breaking changes to results.face output properties

src/draw/draw.ts

@@ -174,8 +174,8 @@ export async function face(inCanvas: HTMLCanvasElement, result: Array<Face>, dra
     if (localOptions.drawBoxes) rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], localOptions);
     // silly hack since fillText does not suport new line
     const labels:string[] = [];
-    labels.push(`face confidence: ${Math.trunc(100 * f.confidence)}%`);
+    labels.push(`face confidence: ${Math.trunc(100 * f.score)}%`);
-    if (f.genderConfidence) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderConfidence)}% confident`);
+    if (f.genderScore) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderScore)}% confident`);
     // if (f.genderConfidence) labels.push(f.gender);
     if (f.age) labels.push(`age: ${f.age || ''}`);
     if (f.iris) labels.push(`distance: ${f.iris}`);

src/face.ts

@@ -4,6 +4,7 @@
  */
 
 import { log, now } from './helpers';
+import * as tf from '../dist/tfjs.esm.js';
 import * as facemesh from './blazeface/facemesh';
 import * as emotion from './emotion/emotion';
 import * as faceres from './faceres/faceres';
@@ -159,7 +160,7 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
     parent.analyze('Get Face');
 
     // is something went wrong, skip the face
-    if (!faces[i].image || faces[i].image.isDisposedInternal) {
+    if (!faces[i].image || faces[i].image['isDisposedInternal']) {
       log('Face object is disposed:', faces[i].image);
       continue;
     }
@@ -210,19 +211,19 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
 
     // combine results
     faceRes.push({
-      id: i,
       ...faces[i],
+      id: i,
       age: descRes.age,
       gender: descRes.gender,
-      genderConfidence: descRes.genderConfidence,
+      genderScore: descRes.genderConfidence,
       embedding: descRes.descriptor,
       emotion: emotionRes,
       iris: irisSize !== 0 ? Math.trunc(500 / irisSize / 11.7) / 100 : 0,
       rotation,
-      tensor: parent.config.face.detector.return ? faces[i].image?.squeeze() : null,
+      tensor: parent.config.face.detector.return ? tf.squeeze(faces[i].image) : null,
     });
     // dispose original face tensor
-    faces[i].image?.dispose();
+    tf.dispose(faces[i].image);
 
     parent.analyze('End Face');
   }

src/handpose/handpose.ts

@@ -63,7 +63,7 @@ export async function predict(input, config): Promise<Hand[]> {
         (predictions[i].box.bottomRight[1] - predictions[i].box.topLeft[1]) / input.shape[1],
       ];
     }
-    hands.push({ id: i, confidence: Math.round(100 * predictions[i].confidence) / 100, box, boxRaw, keypoints, annotations });
+    hands.push({ id: i, score: Math.round(100 * predictions[i].confidence) / 100, box, boxRaw, keypoints, annotations });
   }
   return hands;
 }

src/interpolate.ts

@@ -70,18 +70,22 @@ export function calc(newResult: Result): Result {
         .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / bufferedFactor)) as [number, number, number, number];
       const boxRaw = (newResult.face[i].boxRaw // update boxRaw
         .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / bufferedFactor)) as [number, number, number, number];
-      const matrix = newResult.face[i].rotation.matrix;
+      const rotation: {
-      const angle = {
+        matrix: [number, number, number, number, number, number, number, number, number],
-        roll: ((bufferedFactor - 1) * bufferedResult.face[i].rotation.angle.roll + newResult.face[i].rotation.angle.roll) / bufferedFactor,
+        angle: { roll: number, yaw: number, pitch: number },
-        yaw: ((bufferedFactor - 1) * bufferedResult.face[i].rotation.angle.yaw + newResult.face[i].rotation.angle.yaw) / bufferedFactor,
+        gaze: { bearing: number, strength: number }
-        pitch: ((bufferedFactor - 1) * bufferedResult.face[i].rotation.angle.pitch + newResult.face[i].rotation.angle.pitch) / bufferedFactor,
+      } = { matrix: [0, 0, 0, 0, 0, 0, 0, 0, 0], angle: { roll: 0, yaw: 0, pitch: 0 }, gaze: { bearing: 0, strength: 0 } };
+      rotation.matrix = newResult.face[i].rotation?.matrix as [number, number, number, number, number, number, number, number, number];
+      rotation.angle = {
+        roll: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.roll || 0) + (newResult.face[i].rotation?.angle?.roll || 0)) / bufferedFactor,
+        yaw: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.yaw || 0) + (newResult.face[i].rotation?.angle?.yaw || 0)) / bufferedFactor,
+        pitch: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.pitch || 0) + (newResult.face[i].rotation?.angle?.pitch || 0)) / bufferedFactor,
       };
-      const gaze = {
+      rotation.gaze = {
         // not fully correct due projection on circle, also causes wrap-around draw on jump from negative to positive
-        bearing: ((bufferedFactor - 1) * bufferedResult.face[i].rotation.gaze.bearing + newResult.face[i].rotation.gaze.bearing) / bufferedFactor,
+        bearing: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.bearing || 0) + (newResult.face[i].rotation?.gaze?.bearing || 0)) / bufferedFactor,
-        strength: ((bufferedFactor - 1) * bufferedResult.face[i].rotation.gaze.strength + newResult.face[i].rotation.gaze.strength) / bufferedFactor,
+        strength: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.strength || 0) + (newResult.face[i].rotation?.gaze?.strength || 0)) / bufferedFactor,
       };
-      const rotation = { angle, matrix, gaze };
       bufferedResult.face[i] = { ...newResult.face[i], rotation, box, boxRaw }; // shallow clone plus updated values
     }
   }

src/result.ts

@@ -10,9 +10,9 @@ import { Tensor } from '../dist/tfjs.esm.js';
  *
  * Each result has:
  * - id: face id number
- * - confidence: overal detection confidence value
+ * - score: overal detection confidence score value
- * - boxConfidence: face box detection confidence value
+ * - boxScore: face box detection confidence score value
- * - faceConfidence: face keypoints detection confidence value
+ * - faceScore: face keypoints detection confidence score value
  * - box: face bounding box as array of [x, y, width, height], normalized to image resolution
  * - boxRaw: face bounding box as array of [x, y, width, height], normalized to range 0..1
  * - mesh: face keypoints as array of [x, y, z] points of face mesh, normalized to image resolution
@@ -20,7 +20,7 @@ import { Tensor } from '../dist/tfjs.esm.js';
  * - annotations: annotated face keypoints as array of annotated face mesh points
  * - age: age as value
  * - gender: gender as value
- * - genderConfidence: gender detection confidence as value
+ * - genderScore: gender detection confidence score as value
  * - emotion: emotions as array of possible emotions with their individual scores
  * - embedding: facial descriptor as array of numerical elements
  * - iris: iris distance from current viewpoint as distance value in centimeters for a typical camera
@@ -33,25 +33,26 @@ import { Tensor } from '../dist/tfjs.esm.js';
  */
 export interface Face {
   id: number
-  confidence: number,
+  score: number,
-  boxConfidence: number,
+  boxScore: number,
-  faceConfidence: number,
+  faceScore: number,
   box: [number, number, number, number],
   boxRaw: [number, number, number, number],
   mesh: Array<[number, number, number]>
   meshRaw: Array<[number, number, number]>
-  annotations: Array<{ part: string, points: Array<[number, number, number]>[] }>,
+  annotations: Record<string, Array<[number, number, number]>>,
-  age: number,
+  age?: number,
-  gender: string,
+  gender?: string,
-  genderConfidence: number,
+  genderScore?: number,
-  emotion: Array<{ score: number, emotion: string }>,
+  emotion?: Array<{ score: number, emotion: string }>,
-  embedding: Array<number>,
+  embedding?: Array<number>,
-  iris: number,
+  iris?: number,
-  rotation: {
+  rotation?: {
     angle: { roll: number, yaw: number, pitch: number },
     matrix: [number, number, number, number, number, number, number, number, number],
     gaze: { bearing: number, strength: number },
   }
+  image: typeof Tensor;
   tensor: typeof Tensor,
 }
 
@@ -86,7 +87,7 @@ export interface Body {
  *
  * Each result has:
  * - id: hand id number
- * - confidence: detection confidence score as value
+ * - score: detection confidence score as value
  * - box: bounding box: x, y, width, height normalized to input image resolution
  * - boxRaw: bounding box: x, y, width, height normalized to 0..1
  * - landmarks: landmarks as array of [x, y, z] points of hand, normalized to image resolution
@@ -94,7 +95,7 @@ export interface Body {
  */
 export interface Hand {
   id: number,
-  confidence: number,
+  score: number,
   box: [number, number, number, number],
   boxRaw: [number, number, number, number],
   keypoints: Array<[number, number, number]>,