47 lines
1.8 KiB
TypeScript
47 lines
1.8 KiB
TypeScript
import * as tf from '../../dist/tfjs.esm.js';
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import { FaceDetection } from '../classes/FaceDetection';
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import { extractFaces, extractFaceTensors, TNetInput } from '../dom/index';
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import { WithFaceDetection } from '../factories/WithFaceDetection';
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import { isWithFaceLandmarks, WithFaceLandmarks } from '../factories/WithFaceLandmarks';
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export async function extractAllFacesAndComputeResults<TSource extends WithFaceDetection<{}>, TResult>(
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parentResults: TSource[],
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input: TNetInput,
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computeResults: (faces: Array<HTMLCanvasElement | tf.Tensor3D>) => Promise<TResult>,
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extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null,
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getRectForAlignment: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection = ({ alignedRect }) => alignedRect
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) {
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const faceBoxes = parentResults.map(parentResult =>
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isWithFaceLandmarks(parentResult)
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? getRectForAlignment(parentResult)
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: parentResult.detection
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)
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const faces: Array<HTMLCanvasElement | tf.Tensor3D> = extractedFaces || (
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input instanceof tf.Tensor
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? await extractFaceTensors(input, faceBoxes)
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: await extractFaces(input, faceBoxes)
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)
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const results = await computeResults(faces)
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faces.forEach(f => f instanceof tf.Tensor && f.dispose())
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return results
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}
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export async function extractSingleFaceAndComputeResult<TSource extends WithFaceDetection<{}>, TResult>(
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parentResult: TSource,
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input: TNetInput,
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computeResult: (face: HTMLCanvasElement | tf.Tensor3D) => Promise<TResult>,
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extractedFaces?: Array<HTMLCanvasElement | tf.Tensor3D> | null,
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getRectForAlignment?: (parentResult: WithFaceLandmarks<TSource, any>) => FaceDetection
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) {
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return extractAllFacesAndComputeResults<TSource, TResult>(
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[parentResult],
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input,
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async faces => computeResult(faces[0]),
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extractedFaces,
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getRectForAlignment
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)
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} |