modularize build platform

CHANGELOG.md

@@ -11,9 +11,7 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ### **HEAD -> main** 2021/06/05 mandic00@live.com
 
-
-### **origin/main** 2021/06/05 mandic00@live.com
-
+- minor git corruption
 - unified build
 - enable body segmentation and background replacement
 - work on body segmentation

demo/facematch.js

@@ -27,9 +27,8 @@ const userConfig = {
   hand: { enabled: false },
   gesture: { enabled: false },
   body: { enabled: false },
-  filter: {
-    enabled: false,
-  },
+  filter: { enabled: true },
+  segmentation: { enabled: false },
 };
 
 const human = new Human(userConfig); // new instance of human

demo/index.js

@@ -31,6 +31,7 @@ let userConfig = {
   warmup: 'none',
   backend: 'humangl',
   wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.6.0/dist/',
+  segmentation: { enabled: true },
   /*
   async: false,
   cacheSensitivity: 0,
@@ -210,10 +211,9 @@ async function drawResults(input) {
   // draw fps chart
   await menu.process.updateChart('FPS', ui.detectFPS);
 
-  // get updated canvas if missing or if we want buffering, but skip if segmentation is enabled
-  if (userConfig.segmentation.enabled) {
+  if (userConfig.segmentation.enabled && ui.buffered) { // refresh segmentation if using buffered output
     result.canvas = await human.segmentation(input, ui.background, userConfig);
-  } else if (!result.canvas || ui.buffered) {
+  } else if (!result.canvas || ui.buffered) { // refresh with input if using buffered output or if missing canvas
     const image = await human.image(input);
     result.canvas = image.canvas;
     human.tf.dispose(image.tensor);

src/config.ts

@@ -198,7 +198,10 @@ export interface Config {
   },
 
   /** Controlls and configures all body segmentation module
-   * if segmentation is enabled, output result.canvas will be augmented with masked image containing only person output
+   * removes background from input containing person
+   * if segmentation is enabled it will run as preprocessing task before any other model
+   * alternatively leave it disabled and use it on-demand using human.segmentation method which can
+   * remove background or replace it with user-provided background
    *
    * - enabled: true/false
    * - modelPath: object detection model, can be absolute path or relative to modelBasePath
@@ -351,9 +354,11 @@ const config: Config = {
   },
 
   segmentation: {
-    enabled: false,          // if segmentation is enabled, output result.canvas will be augmented
-                             // with masked image containing only person output
-                             // segmentation is not triggered as part of detection and requires separate call to human.segmentation
+    enabled: false,          // controlls and configures all body segmentation module
+                             // removes background from input containing person
+                             // if segmentation is enabled it will run as preprocessing task before any other model
+                             // alternatively leave it disabled and use it on-demand using human.segmentation method which can
+                             // remove background or replace it with user-provided background
     modelPath: 'selfie.json',  // experimental: object detection model, can be absolute path or relative to modelBasePath
                              // can be 'selfie' or 'meet'
   },

src/faceres/faceres.ts

@@ -39,7 +39,7 @@ export function similarity(embedding1: Array<number>, embedding2: Array<number>,
   if (embedding1?.length !== embedding2?.length) return 0;
   // general minkowski distance, euclidean distance is limited case where order is 2
   const distance = 5.0 * embedding1
-    .map((val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared
+    .map((_val, i) => (Math.abs(embedding1[i] - embedding2[i]) ** order)) // distance squared
     .reduce((sum, now) => (sum + now), 0) // sum all distances
     ** (1 / order); // get root of
   const res = Math.max(0, 100 - distance) / 100.0;

src/human.ts

@@ -435,6 +435,7 @@ export class Human {
     return new Promise(async (resolve) => {
       this.state = 'config';
       let timeStamp;
+      let elapsedTime;
 
       // update configuration
       this.config = mergeDeep(this.config, userConfig) as Config;
@@ -473,14 +474,31 @@ export class Human {
       */
 
       timeStamp = now();
-      const process = image.process(input, this.config);
+      let process = image.process(input, this.config);
+      this.performance.image = Math.trunc(now() - timeStamp);
+      this.analyze('Get Image:');
+
+      // run segmentation preprocessing
+      if (this.config.segmentation.enabled && process && process.tensor) {
+        this.analyze('Start Segmentation:');
+        this.state = 'run:segmentation';
+        timeStamp = now();
+        await segmentation.predict(process);
+        elapsedTime = Math.trunc(now() - timeStamp);
+        if (elapsedTime > 0) this.performance.segmentation = elapsedTime;
+        if (process.canvas) {
+          // replace input
+          process.tensor.dispose();
+          process = image.process(process.canvas, this.config);
+        }
+        this.analyze('End Segmentation:');
+      }
+
       if (!process || !process.tensor) {
         log('could not convert input to tensor');
         resolve({ error: 'could not convert input to tensor' });
         return;
       }
-      this.performance.image = Math.trunc(now() - timeStamp);
-      this.analyze('Get Image:');
 
       timeStamp = now();
       this.config.skipFrame = await this.#skipFrame(process.tensor);
@@ -497,7 +515,6 @@ export class Human {
       let bodyRes;
       let handRes;
       let objectRes;
-      let elapsedTime;
 
       // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion
       if (this.config.async) {
@@ -573,19 +590,6 @@ export class Human {
         else if (this.performance.gesture) delete this.performance.gesture;
       }
 
-      // run segmentation
-      /* not triggered as part of detect
-      if (this.config.segmentation.enabled) {
-        this.analyze('Start Segmentation:');
-        this.state = 'run:segmentation';
-        timeStamp = now();
-        await segmentation.predict(process, this.config);
-        elapsedTime = Math.trunc(now() - timeStamp);
-        if (elapsedTime > 0) this.performance.segmentation = elapsedTime;
-        this.analyze('End Segmentation:');
-      }
-      */
-
       this.performance.total = Math.trunc(now() - timeStart);
       this.state = 'idle';
       this.result = {

src/object/nanodet.ts

@@ -96,7 +96,7 @@ async function process(res, inputSize, outputShape, config) {
 
   // filter & sort results
   results = results
-    .filter((a, idx) => nmsIdx.includes(idx))
+    .filter((_val, idx) => nmsIdx.includes(idx))
     .sort((a, b) => (b.score - a.score));
 
   return results;

test/test-node-gpu.js

@@ -6,9 +6,6 @@ const config = {
   backend: 'tensorflow',
   debug: false,
   async: false,
-  filter: {
-    enabled: true,
-  },
   face: {
     enabled: true,
     detector: { enabled: true, rotation: true },
@@ -20,6 +17,8 @@ const config = {
   hand: { enabled: true },
   body: { enabled: true },
   object: { enabled: true },
+  segmentation: { enabled: true },
+  filter: { enabled: false },
 };
 
 test(Human, config);

test/test-node-wasm.js

@@ -8,9 +8,6 @@ const config = {
   // wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.6.0/dist/',
   debug: false,
   async: false,
-  filter: {
-    enabled: true,
-  },
   face: {
     enabled: true,
     detector: { enabled: true, rotation: true },
@@ -22,6 +19,8 @@ const config = {
   hand: { enabled: true },
   body: { enabled: true },
   object: { enabled: false },
+  segmentation: { enabled: true },
+  filter: { enabled: false },
 };
 
 test(Human, config);

test/test-node.js

@@ -6,9 +6,6 @@ const config = {
   backend: 'tensorflow',
   debug: false,
   async: false,
-  filter: {
-    enabled: true,
-  },
   face: {
     enabled: true,
     detector: { enabled: true, rotation: true },
@@ -20,6 +17,8 @@ const config = {
   hand: { enabled: true },
   body: { enabled: true },
   object: { enabled: true },
+  segmentation: { enabled: true },
+  filter: { enabled: false },
 };
 
 test(Human, config);

tsconfig.json

@@ -7,17 +7,16 @@
     "typeRoots": ["node_modules/@types"],
     "outDir": "types",
     "declaration": true,
+    "allowSyntheticDefaultImports": true,
     "emitDeclarationOnly": true,
     "emitDecoratorMetadata": true,
     "experimentalDecorators": true,
     "importHelpers": true,
-    "noImplicitAny": false,
     "preserveConstEnums": true,
     "removeComments": false,
     "resolveJsonModule": true,
     "skipLibCheck": true,
-    "sourceMap": false,
-    "strictNullChecks": true,
+    "sourceMap": true,
     "allowJs": true,
     "baseUrl": "./",
     "paths": {
@@ -25,10 +24,21 @@
       "@tensorflow/tfjs-node/dist/io/file_system": ["node_modules/@tensorflow/tfjs-node/dist/io/file_system.js"],
       "@tensorflow/tfjs-core/dist/index": ["node_modules/@tensorflow/tfjs-core/dist/index.js"],
       "@tensorflow/tfjs-converter/dist/index": ["node_modules/@tensorflow/tfjs-converter/dist/index.js"]
-    }
+    },
+    "strictNullChecks": true,
+    "noImplicitAny": false,
+    "noUnusedLocals": false,
+    "noImplicitReturns": true,
+    "noImplicitThis": true,
+    "alwaysStrict": true,
+    "noUnusedParameters": true,
+    "pretty": true,
+    "noFallthroughCasesInSwitch": true,
+    "allowUnreachableCode": false
   },
   "formatCodeOptions": { "indentSize": 2, "tabSize": 2 },
   "include": ["src/*", "src/***/*"],
+  "exclude": ["node_modules/"],
   "typedocOptions": {
     "excludePrivate": true,
     "excludeExternals": true,

wiki

@@ -1 +1 @@
-Subproject commit c9408224d824368facc264c00e05d7b520d69051
+Subproject commit 9e92e5eec1e60b5ea58dbf1c4bbc67c828bcf673