EditConfigV6

EditConfig for imagegeneration@006

Fields
bufferZones[] object (BufferZone)

Buffer zone, if provided, must be length 2.

editMode string

The editing mode that describes the use case for editing. The values can be one of: * inpainting-remove * inpainting-insert * outpainting * product-image

maskDilation number

Parameter to control mask dilation, range: [0, 1], default: 0.03.

guidanceScale integer

Guidance scale: this controls strength of text guidance.

productPosition string

Product position: this controls the product position in the returned product editing image. The values can be one of: * reposition - the default behavior in the GPS pipeline * fixed - keeps the product in the same position as in the position as in the input image. This assume input image is square.

maskMode object (MaskMode)

Automatic mask generation configuration.

baseSteps integer

Number of sampling steps for base model.

backend string

The backend to use for the model. The values can be one of: * experimental * prod

semanticFilterConfig object (SemanticFilterConfig)

Semantic Filter Config. This config reduces object hallucination on inpainted images. Users can set filter classes and filter entities to filter out generated images that hallucinate undesired objects in the inpainted area. This config is only enabled in Editing config.

alternateInitConfig object (AlternateInitConfig)

Parameters for AlternateInitConfig

outpaintingConfig object (OutpaintingProcessingConfig)

Outpainting config.

JSON representation 
{
  "bufferZones": [
    {
      object (BufferZone)
    }
  ],
  "editMode": string,
  "maskDilation": number,
  "guidanceScale": integer,
  "productPosition": string,
  "maskMode": {
    object (MaskMode)
  },
  "baseSteps": integer,
  "backend": string,
  "semanticFilterConfig": {
    object (SemanticFilterConfig)
  },
  "alternateInitConfig": {
    object (AlternateInitConfig)
  },
  "outpaintingConfig": {
    object (OutpaintingProcessingConfig)
  }
}

MaskMode

Fields
maskType string

The type of mask to generate from the provided input image. The values can be one of: * background * foreground * semantic

classes[] value (Value format)

The class IDs to generate masks of using the Semantic Segmenter model. Only numeric class IDs are supported.

Not used if the maskType value is not semantic.

JSON representation 
{
  "maskType": string,
  "classes": [
    value
  ]
}

BufferZone

BufferZone config.

Fields
pixels integer

The number of pixels for the mask to dilate.

diffusionT number

When during diffusion this pixel dilation takes effect, 1=start, 0=end.

JSON representation 
{
  "pixels": integer,
  "diffusionT": number
}