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face
Commit 3f4aa56d by vincent
Options

merge with master

parents 896371af 661f228b
Showing with 359 additions and 21 deletions
.npmignore
...@@ -2,7 +2,8 @@ node_modules ...@@ -2,7 +2,8 @@ node_modules
.rpt2_cache .rpt2_cache
examples examples
test
proto proto
weights weights
weights_uncompressed
test
tools tools
\ No newline at end of file
build/Rect.d.ts
...@@ -10,7 +10,10 @@ export declare class Rect implements IRect { ...@@ -10,7 +10,10 @@ export declare class Rect implements IRect {
width: number; width: number;
height: number; height: number;
constructor(x: number, y: number, width: number, height: number); constructor(x: number, y: number, width: number, height: number);
readonly right: number;
readonly bottom: number;
toSquare(): Rect; toSquare(): Rect;
pad(padX: number, padY: number): Rect; pad(padX: number, padY: number): Rect;
floor(): Rect; floor(): Rect;
clipAtImageBorders(imgWidth: number, imgHeight: number): Rect;
} }
build/Rect.js
...@@ -7,6 +7,20 @@ var Rect = /** @class */ (function () { ...@@ -7,6 +7,20 @@ var Rect = /** @class */ (function () {
this.width = width; this.width = width;
this.height = height; 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 () { Rect.prototype.toSquare = function () {
var _a = this, x = _a.x, y = _a.y, width = _a.width, height = _a.height; var _a = this, x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var diff = Math.abs(width - height); var diff = Math.abs(width - height);
...@@ -27,6 +41,16 @@ var Rect = /** @class */ (function () { ...@@ -27,6 +41,16 @@ var Rect = /** @class */ (function () {
Rect.prototype.floor = function () { Rect.prototype.floor = function () {
return new Rect(Math.floor(this.x), Math.floor(this.y), Math.floor(this.width), Math.floor(this.height)); 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; return Rect;
}()); }());
exports.Rect = Rect; exports.Rect = Rect;
......
build/Rect.js.map
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\ No newline at end of file \ No newline at end of file
build/commons/iou.d.ts 0 → 100644
import { BoundingBox } from '../BoundingBox';
export declare function iou(box1: BoundingBox, box2: BoundingBox, isIOU?: boolean): number;
build/commons/iou.js 0 → 100644
"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
build/commons/iou.js.map 0 → 100644
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\ No newline at end of file
build/commons/loadWeightMap.js
...@@ -16,11 +16,13 @@ function getModelUris(uri, defaultModelName) { ...@@ -16,11 +16,13 @@ function getModelUris(uri, defaultModelName) {
manifestUri: "/" + defaultManifestFilename 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 parts = uri.split('/').filter(function (s) { return s; });
var manifestFile = uri.endsWith('.json') var manifestFile = uri.endsWith('.json')
? parts[parts.length - 1] ? parts[parts.length - 1]
: defaultManifestFilename; : 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; modelBaseUri = uri.startsWith('/') ? "/" + modelBaseUri : modelBaseUri;
return { return {
modelBaseUri: modelBaseUri, modelBaseUri: modelBaseUri,
......
build/commons/loadWeightMap.js.map
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\ No newline at end of file \ No newline at end of file
build/commons/normalize.d.ts 0 → 100644
import * as tf from '@tensorflow/tfjs-core';
export declare function normalize(x: tf.Tensor4D, meanRgb: number[]): tf.Tensor4D;
build/commons/normalize.js 0 → 100644
"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
build/commons/normalize.js.map 0 → 100644
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\ No newline at end of file
build/extractFaceTensors.js
...@@ -32,8 +32,9 @@ function extractFaceTensors(input, detections) { ...@@ -32,8 +32,9 @@ function extractFaceTensors(input, detections) {
var imgTensor = netInput.inputs[0].expandDims().toFloat(); var imgTensor = netInput.inputs[0].expandDims().toFloat();
var _a = imgTensor.shape.slice(1), imgHeight = _a[0], imgWidth = _a[1], numChannels = _a[2]; 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 var boxes = detections.map(function (det) { return det instanceof FaceDetection_1.FaceDetection
? det.forSize(imgWidth, imgHeight).getBox().floor() ? det.forSize(imgWidth, imgHeight).getBox()
: det; }); : det; })
.map(function (box) { return box.clipAtImageBorders(imgWidth, imgHeight); });
var faceTensors = boxes.map(function (_a) { var faceTensors = boxes.map(function (_a) {
var x = _a.x, y = _a.y, width = _a.width, height = _a.height; 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]); return tf.slice(imgTensor, [0, y, x, 0], [1, height, width, numChannels]);
......
build/extractFaceTensors.js.map
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\ No newline at end of file \ No newline at end of file
build/extractFaces.js
...@@ -39,7 +39,8 @@ function extractFaces(input, detections) { ...@@ -39,7 +39,8 @@ function extractFaces(input, detections) {
ctx = utils_1.getContext2dOrThrow(canvas); ctx = utils_1.getContext2dOrThrow(canvas);
boxes = detections.map(function (det) { return det instanceof FaceDetection_1.FaceDetection boxes = detections.map(function (det) { return det instanceof FaceDetection_1.FaceDetection
? det.forSize(canvas.width, canvas.height).getBox().floor() ? 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) { return [2 /*return*/, boxes.map(function (_a) {
var x = _a.x, y = _a.y, width = _a.width, height = _a.height; var x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var faceImg = utils_1.createCanvas({ width: width, height: height }); var faceImg = utils_1.createCanvas({ width: width, height: height });
......
build/extractFaces.js.map
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\ No newline at end of file \ No newline at end of file
build/iou.d.ts 0 → 100644
import { BoundingBox } from './BoundingBox';
export declare function iou(box1: BoundingBox, box2: BoundingBox, isIOU?: boolean): number;
build/iou.js 0 → 100644
"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
build/iou.js.map 0 → 100644
{"version":3,"file":"iou.js","sourceRoot":"","sources":["../src/iou.ts"],"names":[],"mappings":";;AAEA,aAAoB,IAAiB,EAAE,IAAiB,EAAE,KAAqB;IAArB,sBAAA,EAAA,YAAqB;IAC7E,IAAM,KAAK,GAAG,IAAI,CAAC,GAAG,CAAC,GAAG,EAAE,IAAI,CAAC,GAAG,CAAC,IAAI,CAAC,KAAK,EAAE,IAAI,CAAC,KAAK,CAAC,GAAG,IAAI,CAAC,GAAG,CAAC,IAAI,CAAC,IAAI,EAAE,IAAI,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC,CAAA;IAClG,IAAM,MAAM,GAAG,IAAI,CAAC,GAAG,CAAC,GAAG,EAAE,IAAI,CAAC,GAAG,CAAC,IAAI,CAAC,MAAM,EAAE,IAAI,CAAC,MAAM,CAAC,GAAG,IAAI,CAAC,GAAG,CAAC,IAAI,CAAC,GAAG,EAAE,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC,CAAA;IACnG,IAAM,YAAY,GAAG,KAAK,GAAG,MAAM,CAAA;IAEnC,OAAO,KAAK;QACV,CAAC,CAAC,YAAY,GAAG,CAAC,IAAI,CAAC,IAAI,GAAG,IAAI,CAAC,IAAI,GAAG,YAAY,CAAC;QACvD,CAAC,CAAC,YAAY,GAAG,IAAI,CAAC,GAAG,CAAC,IAAI,CAAC,IAAI,EAAE,IAAI,CAAC,IAAI,CAAC,CAAA;AACnD,CAAC;AARD,kBAQC"}
\ No newline at end of file
build/tinyYolov2/normalize.d.ts 0 → 100644
import * as tf from '@tensorflow/tfjs-core';
export declare function normalize(x: tf.Tensor4D): tf.Tensor4D;
build/tinyYolov2/normalize.js 0 → 100644
"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
build/tinyYolov2/normalize.js.map 0 → 100644
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\ No newline at end of file
dist/face-api.js
...@@ -242,6 +242,20 @@ ...@@ -242,6 +242,20 @@
this.width = width; this.width = width;
this.height = height; 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 () { Rect.prototype.toSquare = function () {
var _a = this, x = _a.x, y = _a.y, width = _a.width, height = _a.height; var _a = this, x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var diff = Math.abs(width - height); var diff = Math.abs(width - height);
...@@ -262,6 +276,16 @@ ...@@ -262,6 +276,16 @@
Rect.prototype.floor = function () { Rect.prototype.floor = function () {
return new Rect(Math.floor(this.x), Math.floor(this.y), Math.floor(this.width), Math.floor(this.height)); 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; return Rect;
}()); }());
...@@ -1178,11 +1202,13 @@ ...@@ -1178,11 +1202,13 @@
manifestUri: "/" + defaultManifestFilename 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 parts = uri.split('/').filter(function (s) { return s; });
var manifestFile = uri.endsWith('.json') var manifestFile = uri.endsWith('.json')
? parts[parts.length - 1] ? parts[parts.length - 1]
: defaultManifestFilename; : 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; modelBaseUri = uri.startsWith('/') ? "/" + modelBaseUri : modelBaseUri;
return { return {
modelBaseUri: modelBaseUri, modelBaseUri: modelBaseUri,
...@@ -1514,7 +1540,8 @@ ...@@ -1514,7 +1540,8 @@
ctx = getContext2dOrThrow(canvas); ctx = getContext2dOrThrow(canvas);
boxes = detections.map(function (det) { return det instanceof FaceDetection boxes = detections.map(function (det) { return det instanceof FaceDetection
? det.forSize(canvas.width, canvas.height).getBox().floor() ? 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) { return [2 /*return*/, boxes.map(function (_a) {
var x = _a.x, y = _a.y, width = _a.width, height = _a.height; var x = _a.x, y = _a.y, width = _a.width, height = _a.height;
var faceImg = createCanvas({ width: width, height: height }); var faceImg = createCanvas({ width: width, height: height });
...@@ -1555,8 +1582,9 @@ ...@@ -1555,8 +1582,9 @@
var imgTensor = netInput.inputs[0].expandDims().toFloat(); var imgTensor = netInput.inputs[0].expandDims().toFloat();
var _a = imgTensor.shape.slice(1), imgHeight = _a[0], imgWidth = _a[1], numChannels = _a[2]; 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 var boxes = detections.map(function (det) { return det instanceof FaceDetection
? det.forSize(imgWidth, imgHeight).getBox().floor() ? det.forSize(imgWidth, imgHeight).getBox()
: det; }); : det; })
.map(function (box) { return box.clipAtImageBorders(imgWidth, imgHeight); });
var faceTensors = boxes.map(function (_a) { var faceTensors = boxes.map(function (_a) {
var x = _a.x, y = _a.y, width = _a.width, height = _a.height; var x = _a.x, y = _a.y, width = _a.width, height = _a.height;
return slice(imgTensor, [0, y, x, 0], [1, height, width, numChannels]); return slice(imgTensor, [0, y, x, 0], [1, height, width, numChannels]);
......
dist/face-api.js.map
This source diff could not be displayed because it is too large. You can view the blob instead.
dist/face-api.min.js
This source diff could not be displayed because it is too large. You can view the blob instead.
package-lock.json
{ {
"name": "face-api.js", "name": "face-api.js",
"version": "0.10.0", "version": "0.10.1",
"lockfileVersion": 1, "lockfileVersion": 1,
"requires": true, "requires": true,
"dependencies": { "dependencies": {
......
package.json
{ {
"name": "face-api.js", "name": "face-api.js",
"version": "0.10.0", "version": "0.10.1",
"description": "JavaScript API for face detection and face recognition in the browser with tensorflow.js", "description": "JavaScript API for face detection and face recognition in the browser with tensorflow.js",
"main": "./build/index.js", "main": "./build/index.js",
"typings": "./build/index.d.ts", "typings": "./build/index.d.ts",
......
src/Rect.ts
...@@ -19,6 +19,14 @@ export class Rect implements IRect { ...@@ -19,6 +19,14 @@ export class Rect implements IRect {
this.height = height this.height = height
} }
public get right() {
return this.x + this.width
}
public get bottom() {
return this.y + this.height
}
public toSquare(): Rect { public toSquare(): Rect {
let { x, y, width, height } = this let { x, y, width, height } = this
const diff = Math.abs(width - height) const diff = Math.abs(width - height)
...@@ -50,4 +58,17 @@ export class Rect implements IRect { ...@@ -50,4 +58,17 @@ export class Rect implements IRect {
public toBoundingBox(): BoundingBox { public toBoundingBox(): BoundingBox {
return new BoundingBox(this.x, this.y, this.x + this.width, this.y + this.height) return new BoundingBox(this.x, this.y, this.x + this.width, this.y + this.height)
} }
public clipAtImageBorders(imgWidth: number, imgHeight: number): Rect {
const { x, y, right, bottom } = this
const clippedX = Math.max(x, 0)
const clippedY = Math.max(y, 0)
const newWidth = right - clippedX
const newHeight = bottom - clippedY
const clippedWidth = Math.min(newWidth, imgWidth - clippedX)
const clippedHeight = Math.min(newHeight, imgHeight - clippedY)
return (new Rect(clippedX, clippedY, clippedWidth, clippedHeight)).floor()
}
} }
\ No newline at end of file
src/commons/loadWeightMap.ts
...@@ -16,6 +16,8 @@ export function getModelUris(uri: string | undefined, defaultModelName: string) ...@@ -16,6 +16,8 @@ export function getModelUris(uri: string | undefined, defaultModelName: string)
manifestUri: `/${defaultManifestFilename}` manifestUri: `/${defaultManifestFilename}`
} }
} }
const protocol = uri.startsWith('http://') ? 'http://' : uri.startsWith('https://') ? 'https://' : '';
uri = uri.replace(protocol, '');
const parts = uri.split('/').filter(s => s) const parts = uri.split('/').filter(s => s)
...@@ -23,7 +25,7 @@ export function getModelUris(uri: string | undefined, defaultModelName: string) ...@@ -23,7 +25,7 @@ export function getModelUris(uri: string | undefined, defaultModelName: string)
? parts[parts.length - 1] ? parts[parts.length - 1]
: defaultManifestFilename : defaultManifestFilename
let modelBaseUri = (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/') let modelBaseUri = protocol + (uri.endsWith('.json') ? parts.slice(0, parts.length - 1) : parts).join('/')
modelBaseUri = uri.startsWith('/') ? `/${modelBaseUri}` : modelBaseUri modelBaseUri = uri.startsWith('/') ? `/${modelBaseUri}` : modelBaseUri
return { return {
......
src/extractFaceTensors.ts
...@@ -36,9 +36,11 @@ export async function extractFaceTensors( ...@@ -36,9 +36,11 @@ export async function extractFaceTensors(
const boxes = detections.map( const boxes = detections.map(
det => det instanceof FaceDetection det => det instanceof FaceDetection
? det.forSize(imgWidth, imgHeight).getBox().floor() ? det.forSize(imgWidth, imgHeight).getBox()
: det : det
) )
.map(box => box.clipAtImageBorders(imgWidth, imgHeight))
const faceTensors = boxes.map(({ x, y, width, height }) => const faceTensors = boxes.map(({ x, y, width, height }) =>
tf.slice(imgTensor, [0, y, x, 0], [1, height, width, numChannels]) tf.slice(imgTensor, [0, y, x, 0], [1, height, width, numChannels])
) )
......
src/extractFaces.ts
...@@ -42,6 +42,8 @@ export async function extractFaces( ...@@ -42,6 +42,8 @@ export async function extractFaces(
? det.forSize(canvas.width, canvas.height).getBox().floor() ? det.forSize(canvas.width, canvas.height).getBox().floor()
: det : det
) )
.map(box => box.clipAtImageBorders(canvas.width, canvas.height))
return boxes.map(({ x, y, width, height }) => { return boxes.map(({ x, y, width, height }) => {
const faceImg = createCanvas({ width, height }) const faceImg = createCanvas({ width, height })
getContext2dOrThrow(faceImg) getContext2dOrThrow(faceImg)
......
test/tests/commons/loadWeightMap.test.ts
...@@ -59,6 +59,14 @@ describe('loadWeightMap', () => { ...@@ -59,6 +59,14 @@ describe('loadWeightMap', () => {
expect(result.modelBaseUri).toEqual('/path/to/modelfiles') expect(result.modelBaseUri).toEqual('/path/to/modelfiles')
}) })
it('returns correct uris, given external path', () => {
const uri = 'https://example.com/path/to/modelfiles';
const result = getModelUris(uri, FAKE_DEFAULT_MODEL_NAME)
expect(result.manifestUri).toEqual(`${uri}/${FAKE_DEFAULT_MODEL_NAME}-weights_manifest.json`)
expect(result.modelBaseUri).toEqual(uri)
})
}) })
}) })
test/tests/extractFaceTensors.test.ts 0 → 100644
import { extractFaceTensors, Rect } from '../../src';
import { bufferToImage } from '../../src/utils';
describe('extractFaceTensors', () => {
let imgEl: HTMLImageElement
beforeAll(async () => {
const img = await (await fetch('base/test/images/face1.png')).blob()
imgEl = await bufferToImage(img)
})
describe('extracts tensors', () => {
it('single box', async () => {
const rect = new Rect(0, 0, 50, 60)
const tensors = await extractFaceTensors(imgEl, [rect])
expect(tensors.length).toEqual(1)
expect(tensors[0].shape).toEqual([1, 60, 50, 3])
tensors[0].dispose()
})
it('multiple boxes', async () => {
const rects = [
new Rect(0, 0, 50, 60),
new Rect(50, 50, 70, 80),
]
const tensors = await extractFaceTensors(imgEl, rects)
expect(tensors.length).toEqual(2)
expect(tensors[0].shape).toEqual([1, 60, 50, 3])
expect(tensors[1].shape).toEqual([1, 80, 70, 3])
tensors[0].dispose()
tensors[1].dispose()
})
})
describe('box out of image borders', () => {
it('clips upper left corner', async () => {
const rect = new Rect(-10, -10, 110, 110)
const tensors = await extractFaceTensors(imgEl, [rect])
expect(tensors[0].shape).toEqual([1, 100, 100, 3])
tensors[0].dispose()
})
it('clips bottom right corner', async () => {
const rect = new Rect(imgEl.width - 100, imgEl.height - 100, 110, 110)
const tensors = await extractFaceTensors(imgEl, [rect])
expect(tensors[0].shape).toEqual([1, 100, 100, 3])
tensors[0].dispose()
})
it('clips upper left and bottom right corners', async () => {
const rect = new Rect(-10, -10, imgEl.width + 20, imgEl.height + 20)
const tensors = await extractFaceTensors(imgEl, [rect])
expect(tensors[0].shape).toEqual([1, imgEl.height, imgEl.width, 3])
tensors[0].dispose()
})
})
})
test/tests/extractFaces.test.ts 0 → 100644
import { extractFaces, Rect } from '../../src';
import { bufferToImage, createCanvasFromMedia } from '../../src/utils';
describe('extractFaces', () => {
let imgEl: HTMLImageElement, canvasEl: HTMLCanvasElement
beforeAll(async () => {
const img = await (await fetch('base/test/images/face1.png')).blob()
imgEl = await bufferToImage(img)
canvasEl = createCanvasFromMedia(imgEl)
})
describe('extracts canvases', () => {
it('HTMLImageElement, single box', async () => {
const rect = new Rect(0, 0, 50, 60)
const canvases = await extractFaces(imgEl, [rect])
expect(canvases.length).toEqual(1)
expect(canvases[0] instanceof HTMLCanvasElement).toBe(true)
expect(canvases[0].width).toEqual(50)
expect(canvases[0].height).toEqual(60)
})
it('HTMLImageElement, multiple boxes', async () => {
const rects = [
new Rect(0, 0, 50, 60),
new Rect(50, 50, 70, 80),
]
const canvases = await extractFaces(imgEl, rects)
expect(canvases.length).toEqual(2)
expect(canvases[0] instanceof HTMLCanvasElement).toBe(true)
expect(canvases[0].width).toEqual(50)
expect(canvases[0].height).toEqual(60)
expect(canvases[1] instanceof HTMLCanvasElement).toBe(true)
expect(canvases[1].width).toEqual(70)
expect(canvases[1].height).toEqual(80)
})
it('HTMLCanvasElement, single box', async () => {
const rect = new Rect(0, 0, 50, 60)
const canvases = await extractFaces(canvasEl, [rect])
expect(canvases.length).toEqual(1)
expect(canvases[0] instanceof HTMLCanvasElement).toBe(true)
expect(canvases[0].width).toEqual(50)
expect(canvases[0].height).toEqual(60)
})
it('HTMLCanvasElement, multiple boxes', async () => {
const rects = [
new Rect(0, 0, 50, 60),
new Rect(50, 50, 70, 80),
]
const canvases = await extractFaces(canvasEl, rects)
expect(canvases.length).toEqual(2)
expect(canvases[0] instanceof HTMLCanvasElement).toBe(true)
expect(canvases[0].width).toEqual(50)
expect(canvases[0].height).toEqual(60)
expect(canvases[1] instanceof HTMLCanvasElement).toBe(true)
expect(canvases[1].width).toEqual(70)
expect(canvases[1].height).toEqual(80)
})
})
describe('box out of image borders', () => {
it('clips upper left corner', async () => {
const rect = new Rect(-10, -10, 110, 110)
const canvases = await extractFaces(imgEl, [rect])
expect(canvases[0].width).toEqual(100)
expect(canvases[0].height).toEqual(100)
})
it('clips bottom right corner', async () => {
const rect = new Rect(imgEl.width - 100, imgEl.height - 100, 110, 110)
const canvases = await extractFaces(imgEl, [rect])
expect(canvases[0].width).toEqual(100)
expect(canvases[0].height).toEqual(100)
})
it('clips upper left and bottom right corners', async () => {
const rect = new Rect(-10, -10, imgEl.width + 20, imgEl.height + 20)
const canvases = await extractFaces(imgEl, [rect])
expect(canvases[0].width).toEqual(imgEl.width)
expect(canvases[0].height).toEqual(imgEl.height)
})
})
})
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