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post-controlnet-inferences

Generate AI images guided by control inputs like poses, edges, or depth maps to maintain specific structural elements in the output.

Instructions

Trigger a new image generation in ControlNet mode. The control image is used to guide the generation; it can be a pose, canny map, or similar.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originalAssetsNoIf set to true, returns the original asset without transformation
dryRunNo
controlEndNoSpecifies how long the ControlNet guidance should be applied during the inference process. Only available for Flux.1-dev based models. The value represents the percentage of total inference steps where the ControlNet guidance is active. For example: - 1.0: ControlNet guidance is applied during all inference steps - 0.5: ControlNet guidance is only applied during the first half of inference steps Default values: - 0.5 for Canny modality - 0.6 for all other modalities
modalityYesThe modality associated with the control image used for the generation: it can either be an object with a combination of maximum For models of SD1.5 family: - up to 3 modalities from `canny`, `pose`, `depth`, `lines`, `seg`, `scribble`, `lineart`, `normal-map`, `illusion` - or one of the following presets: `character`, `landscape`, `city`, `interior`. For models of the SDXL family: - up to 3 modalities from `canny`, `pose`, `depth`, `seg`, `illusion`, `scribble` - or one of the following presets: `character`, `landscape`. For models of the FLUX schnell or dev families: - one modality from: `canny`, `tile`, `depth`, `blur`, `pose`, `gray`, `low-quality` Optionally, you can associate a value to these modalities or presets. The value must be within `]0.0, 1.0]`. Examples: - `canny` - `depth:0.5,pose:1.0` - `canny:0.5,depth:0.5,lines:0.3` - `landscape` - `character:0.5` - `illusion:1` Note: if you use a value that is not supported by the model family, this will result in an error.
seedNoUsed to reproduce previous results. Default: randomly generated number.
modelIdYesThe model id to use for the inference
schedulerNoThe scheduler to use to override the default configured for the model. See detailed documentation for more details.
disableModalityDetectionNoIf false, the process uses the given image to detect the modality. If true (default), the process will not try to detect the modality of the given image. For example: with `pose` modality and `false` value, the process will detect the pose of people in the given image with `depth` modality and `false` value, the process will detect the depth of the given image with `scribble` modality and `true`value, the process will use the given image as a scribble ⚠️ For models of the FLUX schnell or dev families, this parameter is ignored. The modality detection is always disabled. ⚠️
imageParentIdNoSpecifies the parent asset Id for the image when provided as a dataurl.
baseModelIdNoThe base model to use for the inference. Only Flux LoRA models can use this parameter. Allowed values are available in the model's attribute: `compliantModelIds`
controlStartNoSpecifies the starting point of the ControlNet guidance during the inference process. Only available for Flux.1-dev based models. The value represents the percentage of total inference steps where the ControlNet guidance starts. For example: - 0.0: ControlNet guidance starts at the beginning of the inference steps - 0.5: ControlNet guidance starts at the middle of the inference steps
heightNoThe height of the generated images, must be a 8 multiple (within [64, 2048], default: 512) If model.type is `sd-xl`, `sd-xl-lora`, `sd-xl-composition` the height must be within [512, 2048] If model.type is `sd-1_5`, the height must be within [64, 1024] If model.type is `flux.1.1-pro-ultra`, you can use the aspectRatio parameter instead
imageHideNoToggles the hidden status of the image when provided as a dataurl.
controlImageIdNoThe controlnet input image as an AssetId. Will be ignored if the `controlnet` parameter is provided
imageNoThe input image as a data URL (example: "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVQYV2NgYAAAAAMAAWgmWQ0AAAAASUVORK5CYII=") or the asset ID (example: "asset_GTrL3mq4SXWyMxkOHRxlpw")
imageIdNoDeprecated: The input image as an AssetId. Prefer to use image with the asset ID instead.
modelEpochNoThe epoch of the model to use for the inference. Only available for Flux Lora Trained models.
hideResultsNoIf set, generated assets will be hidden and not returned in the list of images of the inference or when listing assets (default: false)
negativePromptNoThe prompt not to guide the image generation, ignored when guidance < 1 (example: "((ugly face))") For Flux based model (not Fast-Flux): requires negativePromptStrength > 0 and active only for inference types txt2img / img2img / controlnet.
intermediateImagesNoEnable or disable the intermediate images generation (default: false)
conceptsNo
controlImageNoThe controlnet input image as a data URL (example: "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVQYV2NgYAAAAAMAAWgmWQ0AAAAASUVORK5CYII=")
guidanceNoControls how closely the generated image follows the prompt. Higher values result in stronger adherence to the prompt. Default and allowed values depend on the model type: - For Flux dev models, the default is 3.5 and allowed values are within [0, 10] - For Flux pro models, the default is 3 and allowed values are within [2, 5] - For SDXL models, the default is 6 and allowed values are within [0, 20] - For SD1.5 models, the default is 7.5 and allowed values are within [0, 20]
numInferenceStepsNoThe number of denoising steps for each image generation (within [1, 150], default: 30)
numSamplesNoThe number of images to generate (within [1, 128], default: 4)
widthNoThe width of the generated images, must be a 8 multiple (within [64, 2048], default: 512) If model.type is `sd-xl`, `sd-xl-lora`, `sd-xl-composition` the width must be within [512, 2048] If model.type is `sd-1_5`, the width must be within [64, 1024] If model.type is `flux.1.1-pro-ultra`, you can use the aspectRatio parameter instead
negativePromptStrengthNoOnly applicable for flux-dev based models for `txt2img`, `img2img`, and `controlnet` inference types. Controls the influence of the negative prompt. Default 0 means the negative prompt has no effect. Higher values increase negative prompt influence. Must be > 0 if negativePrompt is provided.
promptYesFull text prompt including the model placeholder. (example: "an illustration of phoenix in a fantasy world, flying over a mountain, 8k, bokeh effect")

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