update iris distance calculations

CHANGELOG.md

@@ -9,13 +9,14 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ## Changelog
 
+### **HEAD -> main** 2021/05/23 mandic00@live.com
+
+
 ### **1.9.3** 2021/05/23 mandic00@live.com
 
 - use green weighted for input diff calculation
 - implement experimental drawoptions.bufferedoutput and bufferedfactor
-
-### **origin/main** 2021/05/22 mandic00@live.com
-
+- use explicit tensor interface
 - add tfjs types and remove all instances of any
 - enhance strong typing
 - rebuild all for release

demo/index.js

@@ -18,18 +18,18 @@ const userConfig = {
     enabled: false,
     flip: false,
   },
-  face: { enabled: false,
-    detector: { return: false },
+  face: { enabled: true,
+    detector: { return: true },
     mesh: { enabled: true },
     iris: { enabled: true },
     description: { enabled: false },
     emotion: { enabled: false },
   },
-  hand: { enabled: true },
-  gesture: { enabled: true },
-  body: { enabled: true, modelPath: 'posenet.json' },
+  hand: { enabled: false },
+  body: { enabled: false, modelPath: 'posenet.json' },
   // body: { enabled: true, modelPath: 'blazepose.json' },
   object: { enabled: false },
+  gesture: { enabled: true },
   */
 };
 

src/face.ts

@@ -161,8 +161,8 @@ export const detectFace = async (parent, input): Promise<Face[]> => {
       delete faces[i].annotations.rightEyeIris;
     }
     const irisSize = (faces[i].annotations?.leftEyeIris && faces[i].annotations?.rightEyeIris)
-    /* average human iris size is 11.7mm */
-      ? 11.7 * Math.max(Math.abs(faces[i].annotations.leftEyeIris[3][0] - faces[i].annotations.leftEyeIris[1][0]), Math.abs(faces[i].annotations.rightEyeIris[4][1] - faces[i].annotations.rightEyeIris[2][1]))
+    /* note: average human iris size is 11.7mm */
+      ? Math.max(Math.abs(faces[i].annotations.leftEyeIris[3][0] - faces[i].annotations.leftEyeIris[1][0]), Math.abs(faces[i].annotations.rightEyeIris[4][1] - faces[i].annotations.rightEyeIris[2][1])) / input.shape[2]
       : 0;
 
     // combine results
@@ -174,7 +174,7 @@ export const detectFace = async (parent, input): Promise<Face[]> => {
       genderConfidence: descRes.genderConfidence,
       embedding: descRes.descriptor,
       emotion: emotionRes,
-      iris: (irisSize !== 0) ? Math.trunc(irisSize) / 100 : 0,
+      iris: irisSize !== 0 ? Math.trunc(500 / irisSize / 11.7) / 100 : 0,
       rotation,
       tensor: parent.config.face.detector.return ? faces[i].image?.squeeze() : null,
     });

src/object/centernet.ts

@@ -20,7 +20,7 @@ export async function load(config) {
 }
 
 async function process(res, inputSize, outputShape, config) {
-  const results: Array<{ score: number, class: number, label: string, box: number[], boxRaw: number[] }> = [];
+  const results: Array<Item> = [];
   const detections = res.arraySync();
   const squeezeT = tf.squeeze(res);
   res.dispose();
@@ -38,6 +38,7 @@ async function process(res, inputSize, outputShape, config) {
   classesT.dispose();
   const nms = nmsT.dataSync();
   nmsT.dispose();
+  let i = 0;
   for (const id of nms) {
     const score = detections[0][id][4];
     const classVal = detections[0][id][5];
@@ -54,7 +55,7 @@ async function process(res, inputSize, outputShape, config) {
       Math.trunc(boxRaw[2] * outputShape[0]),
       Math.trunc(boxRaw[3] * outputShape[1]),
     ];
-    results.push({ score, class: classVal, label, box, boxRaw });
+    results.push({ id: i++, score, class: classVal, label, box, boxRaw });
   }
   return results;
 }

src/object/nanodet.ts

@@ -23,7 +23,7 @@ export async function load(config) {
 
 async function process(res, inputSize, outputShape, config) {
   let id = 0;
-  let results: Array<{ score: number, strideSize: number, class: number, label: string, center: number[], centerRaw: number[], box: number[], boxRaw: number[] }> = [];
+  let results: Array<Item> = [];
   for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects
     // find scores, boxes, classes
     tf.tidy(() => { // wrap in tidy to automatically deallocate temp tensors

src/result.ts

@@ -1,8 +1,4 @@
-/**
- * Result interface definition for **Human** library
- *
- * Contains all possible detection results
- */
+import { Tensor } from '../dist/tfjs.esm.js';
 
 /** Face results
  * Combined results of face detector, face mesh, age, gender, emotion, embedding, iris models
@@ -30,8 +26,6 @@
  *  - matrix: 3d transofrmation matrix as array of numeric values
  * - tensor: face tensor as Tensor object which contains detected face
  */
-import { Tensor } from '../dist/tfjs.esm.js';
-
 export interface Face {
   id: number
   confidence: number,
@@ -69,7 +63,6 @@ export interface Face {
  *  - score: body part score value
  *  - presence: body part presence value
  */
-
 export interface Body {
   id: number,
   score: number,
@@ -115,6 +108,7 @@ export interface Hand {
 * - boxRaw as array of [x, y, width, height], normalized to range 0..1
 */
 export interface Item {
+  id: number,
   score: number,
   strideSize?: number,
   class: number,
@@ -138,6 +132,11 @@ export type Gesture =
   | { 'body': number, gesture: string }
   | { 'hand': number, gesture: string }
 
+/**
+ * Result interface definition for **Human** library
+ *
+ * Contains all possible detection results
+ */
 export interface Result {
   /** {@link Face}: detection & analysis results */
   face: Array<Face>,