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face-api.js

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JavaScript API for face detection and face recognition in the browser with tensorflow.js

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import { __awaiter, __generator } from "tslib"; import * as tf from '@tensorflow/tfjs-core'; import { FaceDetection } from '../classes/FaceDetection'; import { isTensor3D, isTensor4D } from '../utils'; /** * Extracts the tensors of the image regions containing the detected faces. * Useful if you want to compute the face descriptors for the face images. * Using this method is faster then extracting a canvas for each face and * converting them to tensors individually. * * @param imageTensor The image tensor that face detection has been performed on. * @param detections The face detection results or face bounding boxes for that image. * @returns Tensors of the corresponding image region for each detected face. */ export function extractFaceTensors(imageTensor, detections) { return __awaiter(this, void 0, void 0, function () { return __generator(this, function (_a) { if (!isTensor3D(imageTensor) && !isTensor4D(imageTensor)) { throw new Error('extractFaceTensors - expected image tensor to be 3D or 4D'); } if (isTensor4D(imageTensor) && imageTensor.shape[0] > 1) { throw new Error('extractFaceTensors - batchSize > 1 not supported'); } return [2 /*return*/, tf.tidy(function () { var _a = imageTensor.shape.slice(isTensor4D(imageTensor) ? 1 : 0), imgHeight = _a[0], imgWidth = _a[1], numChannels = _a[2]; var boxes = detections.map(function (det) { return det instanceof FaceDetection ? det.forSize(imgWidth, imgHeight).box : det; }) .map(function (box) { return box.clipAtImageBorders(imgWidth, imgHeight); }); var faceTensors = boxes.map(function (_a) { var x = _a.x, y = _a.y, width = _a.width, height = _a.height; return tf.slice3d(imageTensor.as3D(imgHeight, imgWidth, numChannels), [y, x, 0], [height, width, numChannels]); }); return faceTensors; })]; }); }); } //# sourceMappingURL=extractFaceTensors.js.map