added faceDetectionNet end to end test

karma.conf.js

@@ -3,7 +3,21 @@ module.exports = function(config) {
     frameworks: ['jasmine', 'karma-typescript'],
     files: [
       'src/**/*.ts',
-      'test/**/*.ts'
+      'test/**/*.ts',
+      {
+        pattern: 'test/images/*.jpg',
+        watched: false,
+        included: false,
+        served: true,
+        nocache: false
+      },
+      {
+        pattern: 'weights/*.weights',
+        watched: false,
+        included: false,
+        served: true,
+        nocache: false
+      }
     ],
     preprocessors: {
       '**/*.ts': ['karma-typescript']

package-lock.json

@@ -12,6 +12,15 @@
         "seedrandom": "2.4.3"
       }
     },
+    "@types/axios": {
+      "version": "0.14.0",
+      "resolved": "https://registry.npmjs.org/@types/axios/-/axios-0.14.0.tgz",
+      "integrity": "sha1-7CMA++fX3d1+udOr+HmZlkyvzkY=",
+      "dev": true,
+      "requires": {
+        "axios": "0.18.0"
+      }
+    },
     "@types/estree": {
       "version": "0.0.39",
       "resolved": "https://registry.npmjs.org/@types/estree/-/estree-0.0.39.tgz",
@@ -368,25 +377,13 @@
       "optional": true
     },
     "axios": {
-      "version": "0.15.3",
-      "resolved": "https://registry.npmjs.org/axios/-/axios-0.15.3.tgz",
-      "integrity": "sha1-LJ1jiy4ZGgjqHWzJiOrda6W9wFM=",
+      "version": "0.18.0",
+      "resolved": "https://registry.npmjs.org/axios/-/axios-0.18.0.tgz",
+      "integrity": "sha1-MtU+SFHv3AoRmTts0AB4nXDAUQI=",
       "dev": true,
-      "optional": true,
       "requires": {
-        "follow-redirects": "1.0.0"
-      },
-      "dependencies": {
-        "follow-redirects": {
-          "version": "1.0.0",
-          "resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.0.0.tgz",
-          "integrity": "sha1-jjQpjL0uF28lTv/sdaHHjMhJ/Tc=",
-          "dev": true,
-          "optional": true,
-          "requires": {
-            "debug": "2.6.9"
-          }
-        }
+        "follow-redirects": "1.5.0",
+        "is-buffer": "1.1.6"
       }
     },
     "backo2": {
@@ -3309,6 +3306,16 @@
         "streamroller": "0.7.0"
       },
       "dependencies": {
+        "axios": {
+          "version": "0.15.3",
+          "resolved": "https://registry.npmjs.org/axios/-/axios-0.15.3.tgz",
+          "integrity": "sha1-LJ1jiy4ZGgjqHWzJiOrda6W9wFM=",
+          "dev": true,
+          "optional": true,
+          "requires": {
+            "follow-redirects": "1.0.0"
+          }
+        },
         "debug": {
           "version": "3.1.0",
           "resolved": "https://registry.npmjs.org/debug/-/debug-3.1.0.tgz",
@@ -3317,6 +3324,28 @@
           "requires": {
             "ms": "2.0.0"
           }
+        },
+        "follow-redirects": {
+          "version": "1.0.0",
+          "resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.0.0.tgz",
+          "integrity": "sha1-jjQpjL0uF28lTv/sdaHHjMhJ/Tc=",
+          "dev": true,
+          "optional": true,
+          "requires": {
+            "debug": "2.6.9"
+          },
+          "dependencies": {
+            "debug": {
+              "version": "2.6.9",
+              "resolved": "https://registry.npmjs.org/debug/-/debug-2.6.9.tgz",
+              "integrity": "sha512-bC7ElrdJaJnPbAP+1EotYvqZsb3ecl5wi6Bfi6BJTUcNowp6cvspg0jXznRTKDjm/E7AdgFBVeAPVMNcKGsHMA==",
+              "dev": true,
+              "optional": true,
+              "requires": {
+                "ms": "2.0.0"
+              }
+            }
+          }
         }
       }
     },

package.json

@@ -23,8 +23,10 @@
     "@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/Rect.ts

-export class Rect {
+export interface IRect {
+  x: number
+  y: number
+  width: number
+  height: number
+}
+
+export class Rect implements IRect {
   public x: number
   public y: number
   public width: number

src/faceDetectionNet/index.ts

@@ -38,7 +38,7 @@ export function faceDetectionNet(weights: Float32Array) {
   }
 
   async function locateFaces(
-    input: tf.Tensor | NetInput,
+    input: tf.Tensor | NetInput | TNetInput,
     minConfidence: number = 0.8,
     maxResults: number = 100,
   ): Promise<FaceDetection[]> {

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';
+
+function expectFaceDetectionEquals(result: FaceDetection, score: number, expectedBox: IRect) {
+  const { x, y, width, height } = result.getBox()
+  expect(result.getScore()).toBeCloseTo(score, 2)
+  expect(Math.floor(x)).toEqual(expectedBox.x)
+  expect(Math.floor(y)).toEqual(expectedBox.y)
+  expect(Math.floor(width)).toEqual(expectedBox.width)
+  expect(Math.floor(height)).toEqual(expectedBox.height)
+}
+
+describe('faceDetectionNet', () => {
+
+  let faceDetectionNet: any, imgEl: HTMLImageElement
+
+  beforeAll(async () => {
+    const res = await axios.get('base/weights/face_detection_model.weights', { responseType: 'arraybuffer' })
+    const weights = new Float32Array(res.data)
+    faceDetectionNet = faceapi.faceDetectionNet(weights)
+
+    const img = await axios.get('base/test/images/faces.jpg', { responseType: 'blob' })
+    imgEl = await faceapi.bufferToImage(img.data)
+  })
+
+  it('scores > 0.9', async () => {
+    const { width, height } = imgEl
+
+    const result = await faceDetectionNet.locateFaces(imgEl) as FaceDetection[]
+    expect(result.length).toEqual(3)
+
+    result.forEach(res => {
+      expect(res.getImageWidth()).toEqual(width)
+      expect(res.getImageHeight()).toEqual(height)
+    })
+    const [d0, d1, d2] = result
+    expectFaceDetectionEquals(d0, 0.98, { x: 48, y: 253, width: 104, height: 129 })
+    expectFaceDetectionEquals(d1, 0.89, { x: 260, y: 227, width: 76, height: 117 })
+    expectFaceDetectionEquals(d2, 0.82, { x: 466, y: 165, width: 88, height: 130 })
+  })
+
+  it('scores > 0.5', async () => {
+    const { width, height } = imgEl
+
+    const result = await faceDetectionNet.locateFaces(imgEl, 0.5) as FaceDetection[]
+    expect(result.length).toEqual(6)
+
+    result.forEach(res => {
+      expect(res.getImageWidth()).toEqual(width)
+      expect(res.getImageHeight()).toEqual(height)
+    })
+    const [d0, d1, d2, d3, d4, d5] = result
+    expectFaceDetectionEquals(d0, 0.98, { x: 48, y: 253, width: 104, height: 129 })
+    expectFaceDetectionEquals(d1, 0.89, { x: 260, y: 227, width: 76, height: 117 })
+    expectFaceDetectionEquals(d2, 0.82, { x: 466, y: 165, width: 88, height: 130 })
+    expectFaceDetectionEquals(d3, 0.75, { x: 234, y: 36, width: 84, height: 119 })
+    expectFaceDetectionEquals(d4, 0.58, { x: 577, y: 65, width: 84, height: 105 })
+    expectFaceDetectionEquals(d5, 0.55, { x: 84, y: 14, width: 79, height: 132 })
+  })
+})
\ No newline at end of file