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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; | |
| } | |