Commit 0b1b816d by vincent

check in latest build

parent eb4684bc
......@@ -10,7 +10,10 @@ export declare class Rect implements IRect {
width: number;
height: number;
constructor(x: number, y: number, width: number, height: number);
readonly right: number;
readonly bottom: number;
toSquare(): Rect;
pad(padX: number, padY: number): Rect;
floor(): Rect;
clipAtImageBorders(imgWidth: number, imgHeight: number): Rect;
}
......@@ -7,6 +7,20 @@ var Rect = /** @class */ (function () {
this.width = width;
this.height = height;
}
Object.defineProperty(Rect.prototype, "right", {
get: function () {
return this.x + this.width;
},
enumerable: true,
configurable: true
});
Object.defineProperty(Rect.prototype, "bottom", {
get: function () {
return this.y + this.height;
},
enumerable: true,
configurable: true
});
Rect.prototype.toSquare = function () {
var _a = this, x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var diff = Math.abs(width - height);
......@@ -27,6 +41,16 @@ var Rect = /** @class */ (function () {
Rect.prototype.floor = function () {
return new Rect(Math.floor(this.x), Math.floor(this.y), Math.floor(this.width), Math.floor(this.height));
};
Rect.prototype.clipAtImageBorders = function (imgWidth, imgHeight) {
var _a = this, x = _a.x, y = _a.y, right = _a.right, bottom = _a.bottom;
var clippedX = Math.max(x, 0);
var clippedY = Math.max(y, 0);
var newWidth = right - clippedX;
var newHeight = bottom - clippedY;
var clippedWidth = Math.min(newWidth, imgWidth - clippedX);
var clippedHeight = Math.min(newHeight, imgHeight - clippedY);
return (new Rect(clippedX, clippedY, clippedWidth, clippedHeight)).floor();
};
return Rect;
}());
exports.Rect = Rect;
......
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\ No newline at end of file
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\ No newline at end of file
import { BoundingBox } from '../BoundingBox';
export declare function iou(box1: BoundingBox, box2: BoundingBox, isIOU?: boolean): number;
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
function iou(box1, box2, isIOU) {
if (isIOU === void 0) { isIOU = true; }
var width = Math.max(0.0, Math.min(box1.right, box2.right) - Math.max(box1.left, box2.left) + 1);
var height = Math.max(0.0, Math.min(box1.bottom, box2.bottom) - Math.max(box1.top, box2.top) + 1);
var interSection = width * height;
return isIOU
? interSection / (box1.area + box2.area - interSection)
: interSection / Math.min(box1.area, box2.area);
}
exports.iou = iou;
//# sourceMappingURL=iou.js.map
\ No newline at end of file
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\ No newline at end of file
......@@ -16,11 +16,13 @@ function getModelUris(uri, defaultModelName) {
manifestUri: "/" + defaultManifestFilename
};
}
var protocol = uri.startsWith('http://') ? 'http://' : uri.startsWith('https://') ? 'https://' : '';
uri = uri.replace(protocol, '');
var parts = uri.split('/').filter(function (s) { return s; });
var manifestFile = uri.endsWith('.json')
? parts[parts.length - 1]
: defaultManifestFilename;
var modelBaseUri = (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/');
var modelBaseUri = protocol + (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/');
modelBaseUri = uri.startsWith('/') ? "/" + modelBaseUri : modelBaseUri;
return {
modelBaseUri: modelBaseUri,
......
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\ No newline at end of file
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import * as tf from '@tensorflow/tfjs-core';
export declare function normalize(x: tf.Tensor4D, meanRgb: number[]): tf.Tensor4D;
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
var tf = require("@tensorflow/tfjs-core");
function normalize(x, meanRgb) {
return tf.tidy(function () {
var r = meanRgb[0], g = meanRgb[1], b = meanRgb[2];
var avg_r = tf.fill(x.shape.slice(0, 3).concat([1]), r);
var avg_g = tf.fill(x.shape.slice(0, 3).concat([1]), g);
var avg_b = tf.fill(x.shape.slice(0, 3).concat([1]), b);
var avg_rgb = tf.concat([avg_r, avg_g, avg_b], 3);
return tf.sub(x, avg_rgb);
});
}
exports.normalize = normalize;
//# sourceMappingURL=normalize.js.map
\ No newline at end of file
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......@@ -32,8 +32,9 @@ function extractFaceTensors(input, detections) {
var imgTensor = netInput.inputs[0].expandDims().toFloat();
var _a = imgTensor.shape.slice(1), imgHeight = _a[0], imgWidth = _a[1], numChannels = _a[2];
var boxes = detections.map(function (det) { return det instanceof FaceDetection_1.FaceDetection
? det.forSize(imgWidth, imgHeight).getBox().floor()
: det; });
? det.forSize(imgWidth, imgHeight).getBox()
: 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.slice(imgTensor, [0, y, x, 0], [1, height, width, numChannels]);
......
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\ No newline at end of file
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\ No newline at end of file
......@@ -39,7 +39,8 @@ function extractFaces(input, detections) {
ctx = utils_1.getContext2dOrThrow(canvas);
boxes = detections.map(function (det) { return det instanceof FaceDetection_1.FaceDetection
? det.forSize(canvas.width, canvas.height).getBox().floor()
: det; });
: det; })
.map(function (box) { return box.clipAtImageBorders(canvas.width, canvas.height); });
return [2 /*return*/, boxes.map(function (_a) {
var x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var faceImg = utils_1.createCanvas({ width: width, height: height });
......
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\ No newline at end of file
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\ No newline at end of file
import { BoundingBox } from './BoundingBox';
export declare function iou(box1: BoundingBox, box2: BoundingBox, isIOU?: boolean): number;
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
function iou(box1, box2, isIOU) {
if (isIOU === void 0) { isIOU = true; }
var width = Math.max(0.0, Math.min(box1.right, box2.right) - Math.max(box1.left, box2.left) + 1);
var height = Math.max(0.0, Math.min(box1.bottom, box2.bottom) - Math.max(box1.top, box2.top) + 1);
var interSection = width * height;
return isIOU
? interSection / (box1.area + box2.area - interSection)
: interSection / Math.min(box1.area, box2.area);
}
exports.iou = iou;
//# sourceMappingURL=iou.js.map
\ No newline at end of file
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\ No newline at end of file
import * as tf from '@tensorflow/tfjs-core';
export declare function normalize(x: tf.Tensor4D): tf.Tensor4D;
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
var tf = require("@tensorflow/tfjs-core");
function normalize(x) {
return tf.tidy(function () {
var avg_r = tf.fill(x.shape.slice(0, 3).concat([1]), 117.001);
var avg_g = tf.fill(x.shape.slice(0, 3).concat([1]), 114.697);
var avg_b = tf.fill(x.shape.slice(0, 3).concat([1]), 97.404);
var avg_rgb = tf.concat([avg_r, avg_g, avg_b], 3);
return tf.sub(x, avg_rgb);
});
}
exports.normalize = normalize;
//# sourceMappingURL=normalize.js.map
\ No newline at end of file
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\ No newline at end of file
......@@ -242,6 +242,20 @@
this.width = width;
this.height = height;
}
Object.defineProperty(Rect.prototype, "right", {
get: function () {
return this.x + this.width;
},
enumerable: true,
configurable: true
});
Object.defineProperty(Rect.prototype, "bottom", {
get: function () {
return this.y + this.height;
},
enumerable: true,
configurable: true
});
Rect.prototype.toSquare = function () {
var _a = this, x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var diff = Math.abs(width - height);
......@@ -262,6 +276,16 @@
Rect.prototype.floor = function () {
return new Rect(Math.floor(this.x), Math.floor(this.y), Math.floor(this.width), Math.floor(this.height));
};
Rect.prototype.clipAtImageBorders = function (imgWidth, imgHeight) {
var _a = this, x = _a.x, y = _a.y, right = _a.right, bottom = _a.bottom;
var clippedX = Math.max(x, 0);
var clippedY = Math.max(y, 0);
var newWidth = right - clippedX;
var newHeight = bottom - clippedY;
var clippedWidth = Math.min(newWidth, imgWidth - clippedX);
var clippedHeight = Math.min(newHeight, imgHeight - clippedY);
return (new Rect(clippedX, clippedY, clippedWidth, clippedHeight)).floor();
};
return Rect;
}());
......@@ -1178,11 +1202,13 @@
manifestUri: "/" + defaultManifestFilename
};
}
var protocol = uri.startsWith('http://') ? 'http://' : uri.startsWith('https://') ? 'https://' : '';
uri = uri.replace(protocol, '');
var parts = uri.split('/').filter(function (s) { return s; });
var manifestFile = uri.endsWith('.json')
? parts[parts.length - 1]
: defaultManifestFilename;
var modelBaseUri = (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/');
var modelBaseUri = protocol + (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/');
modelBaseUri = uri.startsWith('/') ? "/" + modelBaseUri : modelBaseUri;
return {
modelBaseUri: modelBaseUri,
......@@ -1514,7 +1540,8 @@
ctx = getContext2dOrThrow(canvas);
boxes = detections.map(function (det) { return det instanceof FaceDetection
? det.forSize(canvas.width, canvas.height).getBox().floor()
: det; });
: det; })
.map(function (box) { return box.clipAtImageBorders(canvas.width, canvas.height); });
return [2 /*return*/, boxes.map(function (_a) {
var x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var faceImg = createCanvas({ width: width, height: height });
......@@ -1555,8 +1582,9 @@
var imgTensor = netInput.inputs[0].expandDims().toFloat();
var _a = imgTensor.shape.slice(1), imgHeight = _a[0], imgWidth = _a[1], numChannels = _a[2];
var boxes = detections.map(function (det) { return det instanceof FaceDetection
? det.forSize(imgWidth, imgHeight).getBox().floor()
: det; });
? det.forSize(imgWidth, imgHeight).getBox()
: 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 slice(imgTensor, [0, y, x, 0], [1, height, width, numChannels]);
......
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