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import { InferenceOutputError } from "../../lib/InferenceOutputError"; | |
import type { BaseArgs, Options } from "../../types"; | |
import { request } from "../custom/request"; | |
export type ImageSegmentationArgs = BaseArgs & { | |
/** | |
* Binary image data | |
*/ | |
data: Blob | ArrayBuffer; | |
}; | |
export interface ImageSegmentationOutputValue { | |
/** | |
* The label for the class (model specific) of a segment. | |
*/ | |
label: string; | |
/** | |
* A str (base64 str of a single channel black-and-white img) representing the mask of a segment. | |
*/ | |
mask: string; | |
/** | |
* A float that represents how likely it is that the detected object belongs to the given class. | |
*/ | |
score: number; | |
} | |
export type ImageSegmentationOutput = ImageSegmentationOutputValue[]; | |
/** | |
* This task reads some image input and outputs the likelihood of classes & bounding boxes of detected objects. | |
* Recommended model: facebook/detr-resnet-50-panoptic | |
*/ | |
export async function imageSegmentation( | |
args: ImageSegmentationArgs, | |
options?: Options | |
): Promise<ImageSegmentationOutput> { | |
const res = await request<ImageSegmentationOutput>(args, { | |
...options, | |
taskHint: "image-segmentation", | |
}); | |
const isValidOutput = | |
Array.isArray(res) && | |
res.every((x) => typeof x.label === "string" && typeof x.mask === "string" && typeof x.score === "number"); | |
if (!isValidOutput) { | |
throw new InferenceOutputError("Expected Array<{label: string, mask: string, score: number}>"); | |
} | |
return res; | |
} | |