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update tsc config

pull/13/head
Vladimir Mandic 2020-08-19 20:10:42 -04:00
parent 6428d45367
commit 233d08d3f7
303 changed files with 5372 additions and 7522 deletions
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20
build/NeuralNetwork.js
View File

@ -1,11 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.NeuralNetwork = void 0;
const tf = require("@tensorflow/tfjs-core");
const getModelUris_1 = require("./common/getModelUris");
const dom_1 = require("./dom");
const env_1 = require("./env");
class NeuralNetwork {
import * as tf from '@tensorflow/tfjs-core';
import { getModelUris } from './common/getModelUris';
import { loadWeightMap } from './dom';
import { env } from './env';
export class NeuralNetwork {
constructor(_name) {
this._name = _name;
this._params = undefined;
@ -72,15 +69,15 @@ class NeuralNetwork {
if (uri && typeof uri !== 'string') {
throw new Error(`${this._name}.loadFromUri - expected model uri`);
}
const weightMap = await dom_1.loadWeightMap(uri, this.getDefaultModelName());
const weightMap = await loadWeightMap(uri, this.getDefaultModelName());
this.loadFromWeightMap(weightMap);
}
async loadFromDisk(filePath) {
if (filePath && typeof filePath !== 'string') {
throw new Error(`${this._name}.loadFromDisk - expected model file path`);
}
const { readFile } = env_1.env.getEnv();
const { manifestUri, modelBaseUri } = getModelUris_1.getModelUris(filePath, this.getDefaultModelName());
const { readFile } = env.getEnv();
const { manifestUri, modelBaseUri } = getModelUris(filePath, this.getDefaultModelName());
const fetchWeightsFromDisk = (filePaths) => Promise.all(filePaths.map(filePath => readFile(filePath).then(buf => buf.buffer)));
const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk);
const manifest = JSON.parse((await readFile(manifestUri)).toString());
@ -114,5 +111,4 @@ class NeuralNetwork {
return { obj, objProp };
}
}
exports.NeuralNetwork = NeuralNetwork;
//# sourceMappingURL=NeuralNetwork.js.map

2
build/NeuralNetwork.js.map
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@ -1 +1 @@
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44
build/ageGenderNet/AgeGenderNet.js
View File

@ -1,17 +1,14 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.AgeGenderNet = void 0;
const tf = require("@tensorflow/tfjs-core");
const fullyConnectedLayer_1 = require("../common/fullyConnectedLayer");
const util_1 = require("../faceProcessor/util");
const TinyXception_1 = require("../xception/TinyXception");
const extractParams_1 = require("./extractParams");
const extractParamsFromWeigthMap_1 = require("./extractParamsFromWeigthMap");
const types_1 = require("./types");
const NeuralNetwork_1 = require("../NeuralNetwork");
const dom_1 = require("../dom");
class AgeGenderNet extends NeuralNetwork_1.NeuralNetwork {
constructor(faceFeatureExtractor = new TinyXception_1.TinyXception(2)) {
import * as tf from '@tensorflow/tfjs-core';
import { fullyConnectedLayer } from '../common/fullyConnectedLayer';
import { seperateWeightMaps } from '../faceProcessor/util';
import { TinyXception } from '../xception/TinyXception';
import { extractParams } from './extractParams';
import { extractParamsFromWeigthMap } from './extractParamsFromWeigthMap';
import { Gender } from './types';
import { NeuralNetwork } from '../NeuralNetwork';
import { NetInput, toNetInput } from '../dom';
export class AgeGenderNet extends NeuralNetwork {
constructor(faceFeatureExtractor = new TinyXception(2)) {
super('AgeGenderNet');
this._faceFeatureExtractor = faceFeatureExtractor;
}
@ -24,12 +21,12 @@ class AgeGenderNet extends NeuralNetwork_1.NeuralNetwork {
throw new Error(`${this._name} - load model before inference`);
}
return tf.tidy(() => {
const bottleneckFeatures = input instanceof dom_1.NetInput
const bottleneckFeatures = input instanceof NetInput
? this.faceFeatureExtractor.forwardInput(input)
: input;
const pooled = tf.avgPool(bottleneckFeatures, [7, 7], [2, 2], 'valid').as2D(bottleneckFeatures.shape[0], -1);
const age = fullyConnectedLayer_1.fullyConnectedLayer(pooled, params.fc.age).as1D();
const gender = fullyConnectedLayer_1.fullyConnectedLayer(pooled, params.fc.gender);
const age = fullyConnectedLayer(pooled, params.fc.age).as1D();
const gender = fullyConnectedLayer(pooled, params.fc.gender);
return { age, gender };
});
}
@ -40,10 +37,10 @@ class AgeGenderNet extends NeuralNetwork_1.NeuralNetwork {
});
}
async forward(input) {
return this.forwardInput(await dom_1.toNetInput(input));
return this.forwardInput(await toNetInput(input));
}
async predictAgeAndGender(input) {
const netInput = await dom_1.toNetInput(input);
const netInput = await toNetInput(input);
const out = await this.forwardInput(netInput);
const ages = tf.unstack(out.age);
const genders = tf.unstack(out.gender);
@ -55,7 +52,7 @@ class AgeGenderNet extends NeuralNetwork_1.NeuralNetwork {
const age = (await ageTensor.data())[0];
const probMale = (await genderTensor.data())[0];
const isMale = probMale > 0.5;
const gender = isMale ? types_1.Gender.MALE : types_1.Gender.FEMALE;
const gender = isMale ? Gender.MALE : Gender.FEMALE;
const genderProbability = isMale ? probMale : (1 - probMale);
ageTensor.dispose();
genderTensor.dispose();
@ -80,12 +77,12 @@ class AgeGenderNet extends NeuralNetwork_1.NeuralNetwork {
this._paramMappings = paramMappings;
}
extractClassifierParams(weights) {
return extractParams_1.extractParams(weights);
return extractParams(weights);
}
extractParamsFromWeigthMap(weightMap) {
const { featureExtractorMap, classifierMap } = util_1.seperateWeightMaps(weightMap);
const { featureExtractorMap, classifierMap } = seperateWeightMaps(weightMap);
this.faceFeatureExtractor.loadFromWeightMap(featureExtractorMap);
return extractParamsFromWeigthMap_1.extractParamsFromWeigthMap(classifierMap);
return extractParamsFromWeigthMap(classifierMap);
}
extractParams(weights) {
const classifierWeightSize = (512 * 1 + 1) + (512 * 2 + 2);
@ -95,5 +92,4 @@ class AgeGenderNet extends NeuralNetwork_1.NeuralNetwork {
return this.extractClassifierParams(classifierWeights);
}
}
exports.AgeGenderNet = AgeGenderNet;
//# sourceMappingURL=AgeGenderNet.js.map

2
build/ageGenderNet/AgeGenderNet.js.map
View File

@ -1 +1 @@
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12
build/ageGenderNet/extractParams.js
View File

@ -1,11 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractParams = void 0;
const common_1 = require("../common");
function extractParams(weights) {
import { extractFCParamsFactory, extractWeightsFactory } from '../common';
export function extractParams(weights) {
const paramMappings = [];
const { extractWeights, getRemainingWeights } = common_1.extractWeightsFactory(weights);
const extractFCParams = common_1.extractFCParamsFactory(extractWeights, paramMappings);
const { extractWeights, getRemainingWeights } = extractWeightsFactory(weights);
const extractFCParams = extractFCParamsFactory(extractWeights, paramMappings);
const age = extractFCParams(512, 1, 'fc/age');
const gender = extractFCParams(512, 2, 'fc/gender');
if (getRemainingWeights().length !== 0) {
@ -16,5 +13,4 @@ function extractParams(weights) {
params: { fc: { age, gender } }
};
}
exports.extractParams = extractParams;
//# sourceMappingURL=extractParams.js.map

2
build/ageGenderNet/extractParams.js.map
View File

@ -1 +1 @@
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12
build/ageGenderNet/extractParamsFromWeigthMap.js
View File

@ -1,10 +1,7 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractParamsFromWeigthMap = void 0;
const common_1 = require("../common");
function extractParamsFromWeigthMap(weightMap) {
import { disposeUnusedWeightTensors, extractWeightEntryFactory } from '../common';
export function extractParamsFromWeigthMap(weightMap) {
const paramMappings = [];
const extractWeightEntry = common_1.extractWeightEntryFactory(weightMap, paramMappings);
const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings);
function extractFcParams(prefix) {
const weights = extractWeightEntry(`${prefix}/weights`, 2);
const bias = extractWeightEntry(`${prefix}/bias`, 1);
@ -16,8 +13,7 @@ function extractParamsFromWeigthMap(weightMap) {
gender: extractFcParams('fc/gender')
}
};
common_1.disposeUnusedWeightTensors(weightMap, paramMappings);
disposeUnusedWeightTensors(weightMap, paramMappings);
return { params, paramMappings };
}
exports.extractParamsFromWeigthMap = extractParamsFromWeigthMap;
//# sourceMappingURL=extractParamsFromWeigthMap.js.map

2
build/ageGenderNet/extractParamsFromWeigthMap.js.map
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@ -1 +1 @@
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7
build/ageGenderNet/index.js
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@ -1,6 +1,3 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
const tslib_1 = require("tslib");
tslib_1.__exportStar(require("./AgeGenderNet"), exports);
tslib_1.__exportStar(require("./types"), exports);
export * from './AgeGenderNet';
export * from './types';
//# sourceMappingURL=index.js.map

2
build/ageGenderNet/index.js.map
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@ -1 +1 @@
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7
build/ageGenderNet/types.js
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@ -1,9 +1,6 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.Gender = void 0;
var Gender;
export var Gender;
(function (Gender) {
Gender["FEMALE"] = "female";
Gender["MALE"] = "male";
})(Gender = exports.Gender || (exports.Gender = {}));
})(Gender || (Gender = {}));
//# sourceMappingURL=types.js.map

2
build/ageGenderNet/types.js.map
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8
build/classes/BoundingBox.js
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@ -1,11 +1,7 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.BoundingBox = void 0;
const Box_1 = require("./Box");
class BoundingBox extends Box_1.Box {
import { Box } from './Box';
export class BoundingBox extends Box {
constructor(left, top, right, bottom, allowNegativeDimensions = false) {
super({ left, top, right, bottom }, allowNegativeDimensions);
}
}
exports.BoundingBox = BoundingBox;
//# sourceMappingURL=BoundingBox.js.map

2
build/classes/BoundingBox.js.map
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28
build/classes/Box.js
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@ -1,13 +1,10 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.Box = void 0;
const utils_1 = require("../utils");
const Point_1 = require("./Point");
class Box {
import { isDimensions, isValidNumber } from '../utils';
import { Point } from './Point';
export class Box {
constructor(_box, allowNegativeDimensions = true) {
const box = (_box || {});
const isBbox = [box.left, box.top, box.right, box.bottom].every(utils_1.isValidNumber);
const isRect = [box.x, box.y, box.width, box.height].every(utils_1.isValidNumber);
const isBbox = [box.left, box.top, box.right, box.bottom].every(isValidNumber);
const isRect = [box.x, box.y, box.width, box.height].every(isValidNumber);
if (!isRect && !isBbox) {
throw new Error(`Box.constructor - expected box to be IBoundingBox | IRect, instead have ${JSON.stringify(box)}`);
}
@ -21,7 +18,7 @@ class Box {
this._height = height;
}
static isRect(rect) {
return !!rect && [rect.x, rect.y, rect.width, rect.height].every(utils_1.isValidNumber);
return !!rect && [rect.x, rect.y, rect.width, rect.height].every(isValidNumber);
}
static assertIsValidBox(box, callee, allowNegativeDimensions = false) {
if (!Box.isRect(box)) {
@ -40,10 +37,10 @@ class Box {
get right() { return this.x + this.width; }
get bottom() { return this.y + this.height; }
get area() { return this.width * this.height; }
get topLeft() { return new Point_1.Point(this.left, this.top); }
get topRight() { return new Point_1.Point(this.right, this.top); }
get bottomLeft() { return new Point_1.Point(this.left, this.bottom); }
get bottomRight() { return new Point_1.Point(this.right, this.bottom); }
get topLeft() { return new Point(this.left, this.top); }
get topRight() { return new Point(this.right, this.top); }
get bottomLeft() { return new Point(this.left, this.bottom); }
get bottomRight() { return new Point(this.right, this.bottom); }
round() {
const [x, y, width, height] = [this.x, this.y, this.width, this.height]
.map(val => Math.round(val));
@ -68,8 +65,8 @@ class Box {
return new Box({ x, y, width, height });
}
rescale(s) {
const scaleX = utils_1.isDimensions(s) ? s.width : s;
const scaleY = utils_1.isDimensions(s) ? s.height : s;
const scaleX = isDimensions(s) ? s.width : s;
const scaleY = isDimensions(s) ? s.height : s;
return new Box({
x: this.x * scaleX,
y: this.y * scaleY,
@ -140,5 +137,4 @@ class Box {
}).toSquare().round();
}
}
exports.Box = Box;
//# sourceMappingURL=Box.js.map

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10
build/classes/Dimensions.js
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@ -1,10 +1,7 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.Dimensions = void 0;
const utils_1 = require("../utils");
class Dimensions {
import { isValidNumber } from '../utils';
export class Dimensions {
constructor(width, height) {
if (!utils_1.isValidNumber(width) || !utils_1.isValidNumber(height)) {
if (!isValidNumber(width) || !isValidNumber(height)) {
throw new Error(`Dimensions.constructor - expected width and height to be valid numbers, instead have ${JSON.stringify({ width, height })}`);
}
this._width = width;
@ -16,5 +13,4 @@ class Dimensions {
return new Dimensions(1 / this.width, 1 / this.height);
}
}
exports.Dimensions = Dimensions;
//# sourceMappingURL=Dimensions.js.map

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build/classes/Dimensions.js.map
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8
build/classes/FaceDetection.js
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@ -1,8 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.FaceDetection = void 0;
const ObjectDetection_1 = require("./ObjectDetection");
class FaceDetection extends ObjectDetection_1.ObjectDetection {
import { ObjectDetection } from './ObjectDetection';
export class FaceDetection extends ObjectDetection {
constructor(score, relativeBox, imageDims) {
super(score, score, '', relativeBox, imageDims);
}
@ -11,5 +8,4 @@ class FaceDetection extends ObjectDetection_1.ObjectDetection {
return new FaceDetection(score, relativeBox, imageDims);
}
}
exports.FaceDetection = FaceDetection;
//# sourceMappingURL=FaceDetection.js.map

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build/classes/FaceDetection.js.map
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42
build/classes/FaceLandmarks.js
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@ -1,36 +1,33 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.FaceLandmarks = void 0;
const ops_1 = require("../ops");
const utils_1 = require("../utils");
const Box_1 = require("./Box");
const Dimensions_1 = require("./Dimensions");
const FaceDetection_1 = require("./FaceDetection");
const Point_1 = require("./Point");
const Rect_1 = require("./Rect");
import { minBbox } from '../ops';
import { getCenterPoint } from '../utils';
import { Box } from './Box';
import { Dimensions } from './Dimensions';
import { FaceDetection } from './FaceDetection';
import { Point } from './Point';
import { Rect } from './Rect';
// face alignment constants
const relX = 0.5;
const relY = 0.43;
const relScale = 0.45;
class FaceLandmarks {
constructor(relativeFaceLandmarkPositions, imgDims, shift = new Point_1.Point(0, 0)) {
export class FaceLandmarks {
constructor(relativeFaceLandmarkPositions, imgDims, shift = new Point(0, 0)) {
const { width, height } = imgDims;
this._imgDims = new Dimensions_1.Dimensions(width, height);
this._imgDims = new Dimensions(width, height);
this._shift = shift;
this._positions = relativeFaceLandmarkPositions.map(pt => pt.mul(new Point_1.Point(width, height)).add(shift));
this._positions = relativeFaceLandmarkPositions.map(pt => pt.mul(new Point(width, height)).add(shift));
}
get shift() { return new Point_1.Point(this._shift.x, this._shift.y); }
get shift() { return new Point(this._shift.x, this._shift.y); }
get imageWidth() { return this._imgDims.width; }
get imageHeight() { return this._imgDims.height; }
get positions() { return this._positions; }
get relativePositions() {
return this._positions.map(pt => pt.sub(this._shift).div(new Point_1.Point(this.imageWidth, this.imageHeight)));
return this._positions.map(pt => pt.sub(this._shift).div(new Point(this.imageWidth, this.imageHeight)));
}
forSize(width, height) {
return new this.constructor(this.relativePositions, { width, height });
}
shiftBy(x, y) {
return new this.constructor(this.relativePositions, this._imgDims, new Point_1.Point(x, y));
return new this.constructor(this.relativePositions, this._imgDims, new Point(x, y));
}
shiftByPoint(pt) {
return this.shiftBy(pt.x, pt.y);
@ -48,9 +45,9 @@ class FaceLandmarks {
*/
align(detection, options = {}) {
if (detection) {
const box = detection instanceof FaceDetection_1.FaceDetection
const box = detection instanceof FaceDetection
? detection.box.floor()
: new Box_1.Box(detection);
: new Box(detection);
return this.shiftBy(box.x, box.y).align(null, options);
}
const { useDlibAlignment, minBoxPadding } = Object.assign({}, { useDlibAlignment: false, minBoxPadding: 0.2 }, options);
@ -65,19 +62,18 @@ class FaceLandmarks {
const distToMouth = (pt) => mouthCenter.sub(pt).magnitude();
const eyeToMouthDist = (distToMouth(leftEyeCenter) + distToMouth(rightEyeCenter)) / 2;
const size = Math.floor(eyeToMouthDist / relScale);
const refPoint = utils_1.getCenterPoint(centers);
const refPoint = getCenterPoint(centers);
// TODO: pad in case rectangle is out of image bounds
const x = Math.floor(Math.max(0, refPoint.x - (relX * size)));
const y = Math.floor(Math.max(0, refPoint.y - (relY * size)));
return new Rect_1.Rect(x, y, Math.min(size, this.imageWidth + x), Math.min(size, this.imageHeight + y));
return new Rect(x, y, Math.min(size, this.imageWidth + x), Math.min(size, this.imageHeight + y));
}
alignMinBbox(padding) {
const box = ops_1.minBbox(this.positions);
const box = minBbox(this.positions);
return box.pad(box.width * padding, box.height * padding);
}
getRefPointsForAlignment() {
throw new Error('getRefPointsForAlignment not implemented by base class');
}
}
exports.FaceLandmarks = FaceLandmarks;
//# sourceMappingURL=FaceLandmarks.js.map

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@ -1 +1 @@
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12
build/classes/FaceLandmarks5.js
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@ -1,17 +1,13 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.FaceLandmarks5 = void 0;
const utils_1 = require("../utils");
const FaceLandmarks_1 = require("./FaceLandmarks");
class FaceLandmarks5 extends FaceLandmarks_1.FaceLandmarks {
import { getCenterPoint } from '../utils';
import { FaceLandmarks } from './FaceLandmarks';
export class FaceLandmarks5 extends FaceLandmarks {
getRefPointsForAlignment() {
const pts = this.positions;
return [
pts[0],
pts[1],
utils_1.getCenterPoint([pts[3], pts[4]])
getCenterPoint([pts[3], pts[4]])
];
}
}
exports.FaceLandmarks5 = FaceLandmarks5;
//# sourceMappingURL=FaceLandmarks5.js.map

2
build/classes/FaceLandmarks5.js.map
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@ -1 +1 @@
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12
build/classes/FaceLandmarks68.js
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@ -1,9 +1,6 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.FaceLandmarks68 = void 0;
const utils_1 = require("../utils");
const FaceLandmarks_1 = require("./FaceLandmarks");
class FaceLandmarks68 extends FaceLandmarks_1.FaceLandmarks {
import { getCenterPoint } from '../utils';
import { FaceLandmarks } from './FaceLandmarks';
export class FaceLandmarks68 extends FaceLandmarks {
getJawOutline() {
return this.positions.slice(0, 17);
}
@ -30,8 +27,7 @@ class FaceLandmarks68 extends FaceLandmarks_1.FaceLandmarks {
this.getLeftEye(),
this.getRightEye(),
this.getMouth()
].map(utils_1.getCenterPoint);
].map(getCenterPoint);
}
}
exports.FaceLandmarks68 = FaceLandmarks68;
//# sourceMappingURL=FaceLandmarks68.js.map

2
build/classes/FaceLandmarks68.js.map
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@ -1 +1 @@
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10
build/classes/FaceMatch.js
View File

@ -1,8 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.FaceMatch = void 0;
const utils_1 = require("../utils");
class FaceMatch {
import { round } from '../utils';
export class FaceMatch {
constructor(label, distance) {
this._label = label;
this._distance = distance;
@ -10,8 +7,7 @@ class FaceMatch {
get label() { return this._label; }
get distance() { return this._distance; }
toString(withDistance = true) {
return `${this.label}${withDistance ? ` (${utils_1.round(this.distance)})` : ''}`;
return `${this.label}${withDistance ? ` (${round(this.distance)})` : ''}`;
}
}
exports.FaceMatch = FaceMatch;
//# sourceMappingURL=FaceMatch.js.map

2
build/classes/FaceMatch.js.map
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@ -1 +1 @@
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14
build/classes/LabeledBox.js
View File

@ -1,20 +1,16 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.LabeledBox = void 0;
const utils_1 = require("../utils");
const Box_1 = require("./Box");
class LabeledBox extends Box_1.Box {
import { isValidNumber } from '../utils';
import { Box } from './Box';
export class LabeledBox extends Box {
constructor(box, label) {
super(box);
this._label = label;
}
static assertIsValidLabeledBox(box, callee) {
Box_1.Box.assertIsValidBox(box, callee);
if (!utils_1.isValidNumber(box.label)) {
Box.assertIsValidBox(box, callee);
if (!isValidNumber(box.label)) {
throw new Error(`${callee} - expected property label (${box.label}) to be a number`);
}
}
get label() { return this._label; }
}
exports.LabeledBox = LabeledBox;
//# sourceMappingURL=LabeledBox.js.map

2
build/classes/LabeledBox.js.map
View File

@ -1 +1 @@
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6
build/classes/LabeledFaceDescriptors.js
View File

@ -1,7 +1,4 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.LabeledFaceDescriptors = void 0;
class LabeledFaceDescriptors {
export class LabeledFaceDescriptors {
constructor(label, descriptors) {
if (!(typeof label === 'string')) {
throw new Error('LabeledFaceDescriptors - constructor expected label to be a string');
@ -27,5 +24,4 @@ class LabeledFaceDescriptors {
return new LabeledFaceDescriptors(json.label, descriptors);
}
}
exports.LabeledFaceDescriptors = LabeledFaceDescriptors;
//# sourceMappingURL=LabeledFaceDescriptors.js.map

2
build/classes/LabeledFaceDescriptors.js.map
View File

@ -1 +1 @@
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16
build/classes/ObjectDetection.js
View File

@ -1,15 +1,12 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.ObjectDetection = void 0;
const Box_1 = require("./Box");
const Dimensions_1 = require("./Dimensions");
class ObjectDetection {
import { Box } from './Box';
import { Dimensions } from './Dimensions';
export class ObjectDetection {
constructor(score, classScore, className, relativeBox, imageDims) {
this._imageDims = new Dimensions_1.Dimensions(imageDims.width, imageDims.height);
this._imageDims = new Dimensions(imageDims.width, imageDims.height);
this._score = score;
this._classScore = classScore;
this._className = className;
this._box = new Box_1.Box(relativeBox).rescale(this._imageDims);
this._box = new Box(relativeBox).rescale(this._imageDims);
}
get score() { return this._score; }
get classScore() { return this._classScore; }
@ -18,10 +15,9 @@ class ObjectDetection {
get imageDims() { return this._imageDims; }
get imageWidth() { return this.imageDims.width; }
get imageHeight() { return this.imageDims.height; }
get relativeBox() { return new Box_1.Box(this._box).rescale(this.imageDims.reverse()); }
get relativeBox() { return new Box(this._box).rescale(this.imageDims.reverse()); }
forSize(width, height) {
return new ObjectDetection(this.score, this.classScore, this.className, this.relativeBox, { width, height });
}
}
exports.ObjectDetection = ObjectDetection;
//# sourceMappingURL=ObjectDetection.js.map

2
build/classes/ObjectDetection.js.map
View File

@ -1 +1 @@
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6
build/classes/Point.js
View File

@ -1,7 +1,4 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.Point = void 0;
class Point {
export class Point {
constructor(x, y) {
this._x = x;
this._y = y;
@ -30,5 +27,4 @@ class Point {
return new Point(Math.floor(this.x), Math.floor(this.y));
}
}
exports.Point = Point;
//# sourceMappingURL=Point.js.map

2
build/classes/Point.js.map
View File

@ -1 +1 @@
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16
build/classes/PredictedBox.js
View File

@ -1,23 +1,19 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.PredictedBox = void 0;
const utils_1 = require("../utils");
const LabeledBox_1 = require("./LabeledBox");
class PredictedBox extends LabeledBox_1.LabeledBox {
import { isValidProbablitiy } from '../utils';
import { LabeledBox } from './LabeledBox';
export class PredictedBox extends LabeledBox {
constructor(box, label, score, classScore) {
super(box, label);
this._score = score;
this._classScore = classScore;
}
static assertIsValidPredictedBox(box, callee) {
LabeledBox_1.LabeledBox.assertIsValidLabeledBox(box, callee);
if (!utils_1.isValidProbablitiy(box.score)
|| !utils_1.isValidProbablitiy(box.classScore)) {
LabeledBox.assertIsValidLabeledBox(box, callee);
if (!isValidProbablitiy(box.score)
|| !isValidProbablitiy(box.classScore)) {
throw new Error(`${callee} - expected properties score (${box.score}) and (${box.classScore}) to be a number between [0, 1]`);
}
}
get score() { return this._score; }
get classScore() { return this._classScore; }
}
exports.PredictedBox = PredictedBox;
//# sourceMappingURL=PredictedBox.js.map

2
build/classes/PredictedBox.js.map
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@ -1 +1 @@
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8
build/classes/Rect.js
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@ -1,11 +1,7 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.Rect = void 0;
const Box_1 = require("./Box");
class Rect extends Box_1.Box {
import { Box } from './Box';
export class Rect extends Box {
constructor(x, y, width, height, allowNegativeDimensions = false) {
super({ x, y, width, height }, allowNegativeDimensions);
}
}
exports.Rect = Rect;
//# sourceMappingURL=Rect.js.map

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build/classes/Rect.js.map
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@ -1 +1 @@
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31
build/classes/index.js
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@ -1,18 +1,15 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
const tslib_1 = require("tslib");
tslib_1.__exportStar(require("./BoundingBox"), exports);
tslib_1.__exportStar(require("./Box"), exports);
tslib_1.__exportStar(require("./Dimensions"), exports);
tslib_1.__exportStar(require("./FaceDetection"), exports);
tslib_1.__exportStar(require("./FaceLandmarks"), exports);
tslib_1.__exportStar(require("./FaceLandmarks5"), exports);
tslib_1.__exportStar(require("./FaceLandmarks68"), exports);
tslib_1.__exportStar(require("./FaceMatch"), exports);
tslib_1.__exportStar(require("./LabeledBox"), exports);
tslib_1.__exportStar(require("./LabeledFaceDescriptors"), exports);
tslib_1.__exportStar(require("./ObjectDetection"), exports);
tslib_1.__exportStar(require("./Point"), exports);
tslib_1.__exportStar(require("./PredictedBox"), exports);
tslib_1.__exportStar(require("./Rect"), exports);
export * from './BoundingBox';
export * from './Box';
export * from './Dimensions';
export * from './FaceDetection';
export * from './FaceLandmarks';
export * from './FaceLandmarks5';
export * from './FaceLandmarks68';
export * from './FaceMatch';
export * from './LabeledBox';
export * from './LabeledFaceDescriptors';
export * from './ObjectDetection';
export * from './Point';
export * from './PredictedBox';
export * from './Rect';
//# sourceMappingURL=index.js.map

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build/classes/index.js.map
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@ -1 +1 @@
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8
build/common/convLayer.js
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@ -1,12 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.convLayer = void 0;
const tf = require("@tensorflow/tfjs-core");
function convLayer(x, params, padding = 'same', withRelu = false) {
import * as tf from '@tensorflow/tfjs-core';
export function convLayer(x, params, padding = 'same', withRelu = false) {
return tf.tidy(() => {
const out = tf.add(tf.conv2d(x, params.filters, [1, 1], padding), params.bias);
return withRelu ? tf.relu(out) : out;
});
}
exports.convLayer = convLayer;
//# sourceMappingURL=convLayer.js.map

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build/common/convLayer.js.map
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8
build/common/depthwiseSeparableConv.js
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@ -1,13 +1,9 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.depthwiseSeparableConv = void 0;
const tf = require("@tensorflow/tfjs-core");
function depthwiseSeparableConv(x, params, stride) {
import * as tf from '@tensorflow/tfjs-core';
export function depthwiseSeparableConv(x, params, stride) {
return tf.tidy(() => {
let out = tf.separableConv2d(x, params.depthwise_filter, params.pointwise_filter, stride, 'same');
out = tf.add(out, params.bias);
return out;
});
}
exports.depthwiseSeparableConv = depthwiseSeparableConv;
//# sourceMappingURL=depthwiseSeparableConv.js.map

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build/common/depthwiseSeparableConv.js.map
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@ -1 +1 @@
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6
build/common/disposeUnusedWeightTensors.js
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@ -1,12 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.disposeUnusedWeightTensors = void 0;
function disposeUnusedWeightTensors(weightMap, paramMappings) {
export function disposeUnusedWeightTensors(weightMap, paramMappings) {
Object.keys(weightMap).forEach(path => {
if (!paramMappings.some(pm => pm.originalPath === path)) {
weightMap[path].dispose();
}
});
}
exports.disposeUnusedWeightTensors = disposeUnusedWeightTensors;
//# sourceMappingURL=disposeUnusedWeightTensors.js.map

2
build/common/disposeUnusedWeightTensors.js.map
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8
build/common/extractConvParamsFactory.js
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@ -1,8 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractConvParamsFactory = void 0;
const tf = require("@tensorflow/tfjs-core");
function extractConvParamsFactory(extractWeights, paramMappings) {
import * as tf from '@tensorflow/tfjs-core';
export function extractConvParamsFactory(extractWeights, paramMappings) {
return function (channelsIn, channelsOut, filterSize, mappedPrefix) {
const filters = tf.tensor4d(extractWeights(channelsIn * channelsOut * filterSize * filterSize), [filterSize, filterSize, channelsIn, channelsOut]);
const bias = tf.tensor1d(extractWeights(channelsOut));
@ -10,5 +7,4 @@ function extractConvParamsFactory(extractWeights, paramMappings) {
return { filters, bias };
};
}
exports.extractConvParamsFactory = extractConvParamsFactory;
//# sourceMappingURL=extractConvParamsFactory.js.map

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build/common/extractConvParamsFactory.js.map
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8
build/common/extractFCParamsFactory.js
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@ -1,8 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractFCParamsFactory = void 0;
const tf = require("@tensorflow/tfjs-core");
function extractFCParamsFactory(extractWeights, paramMappings) {
import * as tf from '@tensorflow/tfjs-core';
export function extractFCParamsFactory(extractWeights, paramMappings) {
return function (channelsIn, channelsOut, mappedPrefix) {
const fc_weights = tf.tensor2d(extractWeights(channelsIn * channelsOut), [channelsIn, channelsOut]);
const fc_bias = tf.tensor1d(extractWeights(channelsOut));
@ -13,5 +10,4 @@ function extractFCParamsFactory(extractWeights, paramMappings) {
};
};
}
exports.extractFCParamsFactory = extractFCParamsFactory;
//# sourceMappingURL=extractFCParamsFactory.js.map

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build/common/extractFCParamsFactory.js.map
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17
build/common/extractSeparableConvParamsFactory.js
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@ -1,25 +1,20 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.loadSeparableConvParamsFactory = exports.extractSeparableConvParamsFactory = void 0;
const tf = require("@tensorflow/tfjs-core");
const types_1 = require("./types");
function extractSeparableConvParamsFactory(extractWeights, paramMappings) {
import * as tf from '@tensorflow/tfjs-core';
import { SeparableConvParams } from './types';
export function extractSeparableConvParamsFactory(extractWeights, paramMappings) {
return function (channelsIn, channelsOut, mappedPrefix) {
const depthwise_filter = tf.tensor4d(extractWeights(3 * 3 * channelsIn), [3, 3, channelsIn, 1]);
const pointwise_filter = tf.tensor4d(extractWeights(channelsIn * channelsOut), [1, 1, channelsIn, channelsOut]);
const bias = tf.tensor1d(extractWeights(channelsOut));
paramMappings.push({ paramPath: `${mappedPrefix}/depthwise_filter` }, { paramPath: `${mappedPrefix}/pointwise_filter` }, { paramPath: `${mappedPrefix}/bias` });
return new types_1.SeparableConvParams(depthwise_filter, pointwise_filter, bias);
return new SeparableConvParams(depthwise_filter, pointwise_filter, bias);
};
}
exports.extractSeparableConvParamsFactory = extractSeparableConvParamsFactory;
function loadSeparableConvParamsFactory(extractWeightEntry) {
export function loadSeparableConvParamsFactory(extractWeightEntry) {
return function (prefix) {
const depthwise_filter = extractWeightEntry(`${prefix}/depthwise_filter`, 4);
const pointwise_filter = extractWeightEntry(`${prefix}/pointwise_filter`, 4);
const bias = extractWeightEntry(`${prefix}/bias`, 1);
return new types_1.SeparableConvParams(depthwise_filter, pointwise_filter, bias);
return new SeparableConvParams(depthwise_filter, pointwise_filter, bias);
};
}
exports.loadSeparableConvParamsFactory = loadSeparableConvParamsFactory;
//# sourceMappingURL=extractSeparableConvParamsFactory.js.map

2
build/common/extractSeparableConvParamsFactory.js.map
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@ -1 +1 @@
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10
build/common/extractWeightEntryFactory.js
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@ -1,16 +1,12 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractWeightEntryFactory = void 0;
const utils_1 = require("../utils");
function extractWeightEntryFactory(weightMap, paramMappings) {
import { isTensor } from '../utils';
export function extractWeightEntryFactory(weightMap, paramMappings) {
return function (originalPath, paramRank, mappedPath) {
const tensor = weightMap[originalPath];
if (!utils_1.isTensor(tensor, paramRank)) {
if (!isTensor(tensor, paramRank)) {
throw new Error(`expected weightMap[${originalPath}] to be a Tensor${paramRank}D, instead have ${tensor}`);
}
paramMappings.push({ originalPath, paramPath: mappedPath || originalPath });
return tensor;
};
}
exports.extractWeightEntryFactory = extractWeightEntryFactory;
//# sourceMappingURL=extractWeightEntryFactory.js.map

2
build/common/extractWeightEntryFactory.js.map
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@ -1 +1 @@
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6
build/common/extractWeightsFactory.js
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@ -1,7 +1,4 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractWeightsFactory = void 0;
function extractWeightsFactory(weights) {
export function extractWeightsFactory(weights) {
let remainingWeights = weights;
function extractWeights(numWeights) {
const ret = remainingWeights.slice(0, numWeights);
@ -16,5 +13,4 @@ function extractWeightsFactory(weights) {
getRemainingWeights
};
}
exports.extractWeightsFactory = extractWeightsFactory;
//# sourceMappingURL=extractWeightsFactory.js.map

2
build/common/extractWeightsFactory.js.map
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@ -1 +1 @@
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8
build/common/fullyConnectedLayer.js
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@ -1,9 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.fullyConnectedLayer = void 0;
const tf = require("@tensorflow/tfjs-core");
function fullyConnectedLayer(x, params) {
import * as tf from '@tensorflow/tfjs-core';
export function fullyConnectedLayer(x, params) {
return tf.tidy(() => tf.add(tf.matMul(x, params.weights), params.bias));
}
exports.fullyConnectedLayer = fullyConnectedLayer;
//# sourceMappingURL=fullyConnectedLayer.js.map

2
build/common/fullyConnectedLayer.js.map
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@ -1 +1 @@
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6
build/common/getModelUris.js
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@ -1,7 +1,4 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.getModelUris = void 0;
function getModelUris(uri, defaultModelName) {
export function getModelUris(uri, defaultModelName) {
const defaultManifestFilename = `${defaultModelName}-weights_manifest.json`;
if (!uri) {
return {
@ -28,5 +25,4 @@ function getModelUris(uri, defaultModelName) {
manifestUri: modelBaseUri === '/' ? `/${manifestFile}` : `${modelBaseUri}/${manifestFile}`
};
}
exports.getModelUris = getModelUris;
//# sourceMappingURL=getModelUris.js.map

2
build/common/getModelUris.js.map
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@ -1 +1 @@
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23
build/common/index.js
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@ -1,14 +1,11 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
const tslib_1 = require("tslib");
tslib_1.__exportStar(require("./convLayer"), exports);
tslib_1.__exportStar(require("./depthwiseSeparableConv"), exports);
tslib_1.__exportStar(require("./disposeUnusedWeightTensors"), exports);
tslib_1.__exportStar(require("./extractConvParamsFactory"), exports);
tslib_1.__exportStar(require("./extractFCParamsFactory"), exports);
tslib_1.__exportStar(require("./extractSeparableConvParamsFactory"), exports);
tslib_1.__exportStar(require("./extractWeightEntryFactory"), exports);
tslib_1.__exportStar(require("./extractWeightsFactory"), exports);
tslib_1.__exportStar(require("./getModelUris"), exports);
tslib_1.__exportStar(require("./types"), exports);
export * from './convLayer';
export * from './depthwiseSeparableConv';
export * from './disposeUnusedWeightTensors';
export * from './extractConvParamsFactory';
export * from './extractFCParamsFactory';
export * from './extractSeparableConvParamsFactory';
export * from './extractWeightEntryFactory';
export * from './extractWeightsFactory';
export * from './getModelUris';
export * from './types';
//# sourceMappingURL=index.js.map

2
build/common/index.js.map
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@ -1 +1 @@
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6
build/common/loadConvParamsFactory.js
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@ -1,12 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.loadConvParamsFactory = void 0;
function loadConvParamsFactory(extractWeightEntry) {
export function loadConvParamsFactory(extractWeightEntry) {
return function (prefix) {
const filters = extractWeightEntry(`${prefix}/filters`, 4);
const bias = extractWeightEntry(`${prefix}/bias`, 1);
return { filters, bias };
};
}
exports.loadConvParamsFactory = loadConvParamsFactory;
//# sourceMappingURL=loadConvParamsFactory.js.map

2
build/common/loadConvParamsFactory.js.map
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@ -1 +1 @@
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6
build/common/types.js
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@ -1,12 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.SeparableConvParams = void 0;
class SeparableConvParams {
export class SeparableConvParams {
constructor(depthwise_filter, pointwise_filter, bias) {
this.depthwise_filter = depthwise_filter;
this.pointwise_filter = pointwise_filter;
this.bias = bias;
}
}
exports.SeparableConvParams = SeparableConvParams;
//# sourceMappingURL=types.js.map

2
build/common/types.js.map
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@ -1 +1 @@
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38
build/dom/NetInput.js
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@ -1,13 +1,10 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.NetInput = void 0;
const tf = require("@tensorflow/tfjs-core");
const env_1 = require("../env");
const padToSquare_1 = require("../ops/padToSquare");
const utils_1 = require("../utils");
const createCanvas_1 = require("./createCanvas");
const imageToSquare_1 = require("./imageToSquare");
class NetInput {
import * as tf from '@tensorflow/tfjs-core';
import { env } from '../env';
import { padToSquare } from '../ops/padToSquare';
import { computeReshapedDimensions, isTensor3D, isTensor4D, range } from '../utils';
import { createCanvasFromMedia } from './createCanvas';
import { imageToSquare } from './imageToSquare';
export class NetInput {
constructor(inputs, treatAsBatchInput = false) {
this._imageTensors = [];
this._canvases = [];
@ -19,12 +16,12 @@ class NetInput {
this._treatAsBatchInput = treatAsBatchInput;
this._batchSize = inputs.length;
inputs.forEach((input, idx) => {
if (utils_1.isTensor3D(input)) {
if (isTensor3D(input)) {
this._imageTensors[idx] = input;
this._inputDimensions[idx] = input.shape;
return;
}
if (utils_1.isTensor4D(input)) {
if (isTensor4D(input)) {
const batchSize = input.shape[0];
if (batchSize !== 1) {
throw new Error(`NetInput - tf.Tensor4D with batchSize ${batchSize} passed, but not supported in input array`);
@ -33,7 +30,7 @@ class NetInput {
this._inputDimensions[idx] = input.shape.slice(1);
return;
}
const canvas = input instanceof env_1.env.getEnv().Canvas ? input : createCanvas_1.createCanvasFromMedia(input);
const canvas = input instanceof env.getEnv().Canvas ? input : createCanvasFromMedia(input);
this._canvases[idx] = canvas;
this._inputDimensions[idx] = [canvas.height, canvas.width, 3];
});
@ -57,7 +54,7 @@ class NetInput {
return this._inputSize;
}
get reshapedInputDimensions() {
return utils_1.range(this.batchSize, 0, 1).map((_, batchIdx) => this.getReshapedInputDimensions(batchIdx));
return range(this.batchSize, 0, 1).map((_, batchIdx) => this.getReshapedInputDimensions(batchIdx));
}
getInput(batchIdx) {
return this.canvases[batchIdx] || this.imageTensors[batchIdx];
@ -77,7 +74,7 @@ class NetInput {
}
const width = this.getInputWidth(batchIdx);
const height = this.getInputHeight(batchIdx);
return utils_1.computeReshapedDimensions({ width, height }, this.inputSize);
return computeReshapedDimensions({ width, height }, this.inputSize);
}
/**
* Create a batch tensor from all input canvases and tensors
@ -91,20 +88,20 @@ class NetInput {
toBatchTensor(inputSize, isCenterInputs = true) {
this._inputSize = inputSize;
return tf.tidy(() => {
const inputTensors = utils_1.range(this.batchSize, 0, 1).map(batchIdx => {
const inputTensors = range(this.batchSize, 0, 1).map(batchIdx => {
const input = this.getInput(batchIdx);
if (input instanceof tf.Tensor) {
// @ts-ignore: error TS2344: Type 'Rank.R4' does not satisfy the constraint 'Tensor<Rank>'.
let imgTensor = utils_1.isTensor4D(input) ? input : input.expandDims();
let imgTensor = isTensor4D(input) ? input : input.expandDims();
// @ts-ignore: error TS2344: Type 'Rank.R4' does not satisfy the constraint 'Tensor<Rank>'.
imgTensor = padToSquare_1.padToSquare(imgTensor, isCenterInputs);
imgTensor = padToSquare(imgTensor, isCenterInputs);
if (imgTensor.shape[1] !== inputSize || imgTensor.shape[2] !== inputSize) {
imgTensor = tf.image.resizeBilinear(imgTensor, [inputSize, inputSize]);
}
return imgTensor.as3D(inputSize, inputSize, 3);
}
if (input instanceof env_1.env.getEnv().Canvas) {
return tf.browser.fromPixels(imageToSquare_1.imageToSquare(input, inputSize, isCenterInputs));
if (input instanceof env.getEnv().Canvas) {
return tf.browser.fromPixels(imageToSquare(input, inputSize, isCenterInputs));
}
throw new Error(`toBatchTensor - at batchIdx ${batchIdx}, expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have ${input}`);
});
@ -113,5 +110,4 @@ class NetInput {
});
}
}
exports.NetInput = NetInput;
//# sourceMappingURL=NetInput.js.map

2
build/dom/NetInput.js.map
View File

@ -1 +1 @@
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12
build/dom/awaitMediaLoaded.js
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@ -1,11 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.awaitMediaLoaded = void 0;
const env_1 = require("../env");
const isMediaLoaded_1 = require("./isMediaLoaded");
function awaitMediaLoaded(media) {
import { env } from '../env';
import { isMediaLoaded } from './isMediaLoaded';
export function awaitMediaLoaded(media) {
return new Promise((resolve, reject) => {
if (media instanceof env_1.env.getEnv().Canvas || isMediaLoaded_1.isMediaLoaded(media)) {
if (media instanceof env.getEnv().Canvas || isMediaLoaded(media)) {
return resolve();
}
function onLoad(e) {
@ -26,5 +23,4 @@ function awaitMediaLoaded(media) {
media.addEventListener('error', onError);
});
}
exports.awaitMediaLoaded = awaitMediaLoaded;
//# sourceMappingURL=awaitMediaLoaded.js.map

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build/dom/awaitMediaLoaded.js.map
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@ -1 +1 @@
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10
build/dom/bufferToImage.js
View File

@ -1,8 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.bufferToImage = void 0;
const env_1 = require("../env");
function bufferToImage(buf) {
import { env } from '../env';
export function bufferToImage(buf) {
return new Promise((resolve, reject) => {
if (!(buf instanceof Blob)) {
return reject('bufferToImage - expected buf to be of type: Blob');
@ -12,7 +9,7 @@ function bufferToImage(buf) {
if (typeof reader.result !== 'string') {
return reject('bufferToImage - expected reader.result to be a string, in onload');
}
const img = env_1.env.getEnv().createImageElement();
const img = env.getEnv().createImageElement();
img.onload = () => resolve(img);
img.onerror = reject;
img.src = reader.result;
@ -21,5 +18,4 @@ function bufferToImage(buf) {
reader.readAsDataURL(buf);
});
}
exports.bufferToImage = bufferToImage;
//# sourceMappingURL=bufferToImage.js.map

2
build/dom/bufferToImage.js.map
View File

@ -1 +1 @@
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29
build/dom/createCanvas.js
View File

@ -1,32 +1,27 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.createCanvasFromMedia = exports.createCanvas = void 0;
const env_1 = require("../env");
const getContext2dOrThrow_1 = require("./getContext2dOrThrow");
const getMediaDimensions_1 = require("./getMediaDimensions");
const isMediaLoaded_1 = require("./isMediaLoaded");
function createCanvas({ width, height }) {
const { createCanvasElement } = env_1.env.getEnv();
import { env } from '../env';
import { getContext2dOrThrow } from './getContext2dOrThrow';
import { getMediaDimensions } from './getMediaDimensions';
import { isMediaLoaded } from './isMediaLoaded';
export function createCanvas({ width, height }) {
const { createCanvasElement } = env.getEnv();
const canvas = createCanvasElement();
canvas.width = width;
canvas.height = height;
return canvas;
}
exports.createCanvas = createCanvas;
function createCanvasFromMedia(media, dims) {
const { ImageData } = env_1.env.getEnv();
if (!(media instanceof ImageData) && !isMediaLoaded_1.isMediaLoaded(media)) {
export function createCanvasFromMedia(media, dims) {
const { ImageData } = env.getEnv();
if (!(media instanceof ImageData) && !isMediaLoaded(media)) {
throw new Error('createCanvasFromMedia - media has not finished loading yet');
}
const { width, height } = dims || getMediaDimensions_1.getMediaDimensions(media);
const { width, height } = dims || getMediaDimensions(media);
const canvas = createCanvas({ width, height });
if (media instanceof ImageData) {
getContext2dOrThrow_1.getContext2dOrThrow(canvas).putImageData(media, 0, 0);
getContext2dOrThrow(canvas).putImageData(media, 0, 0);
}
else {
getContext2dOrThrow_1.getContext2dOrThrow(canvas).drawImage(media, 0, 0, width, height);
getContext2dOrThrow(canvas).drawImage(media, 0, 0, width, height);
}
return canvas;
}
exports.createCanvasFromMedia = createCanvasFromMedia;
//# sourceMappingURL=createCanvas.js.map

2
build/dom/createCanvas.js.map
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@ -1 +1 @@
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20
build/dom/extractFaceTensors.js
View File

@ -1,9 +1,6 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractFaceTensors = void 0;
const tf = require("@tensorflow/tfjs-core");
const FaceDetection_1 = require("../classes/FaceDetection");
const utils_1 = require("../utils");
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.
@ -14,16 +11,16 @@ const utils_1 = require("../utils");
* @param detections The face detection results or face bounding boxes for that image.
* @returns Tensors of the corresponding image region for each detected face.
*/
async function extractFaceTensors(imageTensor, detections) {
if (!utils_1.isTensor3D(imageTensor) && !utils_1.isTensor4D(imageTensor)) {
export async function extractFaceTensors(imageTensor, detections) {
if (!isTensor3D(imageTensor) && !isTensor4D(imageTensor)) {
throw new Error('extractFaceTensors - expected image tensor to be 3D or 4D');
}
if (utils_1.isTensor4D(imageTensor) && imageTensor.shape[0] > 1) {
if (isTensor4D(imageTensor) && imageTensor.shape[0] > 1) {
throw new Error('extractFaceTensors - batchSize > 1 not supported');
}
return tf.tidy(() => {
const [imgHeight, imgWidth, numChannels] = imageTensor.shape.slice(utils_1.isTensor4D(imageTensor) ? 1 : 0);
const boxes = detections.map(det => det instanceof FaceDetection_1.FaceDetection
const [imgHeight, imgWidth, numChannels] = imageTensor.shape.slice(isTensor4D(imageTensor) ? 1 : 0);
const boxes = detections.map(det => det instanceof FaceDetection
? det.forSize(imgWidth, imgHeight).box
: det)
.map(box => box.clipAtImageBorders(imgWidth, imgHeight));
@ -31,5 +28,4 @@ async function extractFaceTensors(imageTensor, detections) {
return faceTensors;
});
}
exports.extractFaceTensors = extractFaceTensors;
//# sourceMappingURL=extractFaceTensors.js.map

2
build/dom/extractFaceTensors.js.map
View File

@ -1 +1 @@
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32
build/dom/extractFaces.js
View File

@ -1,12 +1,9 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.extractFaces = void 0;
const FaceDetection_1 = require("../classes/FaceDetection");
const env_1 = require("../env");
const createCanvas_1 = require("./createCanvas");
const getContext2dOrThrow_1 = require("./getContext2dOrThrow");
const imageTensorToCanvas_1 = require("./imageTensorToCanvas");
const toNetInput_1 = require("./toNetInput");
import { FaceDetection } from '../classes/FaceDetection';
import { env } from '../env';
import { createCanvas } from './createCanvas';
import { getContext2dOrThrow } from './getContext2dOrThrow';
import { imageTensorToCanvas } from './imageTensorToCanvas';
import { toNetInput } from './toNetInput';
/**
* Extracts the image regions containing the detected faces.
*
@ -14,30 +11,29 @@ const toNetInput_1 = require("./toNetInput");
* @param detections The face detection results or face bounding boxes for that image.
* @returns The Canvases of the corresponding image region for each detected face.
*/
async function extractFaces(input, detections) {
const { Canvas } = env_1.env.getEnv();
export async function extractFaces(input, detections) {
const { Canvas } = env.getEnv();
let canvas = input;
if (!(input instanceof Canvas)) {
const netInput = await toNetInput_1.toNetInput(input);
const netInput = await toNetInput(input);
if (netInput.batchSize > 1) {
throw new Error('extractFaces - batchSize > 1 not supported');
}
const tensorOrCanvas = netInput.getInput(0);
canvas = tensorOrCanvas instanceof Canvas
? tensorOrCanvas
: await imageTensorToCanvas_1.imageTensorToCanvas(tensorOrCanvas);
: await imageTensorToCanvas(tensorOrCanvas);
}
const ctx = getContext2dOrThrow_1.getContext2dOrThrow(canvas);
const boxes = detections.map(det => det instanceof FaceDetection_1.FaceDetection
const ctx = getContext2dOrThrow(canvas);
const boxes = detections.map(det => det instanceof FaceDetection
? det.forSize(canvas.width, canvas.height).box.floor()
: det)
.map(box => box.clipAtImageBorders(canvas.width, canvas.height));
return boxes.map(({ x, y, width, height }) => {
const faceImg = createCanvas_1.createCanvas({ width, height });
getContext2dOrThrow_1.getContext2dOrThrow(faceImg)
const faceImg = createCanvas({ width, height });
getContext2dOrThrow(faceImg)
.putImageData(ctx.getImageData(x, y, width, height), 0, 0);
return faceImg;
});
}
exports.extractFaces = extractFaces;
//# sourceMappingURL=extractFaces.js.map

2
build/dom/extractFaces.js.map
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@ -1 +1 @@
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14
build/dom/fetchImage.js
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@ -1,15 +1,11 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.fetchImage = void 0;
const bufferToImage_1 = require("./bufferToImage");
const fetchOrThrow_1 = require("./fetchOrThrow");
async function fetchImage(uri) {
const res = await fetchOrThrow_1.fetchOrThrow(uri);
import { bufferToImage } from './bufferToImage';
import { fetchOrThrow } from './fetchOrThrow';
export async function fetchImage(uri) {
const res = await fetchOrThrow(uri);
const blob = await (res).blob();
if (!blob.type.startsWith('image/')) {
throw new Error(`fetchImage - expected blob type to be of type image/*, instead have: ${blob.type}, for url: ${res.url}`);
}
return bufferToImage_1.bufferToImage(blob);
return bufferToImage(blob);
}
exports.fetchImage = fetchImage;
//# sourceMappingURL=fetchImage.js.map

2
build/dom/fetchImage.js.map
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@ -1 +1 @@
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10
build/dom/fetchJson.js
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@ -1,9 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.fetchJson = void 0;
const fetchOrThrow_1 = require("./fetchOrThrow");
async function fetchJson(uri) {
return (await fetchOrThrow_1.fetchOrThrow(uri)).json();
import { fetchOrThrow } from './fetchOrThrow';
export async function fetchJson(uri) {
return (await fetchOrThrow(uri)).json();
}
exports.fetchJson = fetchJson;
//# sourceMappingURL=fetchJson.js.map

2
build/dom/fetchJson.js.map
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@ -1 +1 @@
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10
build/dom/fetchNetWeights.js
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@ -1,9 +1,5 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.fetchNetWeights = void 0;
const fetchOrThrow_1 = require("./fetchOrThrow");
async function fetchNetWeights(uri) {
return new Float32Array(await (await fetchOrThrow_1.fetchOrThrow(uri)).arrayBuffer());
import { fetchOrThrow } from './fetchOrThrow';
export async function fetchNetWeights(uri) {
return new Float32Array(await (await fetchOrThrow(uri)).arrayBuffer());
}
exports.fetchNetWeights = fetchNetWeights;
//# sourceMappingURL=fetchNetWeights.js.map

2
build/dom/fetchNetWeights.js.map
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@ -1 +1 @@
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10
build/dom/fetchOrThrow.js
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@ -1,14 +1,10 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.fetchOrThrow = void 0;
const env_1 = require("../env");
async function fetchOrThrow(url, init) {
const fetch = env_1.env.getEnv().fetch;
import { env } from '../env';
export async function fetchOrThrow(url, init) {
const fetch = env.getEnv().fetch;
const res = await fetch(url, init);
if (!(res.status < 400)) {
throw new Error(`failed to fetch: (${res.status}) ${res.statusText}, from url: ${res.url}`);
}
return res;
}
exports.fetchOrThrow = fetchOrThrow;
//# sourceMappingURL=fetchOrThrow.js.map

2
build/dom/fetchOrThrow.js.map
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@ -1 +1 @@
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14
build/dom/getContext2dOrThrow.js
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@ -1,14 +1,11 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.getContext2dOrThrow = void 0;
const env_1 = require("../env");
const resolveInput_1 = require("./resolveInput");
function getContext2dOrThrow(canvasArg) {
const { Canvas, CanvasRenderingContext2D } = env_1.env.getEnv();
import { env } from '../env';
import { resolveInput } from './resolveInput';
export function getContext2dOrThrow(canvasArg) {
const { Canvas, CanvasRenderingContext2D } = env.getEnv();
if (canvasArg instanceof CanvasRenderingContext2D) {
return canvasArg;
}
const canvas = resolveInput_1.resolveInput(canvasArg);
const canvas = resolveInput(canvasArg);
if (!(canvas instanceof Canvas)) {
throw new Error('resolveContext2d - expected canvas to be of instance of Canvas');
}
@ -18,5 +15,4 @@ function getContext2dOrThrow(canvasArg) {
}
return ctx;
}
exports.getContext2dOrThrow = getContext2dOrThrow;
//# sourceMappingURL=getContext2dOrThrow.js.map

2
build/dom/getContext2dOrThrow.js.map
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@ -1 +1 @@
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18
build/dom/getMediaDimensions.js
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@ -1,17 +1,13 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.getMediaDimensions = void 0;
const Dimensions_1 = require("../classes/Dimensions");
const env_1 = require("../env");
function getMediaDimensions(input) {
const { Image, Video } = env_1.env.getEnv();
import { Dimensions } from '../classes/Dimensions';
import { env } from '../env';
export function getMediaDimensions(input) {
const { Image, Video } = env.getEnv();
if (input instanceof Image) {
return new Dimensions_1.Dimensions(input.naturalWidth, input.naturalHeight);
return new Dimensions(input.naturalWidth, input.naturalHeight);
}
if (input instanceof Video) {
return new Dimensions_1.Dimensions(input.videoWidth, input.videoHeight);
return new Dimensions(input.videoWidth, input.videoHeight);
}
return new Dimensions_1.Dimensions(input.width, input.height);
return new Dimensions(input.width, input.height);
}
exports.getMediaDimensions = getMediaDimensions;
//# sourceMappingURL=getMediaDimensions.js.map

2
build/dom/getMediaDimensions.js.map
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@ -1 +1 @@
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16
build/dom/imageTensorToCanvas.js
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@ -1,16 +1,12 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.imageTensorToCanvas = void 0;
const tf = require("@tensorflow/tfjs-core");
const env_1 = require("../env");
const utils_1 = require("../utils");
async function imageTensorToCanvas(imgTensor, canvas) {
const targetCanvas = canvas || env_1.env.getEnv().createCanvasElement();
const [height, width, numChannels] = imgTensor.shape.slice(utils_1.isTensor4D(imgTensor) ? 1 : 0);
import * as tf from '@tensorflow/tfjs-core';
import { env } from '../env';
import { isTensor4D } from '../utils';
export async function imageTensorToCanvas(imgTensor, canvas) {
const targetCanvas = canvas || env.getEnv().createCanvasElement();
const [height, width, numChannels] = imgTensor.shape.slice(isTensor4D(imgTensor) ? 1 : 0);
const imgTensor3D = tf.tidy(() => imgTensor.as3D(height, width, numChannels).toInt());
await tf.browser.toPixels(imgTensor3D, targetCanvas);
imgTensor3D.dispose();
return targetCanvas;
}
exports.imageTensorToCanvas = imageTensorToCanvas;
//# sourceMappingURL=imageTensorToCanvas.js.map

2
build/dom/imageTensorToCanvas.js.map
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@ -1 +1 @@
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24
build/dom/imageToSquare.js
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@ -1,26 +1,22 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.imageToSquare = void 0;
const env_1 = require("../env");
const createCanvas_1 = require("./createCanvas");
const getContext2dOrThrow_1 = require("./getContext2dOrThrow");
const getMediaDimensions_1 = require("./getMediaDimensions");
function imageToSquare(input, inputSize, centerImage = false) {
const { Image, Canvas } = env_1.env.getEnv();
import { env } from '../env';
import { createCanvas, createCanvasFromMedia } from './createCanvas';
import { getContext2dOrThrow } from './getContext2dOrThrow';
import { getMediaDimensions } from './getMediaDimensions';
export function imageToSquare(input, inputSize, centerImage = false) {
const { Image, Canvas } = env.getEnv();
if (!(input instanceof Image || input instanceof Canvas)) {
throw new Error('imageToSquare - expected arg0 to be HTMLImageElement | HTMLCanvasElement');
}
const dims = getMediaDimensions_1.getMediaDimensions(input);
const dims = getMediaDimensions(input);
const scale = inputSize / Math.max(dims.height, dims.width);
const width = scale * dims.width;
const height = scale * dims.height;
const targetCanvas = createCanvas_1.createCanvas({ width: inputSize, height: inputSize });
const inputCanvas = input instanceof Canvas ? input : createCanvas_1.createCanvasFromMedia(input);
const targetCanvas = createCanvas({ width: inputSize, height: inputSize });
const inputCanvas = input instanceof Canvas ? input : createCanvasFromMedia(input);
const offset = Math.abs(width - height) / 2;
const dx = centerImage && width < height ? offset : 0;
const dy = centerImage && height < width ? offset : 0;
getContext2dOrThrow_1.getContext2dOrThrow(targetCanvas).drawImage(inputCanvas, dx, dy, width, height);
getContext2dOrThrow(targetCanvas).drawImage(inputCanvas, dx, dy, width, height);
return targetCanvas;
}
exports.imageToSquare = imageToSquare;
//# sourceMappingURL=imageToSquare.js.map

2
build/dom/imageToSquare.js.map
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45
build/dom/index.js
View File

@ -1,25 +1,22 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
const tslib_1 = require("tslib");
tslib_1.__exportStar(require("./awaitMediaLoaded"), exports);
tslib_1.__exportStar(require("./bufferToImage"), exports);
tslib_1.__exportStar(require("./createCanvas"), exports);
tslib_1.__exportStar(require("./extractFaces"), exports);
tslib_1.__exportStar(require("./extractFaceTensors"), exports);
tslib_1.__exportStar(require("./fetchImage"), exports);
tslib_1.__exportStar(require("./fetchJson"), exports);
tslib_1.__exportStar(require("./fetchNetWeights"), exports);
tslib_1.__exportStar(require("./fetchOrThrow"), exports);
tslib_1.__exportStar(require("./getContext2dOrThrow"), exports);
tslib_1.__exportStar(require("./getMediaDimensions"), exports);
tslib_1.__exportStar(require("./imageTensorToCanvas"), exports);
tslib_1.__exportStar(require("./imageToSquare"), exports);
tslib_1.__exportStar(require("./isMediaElement"), exports);
tslib_1.__exportStar(require("./isMediaLoaded"), exports);
tslib_1.__exportStar(require("./loadWeightMap"), exports);
tslib_1.__exportStar(require("./matchDimensions"), exports);
tslib_1.__exportStar(require("./NetInput"), exports);
tslib_1.__exportStar(require("./resolveInput"), exports);
tslib_1.__exportStar(require("./toNetInput"), exports);
tslib_1.__exportStar(require("./types"), exports);
export * from './awaitMediaLoaded';
export * from './bufferToImage';
export * from './createCanvas';
export * from './extractFaces';
export * from './extractFaceTensors';
export * from './fetchImage';
export * from './fetchJson';
export * from './fetchNetWeights';
export * from './fetchOrThrow';
export * from './getContext2dOrThrow';
export * from './getMediaDimensions';
export * from './imageTensorToCanvas';
export * from './imageToSquare';
export * from './isMediaElement';
export * from './isMediaLoaded';
export * from './loadWeightMap';
export * from './matchDimensions';
export * from './NetInput';
export * from './resolveInput';
export * from './toNetInput';
export * from './types';
//# sourceMappingURL=index.js.map

2
build/dom/index.js.map
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@ -1 +1 @@
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10
build/dom/isMediaElement.js
View File

@ -1,12 +1,8 @@
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.isMediaElement = void 0;
const env_1 = require("../env");
function isMediaElement(input) {
const { Image, Canvas, Video } = env_1.env.getEnv();
import { env } from '../env';
export function isMediaElement(input) {
const { Image, Canvas, Video } = env.getEnv();
return input instanceof Image
|| input instanceof Canvas
|| input instanceof Video;
}
exports.isMediaElement = isMediaElement;
//# sourceMappingURL=isMediaElement.js.map

2
build/dom/isMediaElement.js.map
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