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| import { request } from "../custom/request"; | |
| import type { BaseArgs, Options } from "../../types"; | |
| import { InferenceOutputError } from "../../lib/InferenceOutputError"; | |
| export type ObjectDetectionArgs = BaseArgs & { | |
| /** | |
| * Binary image data | |
| */ | |
| data: Blob | ArrayBuffer; | |
| }; | |
| export interface ObjectDetectionOutputValue { | |
| /** | |
| * A dict (with keys [xmin,ymin,xmax,ymax]) representing the bounding box of a detected object. | |
| */ | |
| box: { | |
| xmax: number; | |
| xmin: number; | |
| ymax: number; | |
| ymin: number; | |
| }; | |
| /** | |
| * The label for the class (model specific) of a detected object. | |
| */ | |
| label: string; | |
| /** | |
| * A float that represents how likely it is that the detected object belongs to the given class. | |
| */ | |
| score: number; | |
| } | |
| export type ObjectDetectionOutput = ObjectDetectionOutputValue[]; | |
| /** | |
| * This task reads some image input and outputs the likelihood of classes & bounding boxes of detected objects. | |
| * Recommended model: facebook/detr-resnet-50 | |
| */ | |
| export async function objectDetection(args: ObjectDetectionArgs, options?: Options): Promise<ObjectDetectionOutput> { | |
| const res = await request<ObjectDetectionOutput>(args, { | |
| ...options, | |
| taskHint: "object-detection", | |
| }); | |
| const isValidOutput = | |
| Array.isArray(res) && | |
| res.every( | |
| (x) => | |
| typeof x.label === "string" && | |
| typeof x.score === "number" && | |
| typeof x.box.xmin === "number" && | |
| typeof x.box.ymin === "number" && | |
| typeof x.box.xmax === "number" && | |
| typeof x.box.ymax === "number" | |
| ); | |
| if (!isValidOutput) { | |
| throw new InferenceOutputError( | |
| "Expected Array<{label:string; score:number; box:{xmin:number; ymin:number; xmax:number; ymax:number}}>" | |
| ); | |
| } | |
| return res; | |
| } | |