mirror of https://github.com/vladmandic/human
20 lines
1.2 KiB
TypeScript
20 lines
1.2 KiB
TypeScript
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import type { Tensor } from '../tfjs/types';
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export async function augment(rawCoords, results: Tensor[]) {
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const t: Record<string, Float32Array> = {
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eyeL: results[0].dataSync() as Float32Array, // 71 x 2d // output_left_eye
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eyeR: results[6].dataSync() as Float32Array, // 71 x 2d // output_right_eye
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irisL: results[3].dataSync() as Float32Array, // 5 x 2d // output_left_iris
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irisR: results[1].dataSync() as Float32Array, // 5 x 2d // output_right_iris
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lips: results[5].dataSync() as Float32Array, // 80 x 2d // output_lips
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// flag: results[4], // already processed in parent // conv_faceflag
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// mesh: results[2], // already have it in rawCoords // output_mesh_identity
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};
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for (let i = 0; i < t.lips.length / 2; i++) rawCoords.push([t.lips[2 * i + 0], t.lips[2 * i + 1], 0]);
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for (let i = 0; i < t.eyeL.length / 2; i++) rawCoords.push([t.eyeL[2 * i + 0], t.eyeL[2 * i + 1], 0]);
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for (let i = 0; i < t.eyeR.length / 2; i++) rawCoords.push([t.eyeR[2 * i + 0], t.eyeR[2 * i + 1], 0]);
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for (let i = 0; i < t.irisL.length / 2; i++) rawCoords.push([t.irisL[2 * i + 0], t.irisL[2 * i + 1], 0]);
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for (let i = 0; i < t.irisR.length / 2; i++) rawCoords.push([t.irisR[2 * i + 0], t.irisR[2 * i + 1], 0]);
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return rawCoords;
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}
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