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import { InferenceOutputError } from "../../lib/InferenceOutputError";
import type { BaseArgs, Options, RequestArgs } from "../../types";
import { request } from "../custom/request";
import { base64FromBytes } from "../../../../shared";
export type ImageToImageArgs = BaseArgs & {
/**
* The initial image condition
*
**/
inputs: Blob | ArrayBuffer;
parameters?: {
/**
* The text prompt to guide the image generation.
*/
prompt?: string;
/**
* strengh param only works for SD img2img and alt diffusion img2img models
* Conceptually, indicates how much to transform the reference `image`. Must be between 0 and 1. `image`
* will be used as a starting point, adding more noise to it the larger the `strength`. The number of
* denoising steps depends on the amount of noise initially added. When `strength` is 1, added noise will
* be maximum and the denoising process will run for the full number of iterations specified in
* `num_inference_steps`. A value of 1, therefore, essentially ignores `image`.
**/
strength?: number;
/**
* An optional negative prompt for the image generation
*/
negative_prompt?: string;
/**
* The height in pixels of the generated image
*/
height?: number;
/**
* The width in pixels of the generated image
*/
width?: number;
/**
* The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.
*/
num_inference_steps?: number;
/**
* Guidance scale: Higher guidance scale encourages to generate images that are closely linked to the text `prompt`, usually at the expense of lower image quality.
*/
guidance_scale?: number;
/**
* guess_mode only works for ControlNet models, defaults to False In this mode, the ControlNet encoder will try best to recognize the content of the input image even if
* you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.
*/
guess_mode?: boolean;
};
};
export type ImageToImageOutput = Blob;
/**
* This task reads some text input and outputs an image.
* Recommended model: lllyasviel/sd-controlnet-depth
*/
export async function imageToImage(args: ImageToImageArgs, options?: Options): Promise<ImageToImageOutput> {
let reqArgs: RequestArgs;
if (!args.parameters) {
reqArgs = {
accessToken: args.accessToken,
model: args.model,
data: args.inputs,
};
} else {
reqArgs = {
...args,
inputs: base64FromBytes(
new Uint8Array(args.inputs instanceof ArrayBuffer ? args.inputs : await args.inputs.arrayBuffer())
),
};
}
const res = await request<ImageToImageOutput>(reqArgs, {
...options,
taskHint: "image-to-image",
});
const isValidOutput = res && res instanceof Blob;
if (!isValidOutput) {
throw new InferenceOutputError("Expected Blob");
}
return res;
}
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