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face
Commit 61b702a6 by vincent
Options

use fetch instead of axios

parent b94260e4
Showing with 34 additions and 76 deletions
dist/face-api.js
......@@ -16071,6 +16071,9 @@
};
FaceDetectionNet.prototype.forwardTensor = function (imgTensor) {
var _this = this;
if (!this._params) {
throw new Error('FaceDetectionNet - load model before inference');
}
return tidy(function () {
var resized = resizeLayer(imgTensor);
var features = mobileNetV1(resized, _this._params.mobilenetv1_params);
......
dist/face-api.min.js
This source diff could not be displayed because it is too large. You can view the blob instead.
dist/faceDetectionNet/FaceDetectionNet.js
......@@ -41,6 +41,9 @@ var FaceDetectionNet = /** @class */ (function () {
};
FaceDetectionNet.prototype.forwardTensor = function (imgTensor) {
var _this = this;
if (!this._params) {
throw new Error('FaceDetectionNet - load model before inference');
}
return tf.tidy(function () {
var resized = resizeLayer(imgTensor);
var features = mobileNetV1(resized, _this._params.mobilenetv1_params);
......
dist/faceDetectionNet/FaceDetectionNet.js.map
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dist/faceLandmarkNet/FaceLandmarkNet.js.map
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\ No newline at end of file
examples/package-lock.json
......@@ -16,15 +16,6 @@
"resolved": "https://registry.npmjs.org/array-flatten/-/array-flatten-1.1.1.tgz",
"integrity": "sha1-ml9pkFGx5wczKPKgCJaLZOopVdI="
},
"axios": {
"version": "0.18.0",
"resolved": "https://registry.npmjs.org/axios/-/axios-0.18.0.tgz",
"integrity": "sha1-MtU+SFHv3AoRmTts0AB4nXDAUQI=",
"requires": {
"follow-redirects": "1.4.1",
"is-buffer": "1.1.6"
}
},
"body-parser": {
"version": "1.18.2",
"resolved": "https://registry.npmjs.org/body-parser/-/body-parser-1.18.2.tgz",
......@@ -156,24 +147,6 @@
"unpipe": "1.0.0"
}
},
"follow-redirects": {
"version": "1.4.1",
"resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.4.1.tgz",
"integrity": "sha512-uxYePVPogtya1ktGnAAXOacnbIuRMB4dkvqeNz2qTtTQsuzSfbDolV+wMMKxAmCx0bLgAKLbBOkjItMbbkR1vg==",
"requires": {
"debug": "3.1.0"
},
"dependencies": {
"debug": {
"version": "3.1.0",
"resolved": "https://registry.npmjs.org/debug/-/debug-3.1.0.tgz",
"integrity": "sha512-OX8XqP7/1a9cqkxYw2yXss15f26NKWBpDXQd0/uK/KPqdQhxbPa994hnzjcE2VqQpDslf55723cKPUOGSmMY3g==",
"requires": {
"ms": "2.0.0"
}
}
}
},
"forwarded": {
"version": "0.1.2",
"resolved": "https://registry.npmjs.org/forwarded/-/forwarded-0.1.2.tgz",
......@@ -210,11 +183,6 @@
"resolved": "https://registry.npmjs.org/ipaddr.js/-/ipaddr.js-1.6.0.tgz",
"integrity": "sha1-4/o1e3c9phnybpXwSdBVxyeW+Gs="
},
"is-buffer": {
"version": "1.1.6",
"resolved": "https://registry.npmjs.org/is-buffer/-/is-buffer-1.1.6.tgz",
"integrity": "sha512-NcdALwpXkTm5Zvvbk7owOUSvVvBKDgKP5/ewfXEznmQFfs4ZRmanOeKBTjRVjka3QFoN6XJ+9F3USqfHqTaU5w=="
},
"media-typer": {
"version": "0.3.0",
"resolved": "https://registry.npmjs.org/media-typer/-/media-typer-0.3.0.tgz",
......
examples/package.json
......@@ -5,7 +5,6 @@
"author": "justadudewhohacks",
"license": "MIT",
"dependencies": {
"axios": "^0.18.0",
"express": "^4.16.3"
}
}
examples/public/commons.js
......@@ -9,12 +9,12 @@ function getFaceImageUri(className, idx) {
}
async function fetchImage(uri) {
return (await axios.get(uri, { responseType: 'blob' })).data
return (await fetch(uri)).blob()
}
async function initFaceRecognitionNet() {
const res = await axios.get('uncompressed/face_recognition_model.weights', { responseType: 'arraybuffer' })
const weights = new Float32Array(res.data)
const res = await fetch('uncompressed/face_recognition_model.weights')
const weights = new Float32Array(await res.arrayBuffer())
return faceapi.faceRecognitionNet(weights)
}
......
examples/views/detectAndDrawFaces.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/detectAndDrawLandmarks.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/detectAndRecognizeFaces.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/faceAlignment.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/faceDetection.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/faceDetectionVideo.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/faceLandmarks.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/faceRecognition.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
examples/views/faceSimilarity.html
......@@ -2,7 +2,6 @@
<html>
<head>
<script src="face-api.js"></script>
<script src="axios.min.js"></script>
<script src="commons.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
......
package.json
......@@ -23,10 +23,8 @@
"@tensorflow/tfjs-core": "^0.11.0"
},
"devDependencies": {
"@types/axios": "^0.14.0",
"@types/jasmine": "^2.8.8",
"@types/node": "^10.1.1",
"axios": "^0.18.0",
"jasmine-core": "^3.1.0",
"karma": "^2.0.3",
"karma-chrome-launcher": "^2.2.0",
......
src/faceDetectionNet/FaceDetectionNet.ts
......@@ -36,6 +36,10 @@ export class FaceDetectionNet {
}
private forwardTensor(imgTensor: tf.Tensor4D) {
if (!this._params) {
throw new Error('FaceDetectionNet - load model before inference')
}
return tf.tidy(() => {
const resized = resizeLayer(imgTensor) as tf.Tensor4D
......
src/faceLandmarkNet/FaceLandmarkNet.ts
......@@ -40,13 +40,11 @@ export class FaceLandmarkNet {
this._params = extractParams(weights)
}
public async detectLandmarks(input: tf.Tensor | NetInput | TNetInput) {
if (!this._params) {
throw new Error('FaceLandmarkNet - load model before inference')
}
let imageDimensions: Dimensions | undefined
const outTensor = tf.tidy(() => {
......
test/e2e/faceDetectionNet.test.ts
import axios from 'axios';
import * as faceapi from '../../src';
import { FaceDetection } from '../../src/faceDetectionNet/FaceDetection';
import { IRect } from '../../src/Rect';
......@@ -15,18 +13,18 @@ function expectFaceDetectionEquals(result: FaceDetection, score: number, expecte
describe('faceDetectionNet', () => {
let faceDetectionNet: any, imgEl: HTMLImageElement
let faceDetectionNet: faceapi.FaceDetectionNet, imgEl: HTMLImageElement
beforeAll(async () => {
const res = await axios.get('base/weights/face_detection_model.weights', { responseType: 'arraybuffer' })
const weights = new Float32Array(res.data)
const res = await fetch('base/weights/uncompressed/face_detection_model.weights')
const weights = new Float32Array(await res.arrayBuffer())
faceDetectionNet = faceapi.faceDetectionNet(weights)
const img = await axios.get('base/test/images/faces.jpg', { responseType: 'blob' })
imgEl = await faceapi.bufferToImage(img.data)
const img = await (await fetch('base/test/images/faces.jpg')).blob()
imgEl = await faceapi.bufferToImage(img)
})
it('scores > 0.9', async () => {
it('scores > 0.8', async () => {
const { width, height } = imgEl
const result = await faceDetectionNet.locateFaces(imgEl) as FaceDetection[]
......
test/e2e/faceLandmarkNet.test.ts
import axios from 'axios';
import * as faceapi from '../../src';
import { FaceLandmarks } from '../../src/faceLandmarkNet/FaceLandmarks';
import { Point } from '../../src/Point';
describe('faceLandmarkNet', () => {
let faceLandmarkNet: any, imgEl: HTMLImageElement, faceLandmarkPositions: Point[]
let faceLandmarkNet: faceapi.FaceLandmarkNet, imgEl: HTMLImageElement, faceLandmarkPositions: Point[]
beforeAll(async () => {
const res = await axios.get('base/weights/uncompressed/face_landmark_68_model.weights', { responseType: 'arraybuffer' })
const weights = new Float32Array(res.data)
const res = await fetch('base/weights/uncompressed/face_landmark_68_model.weights')
const weights = new Float32Array(await res.arrayBuffer())
faceLandmarkNet = faceapi.faceLandmarkNet(weights)
const img = await axios.get('base/test/images/face.png', { responseType: 'blob' })
imgEl = await faceapi.bufferToImage(img.data)
faceLandmarkPositions = (await axios.get('base/test/data/faceLandmarkPositions.json')).data
const img = await (await fetch('base/test/images/face.png')).blob()
imgEl = await faceapi.bufferToImage(img)
faceLandmarkPositions = await (await fetch('base/test/data/faceLandmarkPositions.json')).json()
})
it('computes face descriptor', async () => {
......
test/e2e/faceRecognitionNet.test.ts
import axios from 'axios';
import * as faceapi from '../../src';
describe('faceRecognitionNet', () => {
......@@ -7,13 +5,13 @@ describe('faceRecognitionNet', () => {
let faceRecognitionNet: any, imgEl: HTMLImageElement, faceDescriptor: number[]
beforeAll(async () => {
const res = await axios.get('base/weights/uncompressed/face_recognition_model.weights', { responseType: 'arraybuffer' })
const weights = new Float32Array(res.data)
const res = await fetch('base/weights/uncompressed/face_recognition_model.weights')
const weights = new Float32Array(await res.arrayBuffer())
faceRecognitionNet = faceapi.faceRecognitionNet(weights)
const img = await axios.get('base/test/images/face.png', { responseType: 'blob' })
imgEl = await faceapi.bufferToImage(img.data)
faceDescriptor = (await axios.get('base/test/data/faceDescriptor.json')).data
const img = await (await fetch('base/test/images/face.png')).blob()
imgEl = await faceapi.bufferToImage(img)
faceDescriptor = await (await fetch('base/test/data/faceDescriptor.json')).json()
})
it('computes face descriptor', async () => {
......
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