max: 1, step: 0.0010

Outputs

IndexNameTypeIs ListConnection Reference
0positiveCONDITIONINGNo["{node_id}", 0]
1negativeCONDITIONINGNo["{node_id}", 1]
2latentLATENTNo["{node_id}", 2]
How to connect to these outputs

To connect another node's input to an output from this node, use the connection reference format:

["node_id", output_index]

Where node_id is the ID of this SD_4XUpscale_Conditioning node in your workflow, and output_index is the index from the table above.

Example

If this node has ID "5" in your workflow:

  • positive (CONDITIONING): ["5", 0]
  • negative (CONDITIONING): ["5", 1]
  • latent (LATENT): ["5", 2]
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