Resize Image

Image Url

Radius

BlurMaskInput

Image

BlurMaskOutput

High threshold for the hysteresis procedure

High Threshold

Low threshold for the hysteresis procedure

Low Threshold

CannyInput

Color

Compare Text

Text to return if the input text does not match the compare text

Fail Text

Text to return if the input text matches the compare text

Return Text

Text

CompareTextInput

Background Image Url

Mask Image Url

Overlay Image Url

CompositeImageInput

Bbox

Det Score

Embedding File

Kps Image

FaceDetection

Content Type

File Data

The name of the file. It will be auto-generated if not provided.

File Name

File Size

The URL where the file can be downloaded from.

File

Pixels

The threshold to convert the image to a mask. 0-255.

Threshold

GrowMaskInput

GrowMaskOutput

Detail

HTTPValidationError

Height

Width

ImageInput

ImageOutput

Image Size

ImageSizeOutput

Template

InsertTextInput

Det Size Height

Det Size Width

Max Face Num

Model Url

Sorting

Sync Mode

InsightfaceInput

Faces

InsightfaceOutput

InvertMaskOutput

MaskInput

Color to replace the transparent pixels with

Transparent Color

RGBAToRGBImageInput

Pattern

Replace

RegexReplaceInput

Position of cropping. Only used when mode is 'crop', default is center

Cropping Position

Mode

Color of padding. Only used when mode is 'pad', default is black

Padding Color

Resizing strategy. Only used when mode is 'scale', default is nearest

Resampling

Proportions of the image. Only used when mode is 'scale', default is fit

Scaling Proportions

ResizeImageInput

If set, the output dimensions will be divisible by this value.

Enforce Divisibility

Maximum number of pixels in the output image.

Max Pixels

ResizeToPixelsInput

ShrinkMaskInput

ShrinkMaskOutput

TeedInput

TeedOutput

TextOutput

The threshold to convert the image to a mask.

TransparentImageToMaskInput

TransparentImageToMaskOutput

Location

Message

Error Type

ValidationError

FastAPI

Run Any Stable Diffusion model with customizable LoRA weights.

Stable Diffusion with LoRAs


            The scale of the control net weight. This is used to scale the control net weight
            before merging it with the base model.
        

Conditioning Scale

optional URL to the controlnet config.json file.

Config Url


            The percentage of the image to end applying the controlnet in terms of the total timesteps.
        

End Percentage

URL of the image to be used as the control net.


            The index of the IP adapter to be applied to the controlnet. This is only needed for InstantID ControlNets.
        

Ip Adapter Index


            The mask to use for the controlnet. When using a mask, the control image size and the mask size must be the same and divisible by 32.
        

Mask Url

URL or the path to the control net weights.

Path


            The percentage of the image to start applying the controlnet in terms of the total timesteps.
        

Start Percentage

The optional variant if a Hugging Face repo key is used.

Variant

ControlNet

URL or the path to the embedding weights.


            The tokens to map the embedding weights to. Use these tokens in your prompts.
        

Tokens

Embedding


            The value to set the image projection shortcut to. For FaceID plus V1 models,
            this should be set to False. For FaceID plus V2 models, this should be set to True.
            Default is True.
        

Image Projection Shortcut

URL or the path to the InsightFace model weights.

Insight Face Model Path

URL of the image to be used as the IP adapter.

Ip Adapter Image Url


            The mask to use for the IP adapter. When using a mask, the ip-adapter image size and the mask size must be the same
        

Ip Adapter Mask Url

Subfolder in the model directory where the IP adapter weights are stored.

Model Subfolder

URL or the path to the IP adapter weights.


            The scale of the IP adapter weight. This is used to scale the IP adapter weight
            before merging it with the base model.
        

Scale

Scale Json

The factor to apply to the unconditional noising of the IP adapter.

Unconditional Noising Factor

Weight Name

IPAdapter

ImageSize


            Skips part of the image generation process, leading to slightly different results.
            This means the image renders faster, too.
        

Clip Skip


            If set to true, the controlnet will be applied to only the conditional predictions.
        

Controlnet Guess Mode


            The control nets to use for the image generation. You can use any number of control nets
            and they will be applied to the image at the specified timesteps.
        

Controlnets

If set to true, the latents will be saved for debugging.

Debug Latents

If set to true, the latents will be saved for debugging per pass.

Debug Per Pass Latents


            The embeddings to use for the image generation. Only a single embedding is supported at the moment.
            The embeddings will be used to map the tokens in the prompt to the embedding weights.
        

Embeddings

If set to true, the safety checker will be enabled.

Enable Safety Checker

The eta value to be used for the image generation.


            The CFG (Classifier Free Guidance) scale is a measure of how close you want
            the model to stick to your prompt when looking for a related image to show you.
        

Guidance scale (CFG)


            The URL of the IC Light model image to use for the image generation.
        

Ic Light Image Url


            The URL of the IC Light model background image to use for the image generation.
            Make sure to use a background compatible with the model.
        

Ic Light Model Background Image Url


            The URL of the IC Light model to use for the image generation.
        

Ic Light Model Url


            The path to the image encoder model to use for the image generation.
        

Image Encoder Path


            The subfolder of the image encoder model to use for the image generation.
        

Image Encoder Subfolder


            The weight name of the image encoder model to use for the image generation.
        

Image Encoder Weight Name

Image Format

URL of image to use for image to image/inpainting.


            The IP adapter to use for the image generation.
        

Ip Adapter


            The LoRAs to use for the image generation. You can use any number of LoRAs
            and they will be merged together to generate the final image.
        

Loras

URL or HuggingFace ID of the base model to generate the image.

Model Name


            The negative prompt to use.Use it to address details that you don't want
            in the image. This could be colors, objects, scenery and even the small details
            (e.g. moustache, blurry, low resolution).
        

Negative Prompt

The amount of noise to add to noise image for image. Only used if the image_url is provided. 1.0 is complete noise and 0 is no noise.

Noise Strength


            Number of images to generate in one request. Note that the higher the batch size,
            the longer it will take to generate the images.
        

Number of images


            Increasing the amount of steps tells Stable Diffusion that it should take more steps
            to generate your final result which can increase the amount of detail in your image.
        

Number of inference steps

The prompt to use for generating the image. Be as descriptive as possible for best results.

Prompt


            If set to true, the prompt weighting syntax will be used.
            Additionally, this will lift the 77 token limit by averaging embeddings.
        

Prompt Weighting

Scheduler / sampler to use for the image denoising process.

Scheduler


            The same seed and the same prompt given to the same version of Stable Diffusion
            will output the same image every time.
        

Seed


            Optionally override the sigmas to use for the denoising process. Only works with schedulers which support the `sigmas` argument in their `set_sigmas` method.
            Defaults to not overriding, in which case the scheduler automatically sets the sigmas based on the `num_inference_steps` parameter.
            If set to a custom sigma schedule, the `num_inference_steps` parameter will be ignored. Cannot be set if `timesteps` is set.
        

Sigmas

The size of the tiles to be used for the image generation.

Tile Height

The stride of the tiles to be used for the image generation.

Tile Stride Height

Tile Stride Width

Tile Width


            Optionally override the timesteps to use for the denoising process. Only works with schedulers which support the `timesteps` argument in their `set_timesteps` method.
            Defaults to not overriding, in which case the scheduler automatically sets the timesteps based on the `num_inference_steps` parameter.
            If set to a custom timestep schedule, the `num_inference_steps` parameter will be ignored. Cannot be set if `sigmas` is set.
        

Search

Input

Result

Logs