ambiser
/
human
mirror of https://github.com/vladmandic/human
9
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

expand type safety

pull/293/head
Vladimir Mandic 2022-08-21 15:23:03 -04:00
parent 369026c2b1
commit 5b4a693429
62 changed files with 1671 additions and 1638 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

21
.eslintrc.json
View File

@ -22,13 +22,29 @@
"eslint:recommended", "eslint:recommended",
"plugin:@typescript-eslint/eslint-recommended", "plugin:@typescript-eslint/eslint-recommended",
"plugin:@typescript-eslint/recommended", "plugin:@typescript-eslint/recommended",
"plugin:@typescript-eslint/recommended-requiring-type-checking",
"plugin:@typescript-eslint/strict",
"plugin:import/recommended", "plugin:import/recommended",
"plugin:promise/recommended" "plugin:promise/recommended"
], ],
"rules": { "rules": {
"@typescript-eslint/ban-ts-comment":"off", "@typescript-eslint/ban-ts-comment":"off",
"@typescript-eslint/dot-notation":"off",
"@typescript-eslint/no-empty-interface":"off", "@typescript-eslint/no-empty-interface":"off",
"@typescript-eslint/no-inferrable-types":"off", "@typescript-eslint/no-inferrable-types":"off",
"@typescript-eslint/no-misused-promises":"off",
"@typescript-eslint/no-unnecessary-condition":"off",
"@typescript-eslint/no-unsafe-argument":"off",
"@typescript-eslint/no-unsafe-assignment":"off",
"@typescript-eslint/no-unsafe-call":"off",
"@typescript-eslint/no-unsafe-member-access":"off",
"@typescript-eslint/no-unsafe-return":"off",
"@typescript-eslint/non-nullable-type-assertion-style":"off",
"@typescript-eslint/prefer-for-of":"off",
"@typescript-eslint/prefer-nullish-coalescing":"off",
"@typescript-eslint/prefer-ts-expect-error":"off",
"@typescript-eslint/restrict-plus-operands":"off",
"@typescript-eslint/restrict-template-expressions":"off",
"dot-notation":"off", "dot-notation":"off",
"guard-for-in":"off", "guard-for-in":"off",
"import/extensions": ["off", "always"], "import/extensions": ["off", "always"],
@ -47,6 +63,7 @@
"no-regex-spaces":"off", "no-regex-spaces":"off",
"no-restricted-syntax":"off", "no-restricted-syntax":"off",
"no-return-assign":"off", "no-return-assign":"off",
"no-void":"off",
"object-curly-newline":"off", "object-curly-newline":"off",
"prefer-destructuring":"off", "prefer-destructuring":"off",
"prefer-template":"off", "prefer-template":"off",
@ -130,8 +147,8 @@
"html", "@html-eslint" "html", "@html-eslint"
], ],
"rules": { "rules": {
"@html-eslint/indent": ["error", 2], "@html-eslint/element-newline":"off",
"@html-eslint/element-newline":"off" "@html-eslint/indent": ["error", 2]
} }
} }
], ],

2
CHANGELOG.md
View File

@ -9,7 +9,7 @@
## Changelog ## Changelog
### **HEAD -> main** 2022/08/20 mandic00@live.com ### **HEAD -> main** 2022/08/21 mandic00@live.com
### **2.9.4** 2022/08/20 mandic00@live.com ### **2.9.4** 2022/08/20 mandic00@live.com

2
TODO.md
View File

@ -66,6 +66,8 @@ Model is supported using `WebGL` backend in browser
- Allow hosting models in **Google Cloud Bucket** - Allow hosting models in **Google Cloud Bucket**
Hosted models can be directly used without downloading to local storage Hosted models can be directly used without downloading to local storage
Example: `modelPath: 'https://storage.googleapis.com/human-models/facemesh.json'` Example: `modelPath: 'https://storage.googleapis.com/human-models/facemesh.json'`
- Stricter linting rules for both **TypeScript** and **JavaScript**
See `./eslintrc.json` for details
- Fix **MobileFaceNet** model as alternative for face embedding/descriptor detection - Fix **MobileFaceNet** model as alternative for face embedding/descriptor detection
Configurable using `config.face.mobilefacenet` config section Configurable using `config.face.mobilefacenet` config section
- Fix **EfficientPose** module as alternative body detection - Fix **EfficientPose** module as alternative body detection

4
demo/faceid/index.js
View File

File diff suppressed because one or more lines are too long

6
demo/faceid/index.js.map
View File

File diff suppressed because one or more lines are too long

18
demo/faceid/index.ts
View File

@ -103,20 +103,20 @@ async function webCam() { // initialize webcam
const stream: MediaStream = await navigator.mediaDevices.getUserMedia(cameraOptions); const stream: MediaStream = await navigator.mediaDevices.getUserMedia(cameraOptions);
const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); }); const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });
dom.video.srcObject = stream; dom.video.srcObject = stream;
dom.video.play(); void dom.video.play();
await ready; await ready;
dom.canvas.width = dom.video.videoWidth; dom.canvas.width = dom.video.videoWidth;
dom.canvas.height = dom.video.videoHeight; dom.canvas.height = dom.video.videoHeight;
if (human.env.initial) log('video:', dom.video.videoWidth, dom.video.videoHeight, '|', stream.getVideoTracks()[0].label); if (human.env.initial) log('video:', dom.video.videoWidth, dom.video.videoHeight, '|', stream.getVideoTracks()[0].label);
dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click
if (dom.video.paused) dom.video.play(); if (dom.video.paused) void dom.video.play();
else dom.video.pause(); else dom.video.pause();
}; };
} }
async function detectionLoop() { // main detection loop async function detectionLoop() { // main detection loop
if (!dom.video.paused) { if (!dom.video.paused) {
if (current.face && current.face.tensor) human.tf.dispose(current.face.tensor); // dispose previous tensor if (current.face?.tensor) human.tf.dispose(current.face.tensor); // dispose previous tensor
await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result
const now = human.now(); const now = human.now();
fps.detect = 1000 / (now - timestamp.detect); fps.detect = 1000 / (now - timestamp.detect);
@ -126,8 +126,8 @@ async function detectionLoop() { // main detection loop
} }
async function validationLoop(): Promise<H.FaceResult> { // main screen refresh loop async function validationLoop(): Promise<H.FaceResult> { // main screen refresh loop
const interpolated = await human.next(human.result); // smoothen result using last-known results const interpolated = human.next(human.result); // smoothen result using last-known results
await human.draw.canvas(dom.video, dom.canvas); // draw canvas to screen human.draw.canvas(dom.video, dom.canvas); // draw canvas to screen
await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc. await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.
const now = human.now(); const now = human.now();
fps.draw = 1000 / (now - timestamp.draw); fps.draw = 1000 / (now - timestamp.draw);
@ -135,7 +135,7 @@ async function validationLoop(): Promise<H.FaceResult> { // main screen refresh
printFPS(`fps: ${fps.detect.toFixed(1).padStart(5, ' ')} detect | ${fps.draw.toFixed(1).padStart(5, ' ')} draw`); // write status printFPS(`fps: ${fps.detect.toFixed(1).padStart(5, ' ')} detect | ${fps.draw.toFixed(1).padStart(5, ' ')} draw`); // write status
ok.faceCount = human.result.face.length === 1; // must be exactly detected face ok.faceCount = human.result.face.length === 1; // must be exactly detected face
if (ok.faceCount) { // skip the rest if no face if (ok.faceCount) { // skip the rest if no face
const gestures: string[] = Object.values(human.result.gesture).map((gesture) => (gesture as H.GestureResult).gesture); // flatten all gestures const gestures: string[] = Object.values(human.result.gesture).map((gesture: H.GestureResult) => gesture.gesture); // flatten all gestures
if (gestures.includes('blink left eye') || gestures.includes('blink right eye')) blink.start = human.now(); // blink starts when eyes get closed if (gestures.includes('blink left eye') || gestures.includes('blink right eye')) blink.start = human.now(); // blink starts when eyes get closed
if (blink.start > 0 && !gestures.includes('blink left eye') && !gestures.includes('blink right eye')) blink.end = human.now(); // if blink started how long until eyes are back open if (blink.start > 0 && !gestures.includes('blink left eye') && !gestures.includes('blink right eye')) blink.end = human.now(); // if blink started how long until eyes are back open
ok.blinkDetected = ok.blinkDetected || (Math.abs(blink.end - blink.start) > options.blinkMin && Math.abs(blink.end - blink.start) < options.blinkMax); ok.blinkDetected = ok.blinkDetected || (Math.abs(blink.end - blink.start) > options.blinkMin && Math.abs(blink.end - blink.start) < options.blinkMax);
@ -173,8 +173,8 @@ async function validationLoop(): Promise<H.FaceResult> { // main screen refresh
ok.elapsedMs = Math.trunc(human.now() - startTime); ok.elapsedMs = Math.trunc(human.now() - startTime);
return new Promise((resolve) => { return new Promise((resolve) => {
setTimeout(async () => { setTimeout(async () => {
const res = await validationLoop(); // run validation loop until conditions are met await validationLoop(); // run validation loop until conditions are met
if (res) resolve(human.result.face[0]); // recursive promise resolve resolve(human.result.face[0]); // recursive promise resolve
}, 30); // use to slow down refresh from max refresh rate to target of 30 fps }, 30); // use to slow down refresh from max refresh rate to target of 30 fps
}); });
} }
@ -210,7 +210,7 @@ async function detectFace() {
} }
const db = await indexDb.load(); const db = await indexDb.load();
const descriptors = db.map((rec) => rec.descriptor).filter((desc) => desc.length > 0); const descriptors = db.map((rec) => rec.descriptor).filter((desc) => desc.length > 0);
const res = await human.match(current.face.embedding, descriptors, matchOptions); const res = human.match(current.face.embedding, descriptors, matchOptions);
current.record = db[res.index] || null; current.record = db[res.index] || null;
if (current.record) { if (current.record) {
log(`best match: ${current.record.name} | id: ${current.record.id} | similarity: ${Math.round(1000 * res.similarity) / 10}%`); log(`best match: ${current.record.name} | id: ${current.record.id} | similarity: ${Math.round(1000 * res.similarity) / 10}%`);

4
demo/typescript/index.js
View File

@ -4,6 +4,6 @@
author: <https://github.com/vladmandic>' author: <https://github.com/vladmandic>'
*/ */
import*as c from"../../dist/human.esm.js";var w={async:!1,modelBasePath:"../../models",filter:{enabled:!0,equalization:!1,flip:!1},face:{enabled:!0,detector:{rotation:!1},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0}},body:{enabled:!0},hand:{enabled:!0},object:{enabled:!1},gesture:{enabled:!0}},e=new c.Human(w);e.env.perfadd=!1;e.draw.options.font='small-caps 18px "Lato"';e.draw.options.lineHeight=20;var t={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},n={detect:0,draw:0,tensors:0,start:0},s={detectFPS:0,drawFPS:0,frames:0,averageMs:0},i=(...a)=>{t.log.innerText+=a.join(" ")+` import*as c from"../../dist/human.esm.js";var w={async:!1,modelBasePath:"../../models",filter:{enabled:!0,equalization:!1,flip:!1},face:{enabled:!0,detector:{rotation:!1},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0}},body:{enabled:!0},hand:{enabled:!0},object:{enabled:!1},gesture:{enabled:!0}},e=new c.Human(w);e.env.perfadd=!1;e.draw.options.font='small-caps 18px "Lato"';e.draw.options.lineHeight=20;var t={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},n={detect:0,draw:0,tensors:0,start:0},o={detectFPS:0,drawFPS:0,frames:0,averageMs:0},i=(...a)=>{t.log.innerText+=a.join(" ")+`
`,console.log(...a)},r=a=>t.fps.innerText=a,b=a=>t.perf.innerText="tensors:"+e.tf.memory().numTensors+" | performance: "+JSON.stringify(a).replace(/"|{|}/g,"").replace(/,/g," | ");async function h(){r("starting webcam...");let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth},height:{ideal:document.body.clientHeight}}},d=await navigator.mediaDevices.getUserMedia(a),f=new Promise(p=>{t.video.onloadeddata=()=>p(!0)});t.video.srcObject=d,t.video.play(),await f,t.canvas.width=t.video.videoWidth,t.canvas.height=t.video.videoHeight;let o=d.getVideoTracks()[0],v=o.getCapabilities?o.getCapabilities():"",g=o.getSettings?o.getSettings():"",u=o.getConstraints?o.getConstraints():"";i("video:",t.video.videoWidth,t.video.videoHeight,o.label,{stream:d,track:o,settings:g,constraints:u,capabilities:v}),t.canvas.onclick=()=>{t.video.paused?t.video.play():t.video.pause()}}async function l(){if(!t.video.paused){n.start===0&&(n.start=e.now()),await e.detect(t.video);let a=e.tf.memory().numTensors;a-n.tensors!==0&&i("allocated tensors:",a-n.tensors),n.tensors=a,s.detectFPS=Math.round(1e3*1e3/(e.now()-n.detect))/1e3,s.frames++,s.averageMs=Math.round(1e3*(e.now()-n.start)/s.frames)/1e3,s.frames%100===0&&!t.video.paused&&i("performance",{...s,tensors:n.tensors})}n.detect=e.now(),requestAnimationFrame(l)}async function m(){if(!t.video.paused){let d=await e.next(e.result);e.config.filter.flip?await e.draw.canvas(d.canvas,t.canvas):await e.draw.canvas(t.video,t.canvas),await e.draw.all(t.canvas,d),b(d.performance)}let a=e.now();s.drawFPS=Math.round(1e3*1e3/(a-n.draw))/1e3,n.draw=a,r(t.video.paused?"paused":`fps: ${s.detectFPS.toFixed(1).padStart(5," ")} detect | ${s.drawFPS.toFixed(1).padStart(5," ")} draw`),setTimeout(m,30)}async function M(){i("human version:",e.version,"| tfjs version:",e.tf.version["tfjs-core"]),i("platform:",e.env.platform,"| agent:",e.env.agent),r("loading..."),await e.load(),i("backend:",e.tf.getBackend(),"| available:",e.env.backends),i("models stats:",e.getModelStats()),i("models loaded:",Object.values(e.models).filter(a=>a!==null).length),r("initializing..."),await e.warmup(),await h(),await l(),await m()}window.onload=M; `,console.log(...a)},r=a=>t.fps.innerText=a,b=a=>t.perf.innerText="tensors:"+e.tf.memory().numTensors.toString()+" | performance: "+JSON.stringify(a).replace(/"|{|}/g,"").replace(/,/g," | ");async function h(){r("starting webcam...");let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth},height:{ideal:document.body.clientHeight}}},d=await navigator.mediaDevices.getUserMedia(a),f=new Promise(p=>{t.video.onloadeddata=()=>p(!0)});t.video.srcObject=d,t.video.play(),await f,t.canvas.width=t.video.videoWidth,t.canvas.height=t.video.videoHeight;let s=d.getVideoTracks()[0],v=s.getCapabilities?s.getCapabilities():"",g=s.getSettings?s.getSettings():"",u=s.getConstraints?s.getConstraints():"";i("video:",t.video.videoWidth,t.video.videoHeight,s.label,{stream:d,track:s,settings:g,constraints:u,capabilities:v}),t.canvas.onclick=()=>{t.video.paused?t.video.play():t.video.pause()}}async function l(){if(!t.video.paused){n.start===0&&(n.start=e.now()),await e.detect(t.video);let a=e.tf.memory().numTensors;a-n.tensors!==0&&i("allocated tensors:",a-n.tensors),n.tensors=a,o.detectFPS=Math.round(1e3*1e3/(e.now()-n.detect))/1e3,o.frames++,o.averageMs=Math.round(1e3*(e.now()-n.start)/o.frames)/1e3,o.frames%100===0&&!t.video.paused&&i("performance",{...o,tensors:n.tensors})}n.detect=e.now(),requestAnimationFrame(l)}async function m(){if(!t.video.paused){let d=e.next(e.result);e.config.filter.flip?e.draw.canvas(d.canvas,t.canvas):e.draw.canvas(t.video,t.canvas),await e.draw.all(t.canvas,d),b(d.performance)}let a=e.now();o.drawFPS=Math.round(1e3*1e3/(a-n.draw))/1e3,n.draw=a,r(t.video.paused?"paused":`fps: ${o.detectFPS.toFixed(1).padStart(5," ")} detect | ${o.drawFPS.toFixed(1).padStart(5," ")} draw`),setTimeout(m,30)}async function M(){i("human version:",e.version,"| tfjs version:",e.tf.version["tfjs-core"]),i("platform:",e.env.platform,"| agent:",e.env.agent),r("loading..."),await e.load(),i("backend:",e.tf.getBackend(),"| available:",e.env.backends),i("models stats:",e.getModelStats()),i("models loaded:",Object.values(e.models).filter(a=>a!==null).length),r("initializing..."),await e.warmup(),await h(),await l(),await m()}window.onload=M;
//# sourceMappingURL=index.js.map //# sourceMappingURL=index.js.map

4
demo/typescript/index.js.map
View File

File diff suppressed because one or more lines are too long

12
demo/typescript/index.ts
View File

@ -45,7 +45,7 @@ const log = (...msg) => { // helper method to output messages
console.log(...msg); // eslint-disable-line no-console console.log(...msg); // eslint-disable-line no-console
}; };
const status = (msg) => dom.fps.innerText = msg; // print status element const status = (msg) => dom.fps.innerText = msg; // print status element
const perf = (msg) => dom.perf.innerText = 'tensors:' + human.tf.memory().numTensors + ' | performance: ' + JSON.stringify(msg).replace(/"|{|}/g, '').replace(/,/g, ' | '); // print performance element const perf = (msg) => dom.perf.innerText = 'tensors:' + (human.tf.memory().numTensors as number).toString() + ' | performance: ' + JSON.stringify(msg).replace(/"|{|}/g, '').replace(/,/g, ' | '); // print performance element
async function webCam() { // initialize webcam async function webCam() { // initialize webcam
status('starting webcam...'); status('starting webcam...');
@ -54,7 +54,7 @@ async function webCam() { // initialize webcam
const stream: MediaStream = await navigator.mediaDevices.getUserMedia(options); const stream: MediaStream = await navigator.mediaDevices.getUserMedia(options);
const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); }); const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });
dom.video.srcObject = stream; dom.video.srcObject = stream;
dom.video.play(); void dom.video.play();
await ready; await ready;
dom.canvas.width = dom.video.videoWidth; dom.canvas.width = dom.video.videoWidth;
dom.canvas.height = dom.video.videoHeight; dom.canvas.height = dom.video.videoHeight;
@ -64,7 +64,7 @@ async function webCam() { // initialize webcam
const constraints: MediaTrackConstraints | string = track.getConstraints ? track.getConstraints() : ''; const constraints: MediaTrackConstraints | string = track.getConstraints ? track.getConstraints() : '';
log('video:', dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities }); log('video:', dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities });
dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click
if (dom.video.paused) dom.video.play(); if (dom.video.paused) void dom.video.play();
else dom.video.pause(); else dom.video.pause();
}; };
} }
@ -88,9 +88,9 @@ async function detectionLoop() { // main detection loop
async function drawLoop() { // main screen refresh loop async function drawLoop() { // main screen refresh loop
if (!dom.video.paused) { if (!dom.video.paused) {
const interpolated = await human.next(human.result); // smoothen result using last-known results const interpolated = human.next(human.result); // smoothen result using last-known results
if (human.config.filter.flip) await human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas if (human.config.filter.flip) human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas
else await human.draw.canvas(dom.video, dom.canvas); // draw original video to screen canvas // better than using procesed image as this loop happens faster than processing loop else human.draw.canvas(dom.video, dom.canvas); // draw original video to screen canvas // better than using procesed image as this loop happens faster than processing loop
await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc. await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.
perf(interpolated.performance); // write performance data perf(interpolated.performance); // write performance data
} }

14
dist/human.d.ts vendored
View File

@ -28,7 +28,7 @@ declare interface ArrayMap {
export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu']; export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];
/** draw detected bodies */ /** draw detected bodies */
declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): void;
export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose; export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose;
@ -140,7 +140,7 @@ declare function browserFiles(files: File[]): IOHandler;
declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler; declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;
/** draw processed canvas */ /** draw processed canvas */
declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): Promise<void>; declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): void;
/** /**
* Concatenate a number of ArrayBuffers into one. * Concatenate a number of ArrayBuffers into one.
@ -509,7 +509,7 @@ export declare type Events = 'create' | 'load' | 'image' | 'result' | 'warmup' |
export declare type ExternalCanvas = typeof env.Canvas; export declare type ExternalCanvas = typeof env.Canvas;
/** draw detected faces */ /** draw detected faces */
declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): void;
/** Anti-spoofing part of face configuration */ /** Anti-spoofing part of face configuration */
export declare interface FaceAntiSpoofConfig extends GenericConfig { export declare interface FaceAntiSpoofConfig extends GenericConfig {
@ -780,7 +780,7 @@ export declare interface GenericConfig {
} }
/** draw detected gestures */ /** draw detected gestures */
declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): void;
/** Controlls gesture detection */ /** Controlls gesture detection */
export declare interface GestureConfig { export declare interface GestureConfig {
@ -1038,7 +1038,7 @@ export declare class GraphModel<ModelURL extends Url = string | io.IOHandler> im
} }
/** draw detected hands */ /** draw detected hands */
declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all hand detection specific options */ /** Configures all hand detection specific options */
export declare interface HandConfig extends GenericConfig { export declare interface HandConfig extends GenericConfig {
@ -2022,7 +2022,7 @@ declare type NamedTensorsMap = {
declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64'; declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64';
/** draw detected objects */ /** draw detected objects */
declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all object detection specific options */ /** Configures all object detection specific options */
export declare interface ObjectConfig extends GenericConfig { export declare interface ObjectConfig extends GenericConfig {
@ -2065,7 +2065,7 @@ declare type OnProgressCallback = (fraction: number) => void;
declare const options: DrawOptions; declare const options: DrawOptions;
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): void;
/** Person getter /** Person getter
* - Triggers combining all individual results into a virtual person object * - Triggers combining all individual results into a virtual person object

14
dist/human.esm-nobundle.d.ts vendored
View File

@ -28,7 +28,7 @@ declare interface ArrayMap {
export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu']; export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];
/** draw detected bodies */ /** draw detected bodies */
declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): void;
export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose; export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose;
@ -140,7 +140,7 @@ declare function browserFiles(files: File[]): IOHandler;
declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler; declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;
/** draw processed canvas */ /** draw processed canvas */
declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): Promise<void>; declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): void;
/** /**
* Concatenate a number of ArrayBuffers into one. * Concatenate a number of ArrayBuffers into one.
@ -509,7 +509,7 @@ export declare type Events = 'create' | 'load' | 'image' | 'result' | 'warmup' |
export declare type ExternalCanvas = typeof env.Canvas; export declare type ExternalCanvas = typeof env.Canvas;
/** draw detected faces */ /** draw detected faces */
declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): void;
/** Anti-spoofing part of face configuration */ /** Anti-spoofing part of face configuration */
export declare interface FaceAntiSpoofConfig extends GenericConfig { export declare interface FaceAntiSpoofConfig extends GenericConfig {
@ -780,7 +780,7 @@ export declare interface GenericConfig {
} }
/** draw detected gestures */ /** draw detected gestures */
declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): void;
/** Controlls gesture detection */ /** Controlls gesture detection */
export declare interface GestureConfig { export declare interface GestureConfig {
@ -1038,7 +1038,7 @@ export declare class GraphModel<ModelURL extends Url = string | io.IOHandler> im
} }
/** draw detected hands */ /** draw detected hands */
declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all hand detection specific options */ /** Configures all hand detection specific options */
export declare interface HandConfig extends GenericConfig { export declare interface HandConfig extends GenericConfig {
@ -2022,7 +2022,7 @@ declare type NamedTensorsMap = {
declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64'; declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64';
/** draw detected objects */ /** draw detected objects */
declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all object detection specific options */ /** Configures all object detection specific options */
export declare interface ObjectConfig extends GenericConfig { export declare interface ObjectConfig extends GenericConfig {
@ -2065,7 +2065,7 @@ declare type OnProgressCallback = (fraction: number) => void;
declare const options: DrawOptions; declare const options: DrawOptions;
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): void;
/** Person getter /** Person getter
* - Triggers combining all individual results into a virtual person object * - Triggers combining all individual results into a virtual person object

20
dist/human.esm-nobundle.js vendored
View File

File diff suppressed because one or more lines are too long

6
dist/human.esm-nobundle.js.map vendored
View File

File diff suppressed because one or more lines are too long

14
dist/human.esm.d.ts vendored
View File

@ -28,7 +28,7 @@ declare interface ArrayMap {
export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu']; export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];
/** draw detected bodies */ /** draw detected bodies */
declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): void;
export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose; export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose;
@ -140,7 +140,7 @@ declare function browserFiles(files: File[]): IOHandler;
declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler; declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;
/** draw processed canvas */ /** draw processed canvas */
declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): Promise<void>; declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): void;
/** /**
* Concatenate a number of ArrayBuffers into one. * Concatenate a number of ArrayBuffers into one.
@ -509,7 +509,7 @@ export declare type Events = 'create' | 'load' | 'image' | 'result' | 'warmup' |
export declare type ExternalCanvas = typeof env.Canvas; export declare type ExternalCanvas = typeof env.Canvas;
/** draw detected faces */ /** draw detected faces */
declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): void;
/** Anti-spoofing part of face configuration */ /** Anti-spoofing part of face configuration */
export declare interface FaceAntiSpoofConfig extends GenericConfig { export declare interface FaceAntiSpoofConfig extends GenericConfig {
@ -780,7 +780,7 @@ export declare interface GenericConfig {
} }
/** draw detected gestures */ /** draw detected gestures */
declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): void;
/** Controlls gesture detection */ /** Controlls gesture detection */
export declare interface GestureConfig { export declare interface GestureConfig {
@ -1038,7 +1038,7 @@ export declare class GraphModel<ModelURL extends Url = string | io.IOHandler> im
} }
/** draw detected hands */ /** draw detected hands */
declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all hand detection specific options */ /** Configures all hand detection specific options */
export declare interface HandConfig extends GenericConfig { export declare interface HandConfig extends GenericConfig {
@ -2022,7 +2022,7 @@ declare type NamedTensorsMap = {
declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64'; declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64';
/** draw detected objects */ /** draw detected objects */
declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all object detection specific options */ /** Configures all object detection specific options */
export declare interface ObjectConfig extends GenericConfig { export declare interface ObjectConfig extends GenericConfig {
@ -2065,7 +2065,7 @@ declare type OnProgressCallback = (fraction: number) => void;
declare const options: DrawOptions; declare const options: DrawOptions;
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): void;
/** Person getter /** Person getter
* - Triggers combining all individual results into a virtual person object * - Triggers combining all individual results into a virtual person object

128
dist/human.esm.js vendored
View File

@ -72546,7 +72546,7 @@ var GLProgram = class {
this.gl.shaderSource(shader, source); this.gl.shaderSource(shader, source);
this.gl.compileShader(shader); this.gl.compileShader(shader);
if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) { if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) {
log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader)}`); log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader) || "unknown"}`);
return null; return null;
} }
return shader; return shader;
@ -72565,7 +72565,7 @@ var GLProgram = class {
this.gl.attachShader(this.id, fragmentShader); this.gl.attachShader(this.id, fragmentShader);
this.gl.linkProgram(this.id); this.gl.linkProgram(this.id);
if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) { if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) {
log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`); log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id) || "unknown"}`);
return; return;
} }
this.gl.useProgram(this.id); this.gl.useProgram(this.id);
@ -73187,6 +73187,7 @@ function copy(input2, output) {
return outputCanvas; return outputCanvas;
} }
async function process2(input2, config3, getTensor2 = true) { async function process2(input2, config3, getTensor2 = true) {
var _a, _b;
if (!input2) { if (!input2) {
if (config3.debug) if (config3.debug)
log("input error: input is missing"); log("input error: input is missing");
@ -73217,7 +73218,7 @@ async function process2(input2, config3, getTensor2 = true) {
} }
} }
if (tensor3 == null || tensor3.shape.length !== 4 || tensor3.shape[0] !== 1 || tensor3.shape[3] !== 3) if (tensor3 == null || tensor3.shape.length !== 4 || tensor3.shape[0] !== 1 || tensor3.shape[3] !== 3)
throw new Error(`input error: attempted to use tensor with unrecognized shape: ${input2.shape}`); throw new Error(`input error: attempted to use tensor with unrecognized shape: ${input2.shape.toString()}`);
if (tensor3.dtype === "int32") { if (tensor3.dtype === "int32") {
const cast7 = cast(tensor3, "float32"); const cast7 = cast(tensor3, "float32");
dispose(tensor3); dispose(tensor3);
@ -73247,9 +73248,9 @@ async function process2(input2, config3, getTensor2 = true) {
targetHeight = maxSize; targetHeight = maxSize;
targetWidth = Math.trunc(targetHeight * originalWidth / originalHeight); targetWidth = Math.trunc(targetHeight * originalWidth / originalHeight);
} }
if ((config3.filter.width || 0) > 0) if ((((_a = config3.filter) == null ? void 0 : _a.width) || 0) > 0)
targetWidth = config3.filter.width; targetWidth = config3.filter.width;
else if ((config3.filter.height || 0) > 0) else if ((((_b = config3.filter) == null ? void 0 : _b.height) || 0) > 0)
targetWidth = originalWidth * ((config3.filter.height || 0) / originalHeight); targetWidth = originalWidth * ((config3.filter.height || 0) / originalHeight);
if ((config3.filter.height || 0) > 0) if ((config3.filter.height || 0) > 0)
targetHeight = config3.filter.height; targetHeight = config3.filter.height;
@ -73466,9 +73467,9 @@ var Env = class {
this.worker = this.browser && this.offscreen ? typeof WorkerGlobalScope !== "undefined" : void 0; this.worker = this.browser && this.offscreen ? typeof WorkerGlobalScope !== "undefined" : void 0;
if (typeof navigator !== "undefined") { if (typeof navigator !== "undefined") {
const raw = navigator.userAgent.match(/\(([^()]+)\)/g); const raw = navigator.userAgent.match(/\(([^()]+)\)/g);
if (raw && raw[0]) { if (raw == null ? void 0 : raw[0]) {
const platformMatch = raw[0].match(/\(([^()]+)\)/g); const platformMatch = raw[0].match(/\(([^()]+)\)/g);
this.platform = platformMatch && platformMatch[0] ? platformMatch[0].replace(/\(|\)/g, "") : ""; this.platform = (platformMatch == null ? void 0 : platformMatch[0]) ? platformMatch[0].replace(/\(|\)/g, "") : "";
this.agent = navigator.userAgent.replace(raw[0], ""); this.agent = navigator.userAgent.replace(raw[0], "");
if (this.platform[1]) if (this.platform[1])
this.agent = this.agent.replace(raw[1], ""); this.agent = this.agent.replace(raw[1], "");
@ -77669,7 +77670,7 @@ var inputSize2 = 224;
var anchorTensor; var anchorTensor;
var numLayers = 5; var numLayers = 5;
var strides = [8, 16, 32, 32, 32]; var strides = [8, 16, 32, 32, 32];
async function createAnchors() { function createAnchors() {
const anchors3 = []; const anchors3 = [];
let layerId = 0; let layerId = 0;
while (layerId < numLayers) { while (layerId < numLayers) {
@ -77748,7 +77749,7 @@ async function loadDetect(config3) {
inputSize3.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0; inputSize3.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
} else if (config3.debug && models2.detector) } else if (config3.debug && models2.detector)
log("cached model:", models2.detector["modelUrl"]); log("cached model:", models2.detector["modelUrl"]);
await createAnchors(); createAnchors();
return models2.detector; return models2.detector;
} }
async function loadPose(config3) { async function loadPose(config3) {
@ -77763,7 +77764,7 @@ async function loadPose(config3) {
log("cached model:", models2.landmarks["modelUrl"]); log("cached model:", models2.landmarks["modelUrl"]);
return models2.landmarks; return models2.landmarks;
} }
async function prepareImage(input2, size2) { function prepareImage(input2, size2) {
const t2 = {}; const t2 = {};
if (!input2.shape || !input2.shape[1] || !input2.shape[2]) if (!input2.shape || !input2.shape[1] || !input2.shape[2])
return input2; return input2;
@ -77823,7 +77824,7 @@ function rescaleKeypoints(keypoints, outputSize2) {
} }
return keypoints; return keypoints;
} }
async function fixKeypoints(keypoints) { function fixKeypoints(keypoints) {
const leftPalm = keypoints.find((k) => k.part === "leftPalm"); const leftPalm = keypoints.find((k) => k.part === "leftPalm");
const leftWrist = keypoints.find((k) => k.part === "leftWrist"); const leftWrist = keypoints.find((k) => k.part === "leftWrist");
const leftIndex = keypoints.find((k) => k.part === "leftIndex"); const leftIndex = keypoints.find((k) => k.part === "leftIndex");
@ -77880,7 +77881,7 @@ async function predict5(input2, config3) {
skipped5++; skipped5++;
} else { } else {
const t2 = {}; const t2 = {};
t2.landmarks = await prepareImage(input2, 256); t2.landmarks = prepareImage(input2, 256);
cache = await detectLandmarks(t2.landmarks, config3, outputSize2); cache = await detectLandmarks(t2.landmarks, config3, outputSize2);
Object.keys(t2).forEach((tensor2) => dispose(t2[tensor2])); Object.keys(t2).forEach((tensor2) => dispose(t2[tensor2]));
lastTime5 = now(); lastTime5 = now();
@ -79006,7 +79007,7 @@ async function predict12(image2, config3, idx, count3) {
const resT = model14 == null ? void 0 : model14.execute(enhanced); const resT = model14 == null ? void 0 : model14.execute(enhanced);
lastTime11 = now(); lastTime11 = now();
dispose(enhanced); dispose(enhanced);
const genderT = await resT.find((t2) => t2.shape[1] === 1); const genderT = resT.find((t2) => t2.shape[1] === 1);
const gender2 = await genderT.data(); const gender2 = await genderT.data();
const confidence = Math.trunc(200 * Math.abs(gender2[0] - 0.5)) / 100; const confidence = Math.trunc(200 * Math.abs(gender2[0] - 0.5)) / 100;
if (confidence > (config3.face.description.minConfidence || 0)) { if (confidence > (config3.face.description.minConfidence || 0)) {
@ -82099,10 +82100,11 @@ var HandDetector = class {
__publicField(this, "inputSize"); __publicField(this, "inputSize");
__publicField(this, "inputSizeTensor"); __publicField(this, "inputSizeTensor");
__publicField(this, "doubleInputSizeTensor"); __publicField(this, "doubleInputSizeTensor");
var _a, _b, _c, _d;
this.model = model20; this.model = model20;
this.anchors = anchors2.map((anchor) => [anchor.x, anchor.y]); this.anchors = anchors2.map((anchor) => [anchor.x, anchor.y]);
this.anchorsTensor = tensor2d(this.anchors); this.anchorsTensor = tensor2d(this.anchors);
this.inputSize = this.model && this.model.inputs && this.model.inputs[0].shape ? this.model.inputs[0].shape[2] : 0; this.inputSize = ((_d = (_c = (_b = (_a = this == null ? void 0 : this.model) == null ? void 0 : _a.inputs) == null ? void 0 : _b[0]) == null ? void 0 : _c.shape) == null ? void 0 : _d[2]) || 0;
this.inputSizeTensor = tensor1d([this.inputSize, this.inputSize]); this.inputSizeTensor = tensor1d([this.inputSize, this.inputSize]);
this.doubleInputSizeTensor = tensor1d([this.inputSize * 2, this.inputSize * 2]); this.doubleInputSizeTensor = tensor1d([this.inputSize * 2, this.inputSize * 2]);
} }
@ -82125,12 +82127,13 @@ var HandDetector = class {
const t2 = {}; const t2 = {};
t2.reshape = reshape(rawPalmLandmarks, [-1, 7, 2]); t2.reshape = reshape(rawPalmLandmarks, [-1, 7, 2]);
t2.div = div(t2.reshape, this.inputSizeTensor); t2.div = div(t2.reshape, this.inputSizeTensor);
t2.landmarks = add2(t2.div, this.anchors[index2]); t2.landmarks = add2(t2.div, this.anchors[index2] ? this.anchors[index2] : 0);
const res = mul(t2.landmarks, this.inputSizeTensor); const res = mul(t2.landmarks, this.inputSizeTensor);
Object.keys(t2).forEach((tensor2) => dispose(t2[tensor2])); Object.keys(t2).forEach((tensor2) => dispose(t2[tensor2]));
return res; return res;
} }
async predict(input2, config3) { async predict(input2, config3) {
var _a;
const t2 = {}; const t2 = {};
t2.resize = image.resizeBilinear(input2, [this.inputSize, this.inputSize]); t2.resize = image.resizeBilinear(input2, [this.inputSize, this.inputSize]);
t2.div = div(t2.resize, constants.tf127); t2.div = div(t2.resize, constants.tf127);
@ -82143,7 +82146,7 @@ var HandDetector = class {
const scores = await t2.scores.data(); const scores = await t2.scores.data();
t2.boxes = slice(t2.predictions, [0, 1], [-1, 4]); t2.boxes = slice(t2.predictions, [0, 1], [-1, 4]);
t2.norm = this.normalizeBoxes(t2.boxes); t2.norm = this.normalizeBoxes(t2.boxes);
t2.nms = await image.nonMaxSuppressionAsync(t2.norm, t2.scores, 3 * config3.hand.maxDetected, config3.hand.iouThreshold, config3.hand.minConfidence); t2.nms = await image.nonMaxSuppressionAsync(t2.norm, t2.scores, 3 * (((_a = config3.hand) == null ? void 0 : _a.maxDetected) || 1), config3.hand.iouThreshold, config3.hand.minConfidence);
const nms = await t2.nms.array(); const nms = await t2.nms.array();
const hands = []; const hands = [];
for (const index2 of nms) { for (const index2 of nms) {
@ -82157,7 +82160,7 @@ var HandDetector = class {
const endPoint = box.slice(2, 4); const endPoint = box.slice(2, 4);
const palmLandmarks = await p2.palmLandmarks.array(); const palmLandmarks = await p2.palmLandmarks.array();
const hand3 = { startPoint, endPoint, palmLandmarks, confidence: scores[index2] }; const hand3 = { startPoint, endPoint, palmLandmarks, confidence: scores[index2] };
const scaled = scaleBoxCoordinates2(hand3, [input2.shape[2] / this.inputSize, input2.shape[1] / this.inputSize]); const scaled = scaleBoxCoordinates2(hand3, [(input2.shape[2] || 1) / this.inputSize, (input2.shape[1] || 0) / this.inputSize]);
hands.push(scaled); hands.push(scaled);
Object.keys(p2).forEach((tensor2) => dispose(p2[tensor2])); Object.keys(p2).forEach((tensor2) => dispose(p2[tensor2]));
} }
@ -82181,9 +82184,10 @@ var HandPipeline = class {
__publicField(this, "storedBoxes"); __publicField(this, "storedBoxes");
__publicField(this, "skipped"); __publicField(this, "skipped");
__publicField(this, "detectedHands"); __publicField(this, "detectedHands");
var _a, _b, _c;
this.handDetector = handDetector; this.handDetector = handDetector;
this.handPoseModel = handPoseModel2; this.handPoseModel = handPoseModel2;
this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0; this.inputSize = ((_c = (_b = (_a = this.handPoseModel) == null ? void 0 : _a.inputs) == null ? void 0 : _b[0].shape) == null ? void 0 : _c[2]) || 0;
this.storedBoxes = []; this.storedBoxes = [];
this.skipped = Number.MAX_SAFE_INTEGER; this.skipped = Number.MAX_SAFE_INTEGER;
this.detectedHands = 0; this.detectedHands = 0;
@ -82803,8 +82807,9 @@ async function load14(config3) {
if (config3.debug) if (config3.debug)
log("cached model:", handPoseModel["modelUrl"]); log("cached model:", handPoseModel["modelUrl"]);
} }
const handDetector = new HandDetector(handDetectorModel); const handDetector = handDetectorModel ? new HandDetector(handDetectorModel) : void 0;
handPipeline = new HandPipeline(handDetector, handPoseModel); if (handDetector && handPoseModel)
handPipeline = new HandPipeline(handDetector, handPoseModel);
return [handDetectorModel, handPoseModel]; return [handDetectorModel, handPoseModel];
} }
@ -82832,7 +82837,7 @@ function extensions() {
return; return;
config2.extensions = gl.getSupportedExtensions(); config2.extensions = gl.getSupportedExtensions();
} }
async function register(instance2) { function register(instance2) {
if (instance2.config.backend !== "humangl") if (instance2.config.backend !== "humangl")
return; return;
if (config2.name in engine().registry && (!config2.gl || !config2.gl.getParameter(config2.gl.VERSION))) { if (config2.name in engine().registry && (!config2.gl || !config2.gl.getParameter(config2.gl.VERSION))) {
@ -82841,7 +82846,7 @@ async function register(instance2) {
} }
if (!findBackend(config2.name)) { if (!findBackend(config2.name)) {
try { try {
config2.canvas = await canvas(100, 100); config2.canvas = canvas(100, 100);
} catch (err) { } catch (err) {
log("error: cannot create canvas:", err); log("error: cannot create canvas:", err);
return; return;
@ -82859,7 +82864,7 @@ async function register(instance2) {
return; return;
} }
if (config2.canvas) { if (config2.canvas) {
config2.canvas.addEventListener("webglcontextlost", async (e2) => { config2.canvas.addEventListener("webglcontextlost", (e2) => {
log("error: humangl:", e2.type); log("error: humangl:", e2.type);
log("possible browser memory leak using webgl or conflict with multiple backend registrations"); log("possible browser memory leak using webgl or conflict with multiple backend registrations");
instance2.emit("error"); instance2.emit("error");
@ -82933,7 +82938,7 @@ function registerCustomOps() {
const kernelMod = { const kernelMod = {
kernelName: "FloorMod", kernelName: "FloorMod",
backendName: getBackend(), backendName: getBackend(),
kernelFunc: (op2) => tidy(() => floorDiv(op2.inputs.a / op2.inputs.b) * op2.inputs.b + mod(op2.inputs.a, op2.inputs.b)) kernelFunc: (op2) => tidy(() => add2(mul(floorDiv(op2.inputs.a / op2.inputs.b), op2.inputs.b), mod(op2.inputs.a, op2.inputs.b)))
}; };
registerKernel(kernelMod); registerKernel(kernelMod);
env2.kernels.push("floormod"); env2.kernels.push("floormod");
@ -82976,7 +82981,7 @@ async function check(instance2, force = false) {
} }
} }
if (instance2.config.backend === "humangl") if (instance2.config.backend === "humangl")
await register(instance2); register(instance2);
const available = Object.keys(engine().registryFactory); const available = Object.keys(engine().registryFactory);
if (instance2.config.debug) if (instance2.config.debug)
log("available backends:", available); log("available backends:", available);
@ -82994,7 +82999,7 @@ async function check(instance2, force = false) {
if (instance2.config.debug) if (instance2.config.debug)
log("wasm path:", instance2.config.wasmPath); log("wasm path:", instance2.config.wasmPath);
if (typeof setWasmPaths !== "undefined") if (typeof setWasmPaths !== "undefined")
await setWasmPaths(instance2.config.wasmPath, instance2.config.wasmPlatformFetch); setWasmPaths(instance2.config.wasmPath, instance2.config.wasmPlatformFetch);
else else
throw new Error("backend error: attempting to use wasm backend but wasm path is not set"); throw new Error("backend error: attempting to use wasm backend but wasm path is not set");
let mt = false; let mt = false;
@ -83421,7 +83426,7 @@ function padInput(input2, inputSize10) {
return final; return final;
} }
function rescaleBody(body4, outputSize2) { function rescaleBody(body4, outputSize2) {
body4.keypoints = body4.keypoints.filter((kpt4) => kpt4 && kpt4.position); body4.keypoints = body4.keypoints.filter((kpt4) => kpt4 == null ? void 0 : kpt4.position);
for (const kpt4 of body4.keypoints) { for (const kpt4 of body4.keypoints) {
kpt4.position = [ kpt4.position = [
kpt4.position[0] * (outputSize2[0] + cache5.padding[2][0] + cache5.padding[2][1]) / outputSize2[0] - cache5.padding[2][0], kpt4.position[0] * (outputSize2[0] + cache5.padding[2][0] + cache5.padding[2][1]) / outputSize2[0] - cache5.padding[2][0],
@ -83460,7 +83465,7 @@ async function load16(config3) {
inputSize8 = 256; inputSize8 = 256;
return model16; return model16;
} }
async function parseSinglePose(res, config3, image2) { function parseSinglePose(res, config3, image2) {
const kpt4 = res[0][0]; const kpt4 = res[0][0];
const keypoints = []; const keypoints = [];
let score = 0; let score = 0;
@ -83498,7 +83503,7 @@ async function parseSinglePose(res, config3, image2) {
bodies.push(body4); bodies.push(body4);
return bodies; return bodies;
} }
async function parseMultiPose(res, config3, image2) { function parseMultiPose(res, config3, image2) {
const bodies = []; const bodies = [];
for (let id = 0; id < res[0].length; id++) { for (let id = 0; id < res[0].length; id++) {
const kpt4 = res[0][id]; const kpt4 = res[0][id];
@ -83557,7 +83562,7 @@ async function predict16(input2, config3) {
t2.res = model16 == null ? void 0 : model16.execute(t2.input); t2.res = model16 == null ? void 0 : model16.execute(t2.input);
cache6.last = now(); cache6.last = now();
const res = await t2.res.array(); const res = await t2.res.array();
cache6.bodies = t2.res.shape[2] === 17 ? await parseSinglePose(res, config3, input2) : await parseMultiPose(res, config3, input2); cache6.bodies = t2.res.shape[2] === 17 ? parseSinglePose(res, config3, input2) : parseMultiPose(res, config3, input2);
for (const body4 of cache6.bodies) { for (const body4 of cache6.bodies) {
rescaleBody(body4, [input2.shape[2] || 1, input2.shape[1] || 1]); rescaleBody(body4, [input2.shape[2] || 1, input2.shape[1] || 1]);
jitter(body4.keypoints); jitter(body4.keypoints);
@ -83995,7 +84000,7 @@ async function predict18(input2, config3) {
const buffers = await Promise.all(res.map((tensor2) => tensor2.buffer())); const buffers = await Promise.all(res.map((tensor2) => tensor2.buffer()));
for (const t2 of res) for (const t2 of res)
dispose(t2); dispose(t2);
const decoded = await decode(buffers[0], buffers[1], buffers[2], buffers[3], config3.body.maxDetected, config3.body.minConfidence); const decoded = decode(buffers[0], buffers[1], buffers[2], buffers[3], config3.body.maxDetected, config3.body.minConfidence);
if (!model18.inputs[0].shape) if (!model18.inputs[0].shape)
return []; return [];
const scaled = scalePoses(decoded, [input2.shape[1], input2.shape[2]], [model18.inputs[0].shape[2], model18.inputs[0].shape[1]]); const scaled = scalePoses(decoded, [input2.shape[1], input2.shape[2]], [model18.inputs[0].shape[2], model18.inputs[0].shape[1]]);
@ -84207,6 +84212,7 @@ async function load20(instance2) {
} }
var instance; var instance;
function validateModel(newInstance, model20, name) { function validateModel(newInstance, model20, name) {
var _a;
if (newInstance) if (newInstance)
instance = newInstance; instance = newInstance;
if (!model20) if (!model20)
@ -84221,7 +84227,7 @@ function validateModel(newInstance, model20, name) {
const missing = []; const missing = [];
const url = model20["modelUrl"]; const url = model20["modelUrl"];
const executor = model20["executor"]; const executor = model20["executor"];
if (executor && executor.graph.nodes) { if ((_a = executor == null ? void 0 : executor.graph) == null ? void 0 : _a.nodes) {
for (const kernel of Object.values(executor.graph.nodes)) { for (const kernel of Object.values(executor.graph.nodes)) {
const op2 = kernel.op.toLowerCase(); const op2 = kernel.op.toLowerCase();
if (!ops.includes(op2)) if (!ops.includes(op2))
@ -84321,7 +84327,7 @@ async function loadModel(modelPath) {
log("error saving model:", modelUrl, err); log("error saving model:", modelUrl, err);
} }
} }
validateModel(null, model20, `${modelPath}`); validateModel(null, model20, `${modelPath || ""}`);
return model20; return model20;
} }
@ -84477,6 +84483,7 @@ var options3 = {
// src/draw/face.ts // src/draw/face.ts
var opt; var opt;
function drawLabels(f, ctx) { function drawLabels(f, ctx) {
var _a, _b;
if (opt.drawLabels) { if (opt.drawLabels) {
const labels2 = []; const labels2 = [];
labels2.push(`face: ${Math.trunc(100 * f.score)}%`); labels2.push(`face: ${Math.trunc(100 * f.score)}%`);
@ -84496,7 +84503,7 @@ function drawLabels(f, ctx) {
emotion2.length = 3; emotion2.length = 3;
labels2.push(emotion2.join(" ")); labels2.push(emotion2.join(" "));
} }
if (f.rotation && f.rotation.angle && f.rotation.gaze) { if (((_a = f.rotation) == null ? void 0 : _a.angle) && ((_b = f.rotation) == null ? void 0 : _b.gaze)) {
if (f.rotation.angle.roll) if (f.rotation.angle.roll)
labels2.push(`roll: ${rad2deg(f.rotation.angle.roll)}\xB0 yaw:${rad2deg(f.rotation.angle.yaw)}\xB0 pitch:${rad2deg(f.rotation.angle.pitch)}\xB0`); labels2.push(`roll: ${rad2deg(f.rotation.angle.roll)}\xB0 yaw:${rad2deg(f.rotation.angle.yaw)}\xB0 pitch:${rad2deg(f.rotation.angle.pitch)}\xB0`);
if (f.rotation.gaze.bearing) if (f.rotation.gaze.bearing)
@ -84518,7 +84525,8 @@ function drawLabels(f, ctx) {
} }
} }
function drawIrisElipse(f, ctx) { function drawIrisElipse(f, ctx) {
if (f.annotations && f.annotations.leftEyeIris && f.annotations.leftEyeIris[0]) { var _a, _b, _c, _d;
if (((_a = f.annotations) == null ? void 0 : _a.leftEyeIris) && ((_b = f.annotations) == null ? void 0 : _b.leftEyeIris[0])) {
ctx.strokeStyle = opt.useDepth ? "rgba(255, 200, 255, 0.3)" : opt.color; ctx.strokeStyle = opt.useDepth ? "rgba(255, 200, 255, 0.3)" : opt.color;
ctx.beginPath(); ctx.beginPath();
const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2; const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;
@ -84530,7 +84538,7 @@ function drawIrisElipse(f, ctx) {
ctx.fill(); ctx.fill();
} }
} }
if (f.annotations && f.annotations.rightEyeIris && f.annotations.rightEyeIris[0]) { if (((_c = f.annotations) == null ? void 0 : _c.rightEyeIris) && ((_d = f.annotations) == null ? void 0 : _d.rightEyeIris[0])) {
ctx.strokeStyle = opt.useDepth ? "rgba(255, 200, 255, 0.3)" : opt.color; ctx.strokeStyle = opt.useDepth ? "rgba(255, 200, 255, 0.3)" : opt.color;
ctx.beginPath(); ctx.beginPath();
const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2; const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;
@ -84614,7 +84622,7 @@ function drawFaceBoxes(f, ctx) {
rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], opt); rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], opt);
} }
} }
async function face(inCanvas2, result, drawOptions) { function face(inCanvas2, result, drawOptions) {
opt = mergeDeep(options3, drawOptions); opt = mergeDeep(options3, drawOptions);
if (!result || !inCanvas2) if (!result || !inCanvas2)
return; return;
@ -84637,7 +84645,7 @@ async function face(inCanvas2, result, drawOptions) {
} }
// src/draw/body.ts // src/draw/body.ts
async function body(inCanvas2, result, drawOptions) { function body(inCanvas2, result, drawOptions) {
const localOptions = mergeDeep(options3, drawOptions); const localOptions = mergeDeep(options3, drawOptions);
if (!result || !inCanvas2) if (!result || !inCanvas2)
return; return;
@ -84688,7 +84696,7 @@ async function body(inCanvas2, result, drawOptions) {
} }
// src/draw/hand.ts // src/draw/hand.ts
async function hand(inCanvas2, result, drawOptions) { function hand(inCanvas2, result, drawOptions) {
const localOptions = mergeDeep(options3, drawOptions); const localOptions = mergeDeep(options3, drawOptions);
if (!result || !inCanvas2) if (!result || !inCanvas2)
return; return;
@ -84760,7 +84768,7 @@ async function hand(inCanvas2, result, drawOptions) {
} }
// src/draw/object.ts // src/draw/object.ts
async function object(inCanvas2, result, drawOptions) { function object(inCanvas2, result, drawOptions) {
const localOptions = mergeDeep(options3, drawOptions); const localOptions = mergeDeep(options3, drawOptions);
if (!result || !inCanvas2) if (!result || !inCanvas2)
return; return;
@ -84789,7 +84797,7 @@ async function object(inCanvas2, result, drawOptions) {
} }
// src/draw/gesture.ts // src/draw/gesture.ts
async function gesture(inCanvas2, result, drawOptions) { function gesture(inCanvas2, result, drawOptions) {
const localOptions = mergeDeep(options3, drawOptions); const localOptions = mergeDeep(options3, drawOptions);
if (!result || !inCanvas2) if (!result || !inCanvas2)
return; return;
@ -84821,7 +84829,7 @@ async function gesture(inCanvas2, result, drawOptions) {
// src/draw/draw.ts // src/draw/draw.ts
var drawTime = 0; var drawTime = 0;
async function person(inCanvas2, result, drawOptions) { function person(inCanvas2, result, drawOptions) {
const localOptions = mergeDeep(options3, drawOptions); const localOptions = mergeDeep(options3, drawOptions);
if (!result || !inCanvas2) if (!result || !inCanvas2)
return; return;
@ -84848,7 +84856,7 @@ async function person(inCanvas2, result, drawOptions) {
} }
} }
} }
async function canvas2(input2, output) { function canvas2(input2, output) {
if (!input2 || !output) if (!input2 || !output)
return; return;
const ctx = getCanvasContext(output); const ctx = getCanvasContext(output);
@ -85008,7 +85016,7 @@ var calculateFaceAngle = (face4, imageSize) => {
// src/face/face.ts // src/face/face.ts
var detectFace = async (instance2, input2) => { var detectFace = async (instance2, input2) => {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w; var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A, _B, _C;
let timeStamp = now(); let timeStamp = now();
let ageRes; let ageRes;
let gearRes; let gearRes;
@ -85151,8 +85159,8 @@ var detectFace = async (instance2, input2) => {
} }
if (!((_v = instance2.config.face.iris) == null ? void 0 : _v.enabled)) { if (!((_v = instance2.config.face.iris) == null ? void 0 : _v.enabled)) {
} }
const irisSize = faces[i2].annotations && faces[i2].annotations.leftEyeIris && faces[i2].annotations.leftEyeIris[0] && faces[i2].annotations.rightEyeIris && faces[i2].annotations.rightEyeIris[0] && faces[i2].annotations.leftEyeIris.length > 0 && faces[i2].annotations.rightEyeIris.length > 0 && faces[i2].annotations.leftEyeIris[0] !== null && faces[i2].annotations.rightEyeIris[0] !== null ? Math.max(Math.abs(faces[i2].annotations.leftEyeIris[3][0] - faces[i2].annotations.leftEyeIris[1][0]), Math.abs(faces[i2].annotations.rightEyeIris[4][1] - faces[i2].annotations.rightEyeIris[2][1])) / input2.shape[2] : 0; const irisSize = ((_y = (_x = (_w = faces[i2]) == null ? void 0 : _w.annotations) == null ? void 0 : _x.leftEyeIris) == null ? void 0 : _y[0]) && ((_B = (_A = (_z = faces[i2]) == null ? void 0 : _z.annotations) == null ? void 0 : _A.rightEyeIris) == null ? void 0 : _B[0]) && faces[i2].annotations.leftEyeIris.length > 0 && faces[i2].annotations.rightEyeIris.length > 0 && faces[i2].annotations.leftEyeIris[0] !== null && faces[i2].annotations.rightEyeIris[0] !== null ? Math.max(Math.abs(faces[i2].annotations.leftEyeIris[3][0] - faces[i2].annotations.leftEyeIris[1][0]), Math.abs(faces[i2].annotations.rightEyeIris[4][1] - faces[i2].annotations.rightEyeIris[2][1])) / input2.shape[2] : 0;
const tensor2 = ((_w = instance2.config.face.detector) == null ? void 0 : _w.return) ? squeeze(faces[i2].tensor) : null; const tensor2 = ((_C = instance2.config.face.detector) == null ? void 0 : _C.return) ? squeeze(faces[i2].tensor) : null;
dispose(faces[i2].tensor); dispose(faces[i2].tensor);
if (faces[i2].tensor) if (faces[i2].tensor)
delete faces[i2].tensor; delete faces[i2].tensor;
@ -85324,7 +85332,7 @@ var hand2 = (res) => {
var bufferedResult = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null }; var bufferedResult = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };
var interpolateTime = 0; var interpolateTime = 0;
function calc2(newResult, config3) { function calc2(newResult, config3) {
var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n; var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q;
const t0 = now(); const t0 = now();
if (!newResult) if (!newResult)
return { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null }; return { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };
@ -85398,7 +85406,7 @@ function calc2(newResult, config3) {
annotations2 = bufferedResult.hand[i2].annotations; annotations2 = bufferedResult.hand[i2].annotations;
} else if (newResult.hand[i2].annotations) { } else if (newResult.hand[i2].annotations) {
for (const key of Object.keys(newResult.hand[i2].annotations)) { for (const key of Object.keys(newResult.hand[i2].annotations)) {
annotations2[key] = newResult.hand[i2].annotations[key] && newResult.hand[i2].annotations[key][0] ? newResult.hand[i2].annotations[key].map((val, j) => val.map((coord, k) => ((bufferedFactor - 1) * bufferedResult.hand[i2].annotations[key][j][k] + coord) / bufferedFactor)) : null; annotations2[key] = ((_f = (_e = (_d = newResult.hand[i2]) == null ? void 0 : _d.annotations) == null ? void 0 : _e[key]) == null ? void 0 : _f[0]) ? newResult.hand[i2].annotations[key].map((val, j) => val.map((coord, k) => ((bufferedFactor - 1) * bufferedResult.hand[i2].annotations[key][j][k] + coord) / bufferedFactor)) : null;
} }
} }
bufferedResult.hand[i2] = { ...newResult.hand[i2], box, boxRaw, keypoints, annotations: annotations2 }; bufferedResult.hand[i2] = { ...newResult.hand[i2], box, boxRaw, keypoints, annotations: annotations2 };
@ -85412,15 +85420,15 @@ function calc2(newResult, config3) {
const boxRaw = newResult.face[i2].boxRaw.map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i2].boxRaw[j] + b) / bufferedFactor); const boxRaw = newResult.face[i2].boxRaw.map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i2].boxRaw[j] + b) / bufferedFactor);
if (newResult.face[i2].rotation) { if (newResult.face[i2].rotation) {
const rotation = { matrix: [0, 0, 0, 0, 0, 0, 0, 0, 0], angle: { roll: 0, yaw: 0, pitch: 0 }, gaze: { bearing: 0, strength: 0 } }; const rotation = { matrix: [0, 0, 0, 0, 0, 0, 0, 0, 0], angle: { roll: 0, yaw: 0, pitch: 0 }, gaze: { bearing: 0, strength: 0 } };
rotation.matrix = (_d = newResult.face[i2].rotation) == null ? void 0 : _d.matrix; rotation.matrix = (_g = newResult.face[i2].rotation) == null ? void 0 : _g.matrix;
rotation.angle = { rotation.angle = {
roll: ((bufferedFactor - 1) * (((_e = bufferedResult.face[i2].rotation) == null ? void 0 : _e.angle.roll) || 0) + (((_f = newResult.face[i2].rotation) == null ? void 0 : _f.angle.roll) || 0)) / bufferedFactor, roll: ((bufferedFactor - 1) * (((_h = bufferedResult.face[i2].rotation) == null ? void 0 : _h.angle.roll) || 0) + (((_i = newResult.face[i2].rotation) == null ? void 0 : _i.angle.roll) || 0)) / bufferedFactor,
yaw: ((bufferedFactor - 1) * (((_g = bufferedResult.face[i2].rotation) == null ? void 0 : _g.angle.yaw) || 0) + (((_h = newResult.face[i2].rotation) == null ? void 0 : _h.angle.yaw) || 0)) / bufferedFactor, yaw: ((bufferedFactor - 1) * (((_j = bufferedResult.face[i2].rotation) == null ? void 0 : _j.angle.yaw) || 0) + (((_k = newResult.face[i2].rotation) == null ? void 0 : _k.angle.yaw) || 0)) / bufferedFactor,
pitch: ((bufferedFactor - 1) * (((_i = bufferedResult.face[i2].rotation) == null ? void 0 : _i.angle.pitch) || 0) + (((_j = newResult.face[i2].rotation) == null ? void 0 : _j.angle.pitch) || 0)) / bufferedFactor pitch: ((bufferedFactor - 1) * (((_l = bufferedResult.face[i2].rotation) == null ? void 0 : _l.angle.pitch) || 0) + (((_m = newResult.face[i2].rotation) == null ? void 0 : _m.angle.pitch) || 0)) / bufferedFactor
}; };
rotation.gaze = { rotation.gaze = {
bearing: ((bufferedFactor - 1) * (((_k = bufferedResult.face[i2].rotation) == null ? void 0 : _k.gaze.bearing) || 0) + (((_l = newResult.face[i2].rotation) == null ? void 0 : _l.gaze.bearing) || 0)) / bufferedFactor, bearing: ((bufferedFactor - 1) * (((_n = bufferedResult.face[i2].rotation) == null ? void 0 : _n.gaze.bearing) || 0) + (((_o = newResult.face[i2].rotation) == null ? void 0 : _o.gaze.bearing) || 0)) / bufferedFactor,
strength: ((bufferedFactor - 1) * (((_m = bufferedResult.face[i2].rotation) == null ? void 0 : _m.gaze.strength) || 0) + (((_n = newResult.face[i2].rotation) == null ? void 0 : _n.gaze.strength) || 0)) / bufferedFactor strength: ((bufferedFactor - 1) * (((_p = bufferedResult.face[i2].rotation) == null ? void 0 : _p.gaze.strength) || 0) + (((_q = newResult.face[i2].rotation) == null ? void 0 : _q.gaze.strength) || 0)) / bufferedFactor
}; };
bufferedResult.face[i2] = { ...newResult.face[i2], rotation, box, boxRaw }; bufferedResult.face[i2] = { ...newResult.face[i2], rotation, box, boxRaw };
} }
@ -85554,7 +85562,7 @@ function join2(faces, bodies, hands, gestures, shape) {
const minX = Math.min(...x); const minX = Math.min(...x);
const minY = Math.min(...y); const minY = Math.min(...y);
person2.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY]; person2.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY];
if (shape && shape[1] && shape[2]) if ((shape == null ? void 0 : shape[1]) && (shape == null ? void 0 : shape[2]))
person2.boxRaw = [person2.box[0] / shape[2], person2.box[1] / shape[1], person2.box[2] / shape[2], person2.box[3] / shape[1]]; person2.boxRaw = [person2.box[0] / shape[2], person2.box[1] / shape[1], person2.box[2] / shape[2], person2.box[3] / shape[1]];
persons.push(person2); persons.push(person2);
} }
@ -86358,7 +86366,7 @@ async function warmupNode(instance2) {
let res; let res;
if ("node" in tfjs_esm_exports && getBackend() === "tensorflow") { if ("node" in tfjs_esm_exports && getBackend() === "tensorflow") {
const data = (void 0).decodeJpeg(img); const data = (void 0).decodeJpeg(img);
const expanded = data.expandDims(0); const expanded = expandDims(data, 0);
instance2.tf.dispose(data); instance2.tf.dispose(data);
res = await instance2.detect(expanded, instance2.config); res = await instance2.detect(expanded, instance2.config);
instance2.tf.dispose(expanded); instance2.tf.dispose(expanded);
@ -86379,6 +86387,7 @@ async function runInference(instance2) {
return res; return res;
} }
async function runCompile(allModels) { async function runCompile(allModels) {
var _a, _b, _c, _d;
if (!env().flagRegistry.ENGINE_COMPILE_ONLY) if (!env().flagRegistry.ENGINE_COMPILE_ONLY)
return; return;
const backendType = getBackend(); const backendType = getBackend();
@ -86390,8 +86399,8 @@ async function runCompile(allModels) {
const numTensorsStart = engine().state.numTensors; const numTensorsStart = engine().state.numTensors;
const compiledModels = []; const compiledModels = [];
for (const [modelName, model20] of Object.entries(allModels).filter(([key, val]) => key !== null && val !== null)) { for (const [modelName, model20] of Object.entries(allModels).filter(([key, val]) => key !== null && val !== null)) {
const shape = model20.inputs && model20.inputs[0] && model20.inputs[0].shape ? [...model20.inputs[0].shape] : [1, 64, 64, 3]; const shape = ((_b = (_a = model20.inputs) == null ? void 0 : _a[0]) == null ? void 0 : _b.shape) ? [...model20.inputs[0].shape] : [1, 64, 64, 3];
const dtype = model20.inputs && model20.inputs[0] && model20.inputs[0].dtype ? model20.inputs[0].dtype : "float32"; const dtype = ((_d = (_c = model20.inputs) == null ? void 0 : _c[0]) == null ? void 0 : _d.dtype) ? model20.inputs[0].dtype : "float32";
for (let dim = 0; dim < shape.length; dim++) { for (let dim = 0; dim < shape.length; dim++) {
if (shape[dim] === -1) if (shape[dim] === -1)
shape[dim] = dim === 0 ? 1 : 64; shape[dim] = dim === 0 ? 1 : 64;
@ -86486,7 +86495,8 @@ var Human = class {
__publicField(this, "distance", distance); __publicField(this, "distance", distance);
__publicField(this, "match", match2); __publicField(this, "match", match2);
__publicField(this, "emit", (event) => { __publicField(this, "emit", (event) => {
if (this.events && this.events.dispatchEvent) var _a;
if ((_a = this.events) == null ? void 0 : _a.dispatchEvent)
this.events.dispatchEvent(new Event(event)); this.events.dispatchEvent(new Event(event));
}); });
this.env = env2; this.env = env2;

4
dist/human.esm.js.map vendored
View File

File diff suppressed because one or more lines are too long

570
dist/human.js vendored
View File

File diff suppressed because one or more lines are too long

14
dist/human.node-gpu.d.ts vendored
View File

@ -28,7 +28,7 @@ declare interface ArrayMap {
export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu']; export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];
/** draw detected bodies */ /** draw detected bodies */
declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): void;
export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose; export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose;
@ -140,7 +140,7 @@ declare function browserFiles(files: File[]): IOHandler;
declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler; declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;
/** draw processed canvas */ /** draw processed canvas */
declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): Promise<void>; declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): void;
/** /**
* Concatenate a number of ArrayBuffers into one. * Concatenate a number of ArrayBuffers into one.
@ -509,7 +509,7 @@ export declare type Events = 'create' | 'load' | 'image' | 'result' | 'warmup' |
export declare type ExternalCanvas = typeof env.Canvas; export declare type ExternalCanvas = typeof env.Canvas;
/** draw detected faces */ /** draw detected faces */
declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): void;
/** Anti-spoofing part of face configuration */ /** Anti-spoofing part of face configuration */
export declare interface FaceAntiSpoofConfig extends GenericConfig { export declare interface FaceAntiSpoofConfig extends GenericConfig {
@ -780,7 +780,7 @@ export declare interface GenericConfig {
} }
/** draw detected gestures */ /** draw detected gestures */
declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): void;
/** Controlls gesture detection */ /** Controlls gesture detection */
export declare interface GestureConfig { export declare interface GestureConfig {
@ -1038,7 +1038,7 @@ export declare class GraphModel<ModelURL extends Url = string | io.IOHandler> im
} }
/** draw detected hands */ /** draw detected hands */
declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all hand detection specific options */ /** Configures all hand detection specific options */
export declare interface HandConfig extends GenericConfig { export declare interface HandConfig extends GenericConfig {
@ -2022,7 +2022,7 @@ declare type NamedTensorsMap = {
declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64'; declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64';
/** draw detected objects */ /** draw detected objects */
declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all object detection specific options */ /** Configures all object detection specific options */
export declare interface ObjectConfig extends GenericConfig { export declare interface ObjectConfig extends GenericConfig {
@ -2065,7 +2065,7 @@ declare type OnProgressCallback = (fraction: number) => void;
declare const options: DrawOptions; declare const options: DrawOptions;
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): void;
/** Person getter /** Person getter
* - Triggers combining all individual results into a virtual person object * - Triggers combining all individual results into a virtual person object

20
dist/human.node-gpu.js vendored
View File

File diff suppressed because one or more lines are too long

14
dist/human.node-wasm.d.ts vendored
View File

@ -28,7 +28,7 @@ declare interface ArrayMap {
export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu']; export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];
/** draw detected bodies */ /** draw detected bodies */
declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): void;
export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose; export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose;
@ -140,7 +140,7 @@ declare function browserFiles(files: File[]): IOHandler;
declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler; declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;
/** draw processed canvas */ /** draw processed canvas */
declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): Promise<void>; declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): void;
/** /**
* Concatenate a number of ArrayBuffers into one. * Concatenate a number of ArrayBuffers into one.
@ -509,7 +509,7 @@ export declare type Events = 'create' | 'load' | 'image' | 'result' | 'warmup' |
export declare type ExternalCanvas = typeof env.Canvas; export declare type ExternalCanvas = typeof env.Canvas;
/** draw detected faces */ /** draw detected faces */
declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): void;
/** Anti-spoofing part of face configuration */ /** Anti-spoofing part of face configuration */
export declare interface FaceAntiSpoofConfig extends GenericConfig { export declare interface FaceAntiSpoofConfig extends GenericConfig {
@ -780,7 +780,7 @@ export declare interface GenericConfig {
} }
/** draw detected gestures */ /** draw detected gestures */
declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): void;
/** Controlls gesture detection */ /** Controlls gesture detection */
export declare interface GestureConfig { export declare interface GestureConfig {
@ -1038,7 +1038,7 @@ export declare class GraphModel<ModelURL extends Url = string | io.IOHandler> im
} }
/** draw detected hands */ /** draw detected hands */
declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all hand detection specific options */ /** Configures all hand detection specific options */
export declare interface HandConfig extends GenericConfig { export declare interface HandConfig extends GenericConfig {
@ -2022,7 +2022,7 @@ declare type NamedTensorsMap = {
declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64'; declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64';
/** draw detected objects */ /** draw detected objects */
declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all object detection specific options */ /** Configures all object detection specific options */
export declare interface ObjectConfig extends GenericConfig { export declare interface ObjectConfig extends GenericConfig {
@ -2065,7 +2065,7 @@ declare type OnProgressCallback = (fraction: number) => void;
declare const options: DrawOptions; declare const options: DrawOptions;
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): void;
/** Person getter /** Person getter
* - Triggers combining all individual results into a virtual person object * - Triggers combining all individual results into a virtual person object

20
dist/human.node-wasm.js vendored
View File

File diff suppressed because one or more lines are too long

14
dist/human.node.d.ts vendored
View File

@ -28,7 +28,7 @@ declare interface ArrayMap {
export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu']; export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];
/** draw detected bodies */ /** draw detected bodies */
declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): void;
export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose; export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose;
@ -140,7 +140,7 @@ declare function browserFiles(files: File[]): IOHandler;
declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler; declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;
/** draw processed canvas */ /** draw processed canvas */
declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): Promise<void>; declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): void;
/** /**
* Concatenate a number of ArrayBuffers into one. * Concatenate a number of ArrayBuffers into one.
@ -509,7 +509,7 @@ export declare type Events = 'create' | 'load' | 'image' | 'result' | 'warmup' |
export declare type ExternalCanvas = typeof env.Canvas; export declare type ExternalCanvas = typeof env.Canvas;
/** draw detected faces */ /** draw detected faces */
declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): void;
/** Anti-spoofing part of face configuration */ /** Anti-spoofing part of face configuration */
export declare interface FaceAntiSpoofConfig extends GenericConfig { export declare interface FaceAntiSpoofConfig extends GenericConfig {
@ -780,7 +780,7 @@ export declare interface GenericConfig {
} }
/** draw detected gestures */ /** draw detected gestures */
declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): void;
/** Controlls gesture detection */ /** Controlls gesture detection */
export declare interface GestureConfig { export declare interface GestureConfig {
@ -1038,7 +1038,7 @@ export declare class GraphModel<ModelURL extends Url = string | io.IOHandler> im
} }
/** draw detected hands */ /** draw detected hands */
declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all hand detection specific options */ /** Configures all hand detection specific options */
export declare interface HandConfig extends GenericConfig { export declare interface HandConfig extends GenericConfig {
@ -2022,7 +2022,7 @@ declare type NamedTensorsMap = {
declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64'; declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64';
/** draw detected objects */ /** draw detected objects */
declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all object detection specific options */ /** Configures all object detection specific options */
export declare interface ObjectConfig extends GenericConfig { export declare interface ObjectConfig extends GenericConfig {
@ -2065,7 +2065,7 @@ declare type OnProgressCallback = (fraction: number) => void;
declare const options: DrawOptions; declare const options: DrawOptions;
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): void;
/** Person getter /** Person getter
* - Triggers combining all individual results into a virtual person object * - Triggers combining all individual results into a virtual person object

20
dist/human.node.js vendored
View File

File diff suppressed because one or more lines are too long

8
src/body/blazepose.ts
View File

@ -38,7 +38,7 @@ export async function loadDetect(config: Config): Promise<GraphModel> {
inputSize.detector[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0; inputSize.detector[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;
inputSize.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0; inputSize.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;
} else if (config.debug && models.detector) log('cached model:', models.detector['modelUrl']); } else if (config.debug && models.detector) log('cached model:', models.detector['modelUrl']);
await detect.createAnchors(); detect.createAnchors();
return models.detector as GraphModel; return models.detector as GraphModel;
} }
@ -59,7 +59,7 @@ export async function load(config: Config): Promise<[GraphModel | null, GraphMod
return [models.detector, models.landmarks]; return [models.detector, models.landmarks];
} }
async function prepareImage(input: Tensor, size: number): Promise<Tensor> { function prepareImage(input: Tensor, size: number): Tensor {
const t: Record<string, Tensor> = {}; const t: Record<string, Tensor> = {};
if (!input.shape || !input.shape[1] || !input.shape[2]) return input; if (!input.shape || !input.shape[1] || !input.shape[2]) return input;
let final: Tensor; let final: Tensor;
@ -120,7 +120,7 @@ function rescaleKeypoints(keypoints: BodyKeypoint[], outputSize: [number, number
return keypoints; return keypoints;
} }
async function fixKeypoints(keypoints: BodyKeypoint[]) { function fixKeypoints(keypoints: BodyKeypoint[]) {
// palm z-coord is incorrect around near-zero so we approximate it // palm z-coord is incorrect around near-zero so we approximate it
const leftPalm = keypoints.find((k) => k.part === 'leftPalm') as BodyKeypoint; const leftPalm = keypoints.find((k) => k.part === 'leftPalm') as BodyKeypoint;
const leftWrist = keypoints.find((k) => k.part === 'leftWrist') as BodyKeypoint; const leftWrist = keypoints.find((k) => k.part === 'leftWrist') as BodyKeypoint;
@ -220,7 +220,7 @@ export async function predict(input: Tensor, config: Config): Promise<BodyResult
const boxes = await detectBoxes(t.detector, config, outputSize); const boxes = await detectBoxes(t.detector, config, outputSize);
} }
*/ */
t.landmarks = await prepareImage(input, 256); // padded and resized t.landmarks = prepareImage(input, 256); // padded and resized
cache = await detectLandmarks(t.landmarks, config, outputSize); cache = await detectLandmarks(t.landmarks, config, outputSize);
/* /*
cropBox = [0, 0, 1, 1]; // reset crop coordinates cropBox = [0, 0, 1, 1]; // reset crop coordinates

4
src/body/blazeposedetector.ts
View File

@ -10,7 +10,7 @@ let anchorTensor: { x, y };
const numLayers = 5; const numLayers = 5;
const strides = [8, 16, 32, 32, 32]; const strides = [8, 16, 32, 32, 32];
export async function createAnchors() { export function createAnchors() {
const anchors: { x: number, y: number }[] = []; const anchors: { x: number, y: number }[] = [];
let layerId = 0; let layerId = 0;
while (layerId < numLayers) { while (layerId < numLayers) {
@ -62,7 +62,7 @@ export async function decode(boxesTensor: Tensor, logitsTensor: Tensor, config:
const i = (await t.argmax.data())[0]; const i = (await t.argmax.data())[0];
const scores = await t.scores.data(); const scores = await t.scores.data();
const detected: { box: Box, boxRaw: Box, score: number }[] = []; const detected: { box: Box, boxRaw: Box, score: number }[] = [];
const minScore = (config.body['detector'] && config.body['detector'].minConfidence) ? config.body['detector'].minConfidence : 0; const minScore = config.body?.['detector']?.minConfidence || 0;
if (scores[i] >= minScore) { if (scores[i] >= minScore) {
const boxes = await t.boxes.array(); const boxes = await t.boxes.array();
const boxRaw: Box = boxes[i]; const boxRaw: Box = boxes[i];

8
src/body/movenet.ts
View File

@ -42,7 +42,7 @@ export async function load(config: Config): Promise<GraphModel> {
return model; return model;
} }
async function parseSinglePose(res, config, image) { function parseSinglePose(res, config, image) {
const kpt = res[0][0]; const kpt = res[0][0];
const keypoints: BodyKeypoint[] = []; const keypoints: BodyKeypoint[] = [];
let score = 0; let score = 0;
@ -80,7 +80,7 @@ async function parseSinglePose(res, config, image) {
return bodies; return bodies;
} }
async function parseMultiPose(res, config, image) { function parseMultiPose(res, config, image) {
const bodies: BodyResult[] = []; const bodies: BodyResult[] = [];
for (let id = 0; id < res[0].length; id++) { for (let id = 0; id < res[0].length; id++) {
const kpt = res[0][id]; const kpt = res[0][id];
@ -174,8 +174,8 @@ export async function predict(input: Tensor, config: Config): Promise<BodyResult
cache.last = now(); cache.last = now();
const res = await t.res.array(); const res = await t.res.array();
cache.bodies = (t.res.shape[2] === 17) cache.bodies = (t.res.shape[2] === 17)
? await parseSinglePose(res, config, input) ? parseSinglePose(res, config, input)
: await parseMultiPose(res, config, input); : parseMultiPose(res, config, input);
for (const body of cache.bodies) { for (const body of cache.bodies) {
fix.rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]); fix.rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);
fix.jitter(body.keypoints); fix.jitter(body.keypoints);

2
src/body/movenetfix.ts
View File

@ -90,7 +90,7 @@ export function padInput(input: Tensor, inputSize: number): Tensor {
} }
export function rescaleBody(body: BodyResult, outputSize: [number, number]): BodyResult { export function rescaleBody(body: BodyResult, outputSize: [number, number]): BodyResult {
body.keypoints = body.keypoints.filter((kpt) => kpt && kpt.position); // filter invalid keypoints body.keypoints = body.keypoints.filter((kpt) => kpt?.position); // filter invalid keypoints
for (const kpt of body.keypoints) { for (const kpt of body.keypoints) {
kpt.position = [ kpt.position = [
kpt.position[0] * (outputSize[0] + cache.padding[2][0] + cache.padding[2][1]) / outputSize[0] - cache.padding[2][0], kpt.position[0] * (outputSize[0] + cache.padding[2][0] + cache.padding[2][1]) / outputSize[0] - cache.padding[2][0],

8
src/body/posenet.ts
View File

@ -19,7 +19,7 @@ const localMaximumRadius = 1;
const outputStride = 16; const outputStride = 16;
const squaredNmsRadius = 50 ** 2; const squaredNmsRadius = 50 ** 2;
function traverse(edgeId, sourceKeypoint, targetId, scores, offsets, displacements, offsetRefineStep = 2) { function traverse(edgeId: number, sourceKeypoint, targetId, scores, offsets, displacements, offsetRefineStep = 2) {
const getDisplacement = (point) => ({ const getDisplacement = (point) => ({
y: displacements.get(point.y, point.x, edgeId), y: displacements.get(point.y, point.x, edgeId),
x: displacements.get(point.y, point.x, (displacements.shape[2] / 2) + edgeId), x: displacements.get(point.y, point.x, (displacements.shape[2] / 2) + edgeId),
@ -81,8 +81,8 @@ export function decodePose(root, scores, offsets, displacementsFwd, displacement
return keypoints; return keypoints;
} }
function scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores) { function scoreIsMaximumInLocalWindow(keypointId, score: number, heatmapY: number, heatmapX: number, scores) {
const [height, width] = scores.shape; const [height, width]: [number, number] = scores.shape;
let localMaximum = true; let localMaximum = true;
const yStart = Math.max(heatmapY - localMaximumRadius, 0); const yStart = Math.max(heatmapY - localMaximumRadius, 0);
const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height); const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);
@ -172,7 +172,7 @@ export async function predict(input: Tensor, config: Config): Promise<BodyResult
const buffers = await Promise.all(res.map((tensor: Tensor) => tensor.buffer())); const buffers = await Promise.all(res.map((tensor: Tensor) => tensor.buffer()));
for (const t of res) tf.dispose(t); for (const t of res) tf.dispose(t);
const decoded = await decode(buffers[0], buffers[1], buffers[2], buffers[3], config.body.maxDetected, config.body.minConfidence); const decoded = decode(buffers[0], buffers[1], buffers[2], buffers[3], config.body.maxDetected, config.body.minConfidence);
if (!model.inputs[0].shape) return []; if (!model.inputs[0].shape) return [];
const scaled = utils.scalePoses(decoded, [input.shape[1], input.shape[2]], [model.inputs[0].shape[2], model.inputs[0].shape[1]]); const scaled = utils.scalePoses(decoded, [input.shape[1], input.shape[2]], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);
return scaled; return scaled;

6
src/body/posenetutils.ts
View File

@ -154,14 +154,14 @@ export class MaxHeap {
} }
} }
export function getOffsetPoint(y, x, keypoint, offsets) { export function getOffsetPoint(y, x, keypoint: number, offsets) {
return { return {
y: offsets.get(y, x, keypoint), y: offsets.get(y, x, keypoint),
x: offsets.get(y, x, keypoint + count), x: offsets.get(y, x, keypoint + count),
}; };
} }
export function getImageCoords(part, outputStride, offsets) { export function getImageCoords(part, outputStride: number, offsets) {
const { heatmapY, heatmapX, id: keypoint } = part; const { heatmapY, heatmapX, id: keypoint } = part;
const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets); const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);
return { return {
@ -190,7 +190,7 @@ export function squaredDistance(y1, x1, y2, x2) {
return dy * dy + dx * dx; return dy * dy + dx * dx;
} }
export function addVectors(a, b) { export function addVectors(a: { x: number, y: number }, b: { x: number, y: number }) {
return { x: a.x + b.x, y: a.y + b.y }; return { x: a.x + b.x, y: a.y + b.y };
} }

4
src/draw/body.ts
View File

@ -5,8 +5,8 @@ import type { BodyResult } from '../result';
import type { AnyCanvas, DrawOptions } from '../exports'; import type { AnyCanvas, DrawOptions } from '../exports';
/** draw detected bodies */ /** draw detected bodies */
export async function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>) { export function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>) {
const localOptions = mergeDeep(options, drawOptions); const localOptions: DrawOptions = mergeDeep(options, drawOptions);
if (!result || !inCanvas) return; if (!result || !inCanvas) return;
const ctx = getCanvasContext(inCanvas); const ctx = getCanvasContext(inCanvas);
if (!ctx) return; if (!ctx) return;

6
src/draw/draw.ts
View File

@ -24,8 +24,8 @@ export { object } from './object';
export { gesture } from './gesture'; export { gesture } from './gesture';
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
export async function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>) { export function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>) {
const localOptions = mergeDeep(options, drawOptions); const localOptions: DrawOptions = mergeDeep(options, drawOptions);
if (!result || !inCanvas) return; if (!result || !inCanvas) return;
const ctx = getCanvasContext(inCanvas); const ctx = getCanvasContext(inCanvas);
if (!ctx) return; if (!ctx) return;
@ -52,7 +52,7 @@ export async function person(inCanvas: AnyCanvas, result: PersonResult[], drawOp
} }
/** draw processed canvas */ /** draw processed canvas */
export async function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) { export function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) {
if (!input || !output) return; if (!input || !output) return;
const ctx = getCanvasContext(output); const ctx = getCanvasContext(output);
if (!ctx) return; if (!ctx) return;

8
src/draw/face.ts
View File

@ -23,7 +23,7 @@ function drawLabels(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanv
if (emotion.length > 3) emotion.length = 3; if (emotion.length > 3) emotion.length = 3;
labels.push(emotion.join(' ')); labels.push(emotion.join(' '));
} }
if (f.rotation && f.rotation.angle && f.rotation.gaze) { if (f.rotation?.angle && f.rotation?.gaze) {
if (f.rotation.angle.roll) labels.push(`roll: ${rad2deg(f.rotation.angle.roll)}° yaw:${rad2deg(f.rotation.angle.yaw)}° pitch:${rad2deg(f.rotation.angle.pitch)}°`); if (f.rotation.angle.roll) labels.push(`roll: ${rad2deg(f.rotation.angle.roll)}° yaw:${rad2deg(f.rotation.angle.yaw)}° pitch:${rad2deg(f.rotation.angle.pitch)}°`);
if (f.rotation.gaze.bearing) labels.push(`gaze: ${rad2deg(f.rotation.gaze.bearing)}°`); if (f.rotation.gaze.bearing) labels.push(`gaze: ${rad2deg(f.rotation.gaze.bearing)}°`);
} }
@ -44,7 +44,7 @@ function drawLabels(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanv
function drawIrisElipse(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) { function drawIrisElipse(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {
// iris: array[center, left, top, right, bottom] // iris: array[center, left, top, right, bottom]
if (f.annotations && f.annotations.leftEyeIris && f.annotations.leftEyeIris[0]) { if (f.annotations?.leftEyeIris && f.annotations?.leftEyeIris[0]) {
ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color; ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;
ctx.beginPath(); ctx.beginPath();
const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2; const sizeX = Math.abs(f.annotations.leftEyeIris[3][0] - f.annotations.leftEyeIris[1][0]) / 2;
@ -56,7 +56,7 @@ function drawIrisElipse(f: FaceResult, ctx: CanvasRenderingContext2D | Offscreen
ctx.fill(); ctx.fill();
} }
} }
if (f.annotations && f.annotations.rightEyeIris && f.annotations.rightEyeIris[0]) { if (f.annotations?.rightEyeIris && f.annotations?.rightEyeIris[0]) {
ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color; ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;
ctx.beginPath(); ctx.beginPath();
const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2; const sizeX = Math.abs(f.annotations.rightEyeIris[3][0] - f.annotations.rightEyeIris[1][0]) / 2;
@ -149,7 +149,7 @@ function drawFaceBoxes(f: FaceResult, ctx) {
} }
/** draw detected faces */ /** draw detected faces */
export async function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>) { export function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>) {
opt = mergeDeep(options, drawOptions); opt = mergeDeep(options, drawOptions);
if (!result || !inCanvas) return; if (!result || !inCanvas) return;
const ctx = getCanvasContext(inCanvas); const ctx = getCanvasContext(inCanvas);

4
src/draw/gesture.ts
View File

@ -5,8 +5,8 @@ import type { GestureResult } from '../result';
import type { AnyCanvas, DrawOptions } from '../exports'; import type { AnyCanvas, DrawOptions } from '../exports';
/** draw detected gestures */ /** draw detected gestures */
export async function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>) { export function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>) {
const localOptions = mergeDeep(options, drawOptions); const localOptions: DrawOptions = mergeDeep(options, drawOptions);
if (!result || !inCanvas) return; if (!result || !inCanvas) return;
if (localOptions.drawGestures) { if (localOptions.drawGestures) {
const ctx = getCanvasContext(inCanvas); const ctx = getCanvasContext(inCanvas);

4
src/draw/hand.ts
View File

@ -5,8 +5,8 @@ import type { HandResult } from '../result';
import type { AnyCanvas, DrawOptions, Point } from '../exports'; import type { AnyCanvas, DrawOptions, Point } from '../exports';
/** draw detected hands */ /** draw detected hands */
export async function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>) { export function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>) {
const localOptions = mergeDeep(options, drawOptions); const localOptions: DrawOptions = mergeDeep(options, drawOptions);
if (!result || !inCanvas) return; if (!result || !inCanvas) return;
const ctx = getCanvasContext(inCanvas); const ctx = getCanvasContext(inCanvas);
if (!ctx) return; if (!ctx) return;

4
src/draw/object.ts
View File

@ -5,8 +5,8 @@ import type { ObjectResult } from '../result';
import type { AnyCanvas, DrawOptions } from '../exports'; import type { AnyCanvas, DrawOptions } from '../exports';
/** draw detected objects */ /** draw detected objects */
export async function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>) { export function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>) {
const localOptions = mergeDeep(options, drawOptions); const localOptions: DrawOptions = mergeDeep(options, drawOptions);
if (!result || !inCanvas) return; if (!result || !inCanvas) return;
const ctx = getCanvasContext(inCanvas); const ctx = getCanvasContext(inCanvas);
if (!ctx) return; if (!ctx) return;

38
src/draw/options.ts
View File

@ -44,23 +44,23 @@ export interface DrawOptions {
/** currently set draw options {@link DrawOptions} */ /** currently set draw options {@link DrawOptions} */
export const options: DrawOptions = { export const options: DrawOptions = {
color: <string>'rgba(173, 216, 230, 0.6)', // 'lightblue' with light alpha channel color: 'rgba(173, 216, 230, 0.6)' as string, // 'lightblue' with light alpha channel
labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel labelColor: 'rgba(173, 216, 230, 1)' as string, // 'lightblue' with dark alpha channel
shadowColor: <string>'black', shadowColor: 'black' as string,
alpha: 0.5, alpha: 0.5 as number,
font: <string>'small-caps 16px "Segoe UI"', font: 'small-caps 16px "Segoe UI"' as string,
lineHeight: <number>18, lineHeight: 18 as number,
lineWidth: <number>4, lineWidth: 4 as number,
pointSize: <number>2, pointSize: 2 as number,
roundRect: <number>8, roundRect: 8 as number,
drawPoints: <boolean>false, drawPoints: false as boolean,
drawLabels: <boolean>true, drawLabels: true as boolean,
drawBoxes: <boolean>true, drawBoxes: true as boolean,
drawAttention: <boolean>true, drawAttention: true as boolean,
drawGestures: <boolean>true, drawGestures: true as boolean,
drawPolygons: <boolean>true, drawPolygons: true as boolean,
drawGaze: <boolean>true, drawGaze: true as boolean,
fillPolygons: <boolean>false, fillPolygons: false as boolean,
useDepth: <boolean>true, useDepth: true as boolean,
useCurves: <boolean>false, useCurves: false as boolean,
}; };

2
src/face/face.ts
View File

@ -200,7 +200,7 @@ export const detectFace = async (instance: Human /* instance of human */, input:
// if (faces[i]?.annotations?.leftEyeIris) delete faces[i].annotations.leftEyeIris; // if (faces[i]?.annotations?.leftEyeIris) delete faces[i].annotations.leftEyeIris;
// if (faces[i]?.annotations?.rightEyeIris) delete faces[i].annotations.rightEyeIris; // if (faces[i]?.annotations?.rightEyeIris) delete faces[i].annotations.rightEyeIris;
} }
const irisSize = (faces[i].annotations && faces[i].annotations.leftEyeIris && faces[i].annotations.leftEyeIris[0] && faces[i].annotations.rightEyeIris && faces[i].annotations.rightEyeIris[0] const irisSize = (faces[i]?.annotations?.leftEyeIris?.[0] && faces[i]?.annotations?.rightEyeIris?.[0]
&& (faces[i].annotations.leftEyeIris.length > 0) && (faces[i].annotations.rightEyeIris.length > 0) && (faces[i].annotations.leftEyeIris.length > 0) && (faces[i].annotations.rightEyeIris.length > 0)
&& (faces[i].annotations.leftEyeIris[0] !== null) && (faces[i].annotations.rightEyeIris[0] !== null)) && (faces[i].annotations.leftEyeIris[0] !== null) && (faces[i].annotations.rightEyeIris[0] !== null))
? 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] ? 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]

8
src/face/faceboxes.ts
View File

@ -56,11 +56,11 @@ export class FaceBoxes {
} }
} }
export async function load(config) { export async function load(config: Config) {
const model = await loadModel(config.face.detector?.modelPath); const model = await loadModel(config.face.detector?.modelPath);
if (config.debug) log(`load model: ${config.face.detector.modelPath.match(/\/(.*)\./)[1]}`); if (config.face.detector?.modelPath && config.debug) log(`load model: ${config.face.detector.modelPath?.match(/\/(.*)\./)?.[1] || ''}`);
const faceboxes = new FaceBoxes(model, config); const faceboxes = new FaceBoxes(model, config);
if (config.face.mesh.enabled && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\/(.*)\./)[1]}`); if (config.face.mesh?.enabled && config.face.mesh?.modelPath && config.debug) log(`load model: ${config.face.mesh.modelPath.match(/\/(.*)\./)?.[1] || ''}`);
if (config.face.iris.enabled && config.debug) log(`load model: ${config.face.iris.modelPath.match(/\/(.*)\./)[1]}`); if (config.face.iris?.enabled && config.face.iris?.modelPath && config.debug) log(`load model: ${config.face.iris.modelPath?.match(/\/(.*)\./)?.[1] || ''}`);
return faceboxes; return faceboxes;
} }

4
src/face/facemeshutil.ts
View File

@ -69,7 +69,7 @@ export const calculateLandmarksBoundingBox = (landmarks) => {
export const fixedRotationMatrix = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]; export const fixedRotationMatrix = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];
export const normalizeRadians = (angle) => angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI)); export const normalizeRadians = (angle: number) => angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));
export const computeRotation = (point1, point2) => normalizeRadians(Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0])); export const computeRotation = (point1, point2) => normalizeRadians(Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]));
@ -120,7 +120,7 @@ export const rotatePoint = (homogeneousCoordinate, rotationMatrix) => [dot(homog
export const xyDistanceBetweenPoints = (a, b) => Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2)); export const xyDistanceBetweenPoints = (a, b) => Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));
export function generateAnchors(inputSize) { export function generateAnchors(inputSize: number) {
const spec = inputSize === 192 const spec = inputSize === 192
? { strides: [4], anchors: [1] } // facemesh-detector ? { strides: [4], anchors: [1] } // facemesh-detector
: { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] }; // blazeface : { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] }; // blazeface

18
src/face/faceres.ts
View File

@ -40,8 +40,8 @@ export async function load(config: Config): Promise<GraphModel> {
export function enhance(input): Tensor { export function enhance(input): Tensor {
const tensor = (input.image || input.tensor || input) as Tensor; // input received from detector is already normalized to 0..1, input is also assumed to be straightened const tensor = (input.image || input.tensor || input) as Tensor; // input received from detector is already normalized to 0..1, input is also assumed to be straightened
if (!model?.inputs[0].shape) return tensor; // model has no shape so no point continuing if (!model?.inputs[0].shape) return tensor; // model has no shape so no point continuing
const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); const crop: Tensor = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);
const norm = tf.mul(crop, constants.tf255); const norm: Tensor = tf.mul(crop, constants.tf255);
tf.dispose(crop); tf.dispose(crop);
return norm; return norm;
/* /*
@ -74,10 +74,10 @@ export async function predict(image: Tensor, config: Config, idx: number, count:
skipped = 0; skipped = 0;
return new Promise(async (resolve) => { return new Promise(async (resolve) => {
const obj = { const obj = {
age: <number>0, age: 0 as number,
gender: <Gender>'unknown', gender: 'unknown' as Gender,
genderScore: <number>0, genderScore: 0 as number,
descriptor: <number[]>[], descriptor: [] as number[],
}; };
if (config.face.description?.enabled) { if (config.face.description?.enabled) {
@ -85,7 +85,7 @@ export async function predict(image: Tensor, config: Config, idx: number, count:
const resT = model?.execute(enhanced) as Tensor[]; const resT = model?.execute(enhanced) as Tensor[];
lastTime = now(); lastTime = now();
tf.dispose(enhanced); tf.dispose(enhanced);
const genderT = await resT.find((t) => t.shape[1] === 1) as Tensor; const genderT = resT.find((t) => t.shape[1] === 1) as Tensor;
const gender = await genderT.data(); const gender = await genderT.data();
const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100; const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;
if (confidence > (config.face.description.minConfidence || 0)) { if (confidence > (config.face.description.minConfidence || 0)) {
@ -93,7 +93,7 @@ export async function predict(image: Tensor, config: Config, idx: number, count:
obj.genderScore = Math.min(0.99, confidence); obj.genderScore = Math.min(0.99, confidence);
} }
const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1); const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1);
const age = (await argmax.data())[0]; const age: number = (await argmax.data())[0];
tf.dispose(argmax); tf.dispose(argmax);
const ageT = resT.find((t) => t.shape[1] === 100) as Tensor; const ageT = resT.find((t) => t.shape[1] === 100) as Tensor;
const all = await ageT.data(); const all = await ageT.data();
@ -102,7 +102,7 @@ export async function predict(image: Tensor, config: Config, idx: number, count:
const desc = resT.find((t) => t.shape[1] === 1024); const desc = resT.find((t) => t.shape[1] === 1024);
// const reshape = desc.reshape([128, 8]); // reshape large 1024-element descriptor to 128 x 8 // const reshape = desc.reshape([128, 8]); // reshape large 1024-element descriptor to 128 x 8
// const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it which leaves us with 128-element descriptor // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it which leaves us with 128-element descriptor
const descriptor = desc ? await desc.data() : <number[]>[]; const descriptor = desc ? await desc.data() : [] as number[];
obj.descriptor = Array.from(descriptor); obj.descriptor = Array.from(descriptor);
resT.forEach((t) => tf.dispose(t)); resT.forEach((t) => tf.dispose(t));
} }

4
src/hand/handpose.ts
View File

@ -96,7 +96,7 @@ export async function load(config: Config): Promise<[GraphModel | null, GraphMod
if (config.debug) log('cached model:', handDetectorModel['modelUrl']); if (config.debug) log('cached model:', handDetectorModel['modelUrl']);
if (config.debug) log('cached model:', handPoseModel['modelUrl']); if (config.debug) log('cached model:', handPoseModel['modelUrl']);
} }
const handDetector = new handdetector.HandDetector(handDetectorModel); const handDetector = handDetectorModel ? new handdetector.HandDetector(handDetectorModel) : undefined;
handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel); if (handDetector && handPoseModel) handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel);
return [handDetectorModel, handPoseModel]; return [handDetectorModel, handPoseModel];
} }

19
src/hand/handposedetector.ts
View File

@ -9,6 +9,7 @@ import * as anchors from './handposeanchors';
import { constants } from '../tfjs/constants'; import { constants } from '../tfjs/constants';
import type { Tensor, GraphModel } from '../tfjs/types'; import type { Tensor, GraphModel } from '../tfjs/types';
import type { Point } from '../result'; import type { Point } from '../result';
import type { Config } from '../config';
export class HandDetector { export class HandDetector {
model: GraphModel; model: GraphModel;
@ -18,11 +19,11 @@ export class HandDetector {
inputSizeTensor: Tensor; inputSizeTensor: Tensor;
doubleInputSizeTensor: Tensor; doubleInputSizeTensor: Tensor;
constructor(model) { constructor(model: GraphModel) {
this.model = model; this.model = model;
this.anchors = anchors.anchors.map((anchor) => [anchor.x, anchor.y]); this.anchors = anchors.anchors.map((anchor) => [anchor.x, anchor.y]);
this.anchorsTensor = tf.tensor2d(this.anchors); this.anchorsTensor = tf.tensor2d(this.anchors);
this.inputSize = (this.model && this.model.inputs && this.model.inputs[0].shape) ? this.model.inputs[0].shape[2] : 0; this.inputSize = this?.model?.inputs?.[0]?.shape?.[2] || 0;
this.inputSizeTensor = tf.tensor1d([this.inputSize, this.inputSize]); this.inputSizeTensor = tf.tensor1d([this.inputSize, this.inputSize]);
this.doubleInputSizeTensor = tf.tensor1d([this.inputSize * 2, this.inputSize * 2]); this.doubleInputSizeTensor = tf.tensor1d([this.inputSize * 2, this.inputSize * 2]);
} }
@ -40,20 +41,20 @@ export class HandDetector {
t.endPoints = tf.mul(t.add, this.inputSizeTensor); t.endPoints = tf.mul(t.add, this.inputSizeTensor);
const res = tf.concat2d([t.startPoints, t.endPoints], 1); const res = tf.concat2d([t.startPoints, t.endPoints], 1);
Object.keys(t).forEach((tensor) => tf.dispose(t[tensor])); Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
return res; return res as Tensor;
} }
normalizeLandmarks(rawPalmLandmarks, index) { normalizeLandmarks(rawPalmLandmarks, index: number) {
const t: Record<string, Tensor> = {}; const t: Record<string, Tensor> = {};
t.reshape = tf.reshape(rawPalmLandmarks, [-1, 7, 2]); t.reshape = tf.reshape(rawPalmLandmarks, [-1, 7, 2]);
t.div = tf.div(t.reshape, this.inputSizeTensor); t.div = tf.div(t.reshape, this.inputSizeTensor);
t.landmarks = tf.add(t.div, this.anchors[index]); t.landmarks = tf.add(t.div, this.anchors[index] ? this.anchors[index] : 0);
const res = tf.mul(t.landmarks, this.inputSizeTensor); const res = tf.mul(t.landmarks, this.inputSizeTensor);
Object.keys(t).forEach((tensor) => tf.dispose(t[tensor])); Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));
return res; return res as Tensor;
} }
async predict(input, config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> { async predict(input: Tensor, config: Config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> {
const t: Record<string, Tensor> = {}; const t: Record<string, Tensor> = {};
t.resize = tf.image.resizeBilinear(input, [this.inputSize, this.inputSize]); t.resize = tf.image.resizeBilinear(input, [this.inputSize, this.inputSize]);
t.div = tf.div(t.resize, constants.tf127); t.div = tf.div(t.resize, constants.tf127);
@ -67,7 +68,7 @@ export class HandDetector {
t.boxes = tf.slice(t.predictions, [0, 1], [-1, 4]); t.boxes = tf.slice(t.predictions, [0, 1], [-1, 4]);
t.norm = this.normalizeBoxes(t.boxes); t.norm = this.normalizeBoxes(t.boxes);
// box detection is flaky so we look for 3x boxes than we need results // box detection is flaky so we look for 3x boxes than we need results
t.nms = await tf.image.nonMaxSuppressionAsync(t.norm, t.scores, 3 * config.hand.maxDetected, config.hand.iouThreshold, config.hand.minConfidence); t.nms = await tf.image.nonMaxSuppressionAsync(t.norm, t.scores, 3 * (config.hand?.maxDetected || 1), config.hand.iouThreshold, config.hand.minConfidence);
const nms = await t.nms.array() as number[]; const nms = await t.nms.array() as number[];
const hands: { startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number }[] = []; const hands: { startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number }[] = [];
for (const index of nms) { for (const index of nms) {
@ -81,7 +82,7 @@ export class HandDetector {
const endPoint = box.slice(2, 4) as unknown as Point; const endPoint = box.slice(2, 4) as unknown as Point;
const palmLandmarks = await p.palmLandmarks.array(); const palmLandmarks = await p.palmLandmarks.array();
const hand = { startPoint, endPoint, palmLandmarks, confidence: scores[index] }; const hand = { startPoint, endPoint, palmLandmarks, confidence: scores[index] };
const scaled = util.scaleBoxCoordinates(hand, [input.shape[2] / this.inputSize, input.shape[1] / this.inputSize]); const scaled = util.scaleBoxCoordinates(hand, [(input.shape[2] || 1) / this.inputSize, (input.shape[1] || 0) / this.inputSize]);
hands.push(scaled); hands.push(scaled);
Object.keys(p).forEach((tensor) => tf.dispose(p[tensor])); Object.keys(p).forEach((tensor) => tf.dispose(p[tensor]));
} }

2
src/hand/handposepipeline.ts
View File

@ -30,7 +30,7 @@ export class HandPipeline {
constructor(handDetector, handPoseModel) { constructor(handDetector, handPoseModel) {
this.handDetector = handDetector; this.handDetector = handDetector;
this.handPoseModel = handPoseModel; this.handPoseModel = handPoseModel;
this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0; this.inputSize = this.handPoseModel?.inputs?.[0].shape?.[2] || 0;
this.storedBoxes = []; this.storedBoxes = [];
this.skipped = Number.MAX_SAFE_INTEGER; this.skipped = Number.MAX_SAFE_INTEGER;
this.detectedHands = 0; this.detectedHands = 0;

4
src/human.ts
View File

@ -295,7 +295,7 @@ export class Human {
if (this.env.initial) { // print version info on first run and check for correct backend setup if (this.env.initial) { // print version info on first run and check for correct backend setup
if (this.config.debug) log(`version: ${this.version}`); if (this.config.debug) log(`version: ${this.version}`);
if (this.config.debug) log(`tfjs version: ${this.tf.version['tfjs-core']}`); if (this.config.debug) log(`tfjs version: ${this.tf.version['tfjs-core'] as string}`);
if (!await backend.check(this)) log('error: backend check failed'); if (!await backend.check(this)) log('error: backend check failed');
await tf.ready(); await tf.ready();
if (this.env.browser) { if (this.env.browser) {
@ -321,7 +321,7 @@ export class Human {
/** emit event */ /** emit event */
emit = (event: string) => { emit = (event: string) => {
if (this.events && this.events.dispatchEvent) this.events.dispatchEvent(new Event(event)); if (this.events?.dispatchEvent) this.events.dispatchEvent(new Event(event));
}; };
/** Runs interpolation using last known result and returns smoothened result /** Runs interpolation using last known result and returns smoothened result

2
src/image/enhance.ts
View File

@ -20,5 +20,5 @@ export async function histogramEqualization(inputImage: Tensor): Promise<Tensor>
const rgb = tf.stack([enh[0], enh[1], enh[2]], 2); const rgb = tf.stack([enh[0], enh[1], enh[2]], 2);
const reshape = tf.reshape(rgb, [1, squeeze.shape[0], squeeze.shape[1], 3]); const reshape = tf.reshape(rgb, [1, squeeze.shape[0], squeeze.shape[1], 3]);
tf.dispose([...channels, ...min, ...max, ...sub, ...range, ...fact, ...enh, rgb, squeeze]); tf.dispose([...channels, ...min, ...max, ...sub, ...range, ...fact, ...enh, rgb, squeeze]);
return reshape; // output shape is [1, height, width, 3] return reshape as Tensor; // output shape is [1, height, width, 3]
} }

23
src/image/image.ts
View File

@ -25,7 +25,7 @@ const last: { inputSum: number, cacheDiff: number, sumMethod: number, inputTenso
}; };
export function canvas(width: number, height: number): AnyCanvas { export function canvas(width: number, height: number): AnyCanvas {
let c; let c: AnyCanvas;
if (env.browser) { // browser defines canvas object if (env.browser) { // browser defines canvas object
if (env.worker) { // if runing in web worker use OffscreenCanvas if (env.worker) { // if runing in web worker use OffscreenCanvas
if (typeof OffscreenCanvas === 'undefined') throw new Error('canvas error: attempted to run in web worker but OffscreenCanvas is not supported'); if (typeof OffscreenCanvas === 'undefined') throw new Error('canvas error: attempted to run in web worker but OffscreenCanvas is not supported');
@ -42,6 +42,7 @@ export function canvas(width: number, height: number): AnyCanvas {
else if (typeof globalThis.Canvas !== 'undefined') c = new globalThis.Canvas(width, height); else if (typeof globalThis.Canvas !== 'undefined') c = new globalThis.Canvas(width, height);
// else throw new Error('canvas error: attempted to use canvas in nodejs without canvas support installed'); // else throw new Error('canvas error: attempted to use canvas in nodejs without canvas support installed');
} }
// @ts-ignore its either defined or we already threw an error
return c; return c;
} }
@ -98,7 +99,7 @@ export async function process(input: Input, config: Config, getTensor: boolean =
} }
} }
// at the end shape must be [1, height, width, 3] // at the end shape must be [1, height, width, 3]
if (tensor == null || (tensor as Tensor).shape.length !== 4 || (tensor as Tensor).shape[0] !== 1 || (tensor as Tensor).shape[3] !== 3) throw new Error(`input error: attempted to use tensor with unrecognized shape: ${(input as Tensor).shape}`); if (tensor == null || tensor.shape.length !== 4 || tensor.shape[0] !== 1 || tensor.shape[3] !== 3) throw new Error(`input error: attempted to use tensor with unrecognized shape: ${((input as Tensor).shape).toString()}`);
if ((tensor).dtype === 'int32') { if ((tensor).dtype === 'int32') {
const cast = tf.cast(tensor, 'float32'); const cast = tf.cast(tensor, 'float32');
tf.dispose(tensor); tf.dispose(tensor);
@ -111,14 +112,14 @@ export async function process(input: Input, config: Config, getTensor: boolean =
if (config.debug) log('input stream is not ready'); if (config.debug) log('input stream is not ready');
return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize
} }
const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0)); const originalWidth: number = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0));
const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0)); const originalHeight: number = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0));
if (!originalWidth || !originalHeight) { if (!originalWidth || !originalHeight) {
if (config.debug) log('cannot determine input dimensions'); if (config.debug) log('cannot determine input dimensions');
return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize
} }
let targetWidth = originalWidth; let targetWidth: number = originalWidth;
let targetHeight = originalHeight; let targetHeight: number = originalHeight;
if (targetWidth > maxSize) { if (targetWidth > maxSize) {
targetWidth = maxSize; targetWidth = maxSize;
targetHeight = Math.trunc(targetWidth * originalHeight / originalWidth); targetHeight = Math.trunc(targetWidth * originalHeight / originalWidth);
@ -129,9 +130,9 @@ export async function process(input: Input, config: Config, getTensor: boolean =
} }
// create our canvas and resize it if needed // create our canvas and resize it if needed
if ((config.filter.width || 0) > 0) targetWidth = config.filter.width; if ((config.filter?.width || 0) > 0) targetWidth = config.filter.width as number;
else if ((config.filter.height || 0) > 0) targetWidth = originalWidth * ((config.filter.height || 0) / originalHeight); else if ((config.filter?.height || 0) > 0) targetWidth = originalWidth * ((config.filter.height || 0) / originalHeight);
if ((config.filter.height || 0) > 0) targetHeight = config.filter.height; if ((config.filter.height || 0) > 0) targetHeight = config.filter.height as number;
else if ((config.filter.width || 0) > 0) targetHeight = originalHeight * ((config.filter.width || 0) / originalWidth); else if ((config.filter.width || 0) > 0) targetHeight = originalHeight * ((config.filter.width || 0) / originalWidth);
if (!targetWidth || !targetHeight) throw new Error('input error: cannot determine dimension'); if (!targetWidth || !targetHeight) throw new Error('input error: cannot determine dimension');
if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) inCanvas = canvas(targetWidth, targetHeight); if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) inCanvas = canvas(targetWidth, targetHeight);
@ -227,8 +228,8 @@ export async function process(input: Input, config: Config, getTensor: boolean =
pixels = rgb; pixels = rgb;
} }
if (!pixels) throw new Error('input error: cannot create tensor'); if (!pixels) throw new Error('input error: cannot create tensor');
const casted = tf.cast(pixels, 'float32'); const casted: Tensor = tf.cast(pixels, 'float32');
const tensor = config.filter.equalization ? await enhance.histogramEqualization(casted) : tf.expandDims(casted, 0); const tensor: Tensor = config.filter.equalization ? await enhance.histogramEqualization(casted) : tf.expandDims(casted, 0);
tf.dispose([pixels, casted]); tf.dispose([pixels, casted]);
return { tensor, canvas: (config.filter.return ? outCanvas : null) }; return { tensor, canvas: (config.filter.return ? outCanvas : null) };
} }

24
src/image/imagefx.ts
View File

@ -9,7 +9,7 @@ import * as shaders from './imagefxshaders';
import { canvas } from './image'; import { canvas } from './image';
import { log } from '../util/util'; import { log } from '../util/util';
const collect = (source, prefix, collection) => { const collect = (source, prefix: string, collection) => {
const r = new RegExp('\\b' + prefix + ' \\w+ (\\w+)', 'ig'); const r = new RegExp('\\b' + prefix + ' \\w+ (\\w+)', 'ig');
source.replace(r, (match, name) => { source.replace(r, (match, name) => {
collection[name] = 0; collection[name] = 0;
@ -37,7 +37,7 @@ class GLProgram {
this.gl.attachShader(this.id, fragmentShader); this.gl.attachShader(this.id, fragmentShader);
this.gl.linkProgram(this.id); this.gl.linkProgram(this.id);
if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) { if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) {
log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`); log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id) || 'unknown'}`);
return; return;
} }
this.gl.useProgram(this.id); this.gl.useProgram(this.id);
@ -57,7 +57,7 @@ class GLProgram {
this.gl.shaderSource(shader, source); this.gl.shaderSource(shader, source);
this.gl.compileShader(shader); this.gl.compileShader(shader);
if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) { if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) {
log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader)}`); log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader) || 'unknown'}`);
return null; return null;
} }
return shader; return shader;
@ -174,7 +174,7 @@ export function GLImageFilter() {
} }
const filter = { const filter = {
colorMatrix: (matrix) => { // general color matrix filter colorMatrix: (matrix: number[]) => { // general color matrix filter
const m = new Float32Array(matrix); const m = new Float32Array(matrix);
m[4] /= 255; m[4] /= 255;
m[9] /= 255; m[9] /= 255;
@ -189,7 +189,7 @@ export function GLImageFilter() {
draw(); draw();
}, },
brightness: (brightness) => { brightness: (brightness: number) => {
const b = (brightness || 0) + 1; const b = (brightness || 0) + 1;
filter.colorMatrix([ filter.colorMatrix([
b, 0, 0, 0, 0, b, 0, 0, 0, 0,
@ -199,7 +199,7 @@ export function GLImageFilter() {
]); ]);
}, },
saturation: (amount) => { saturation: (amount: number) => {
const x = (amount || 0) * 2 / 3 + 1; const x = (amount || 0) * 2 / 3 + 1;
const y = ((x - 1) * -0.5); const y = ((x - 1) * -0.5);
filter.colorMatrix([ filter.colorMatrix([
@ -214,7 +214,7 @@ export function GLImageFilter() {
filter.saturation(-1); filter.saturation(-1);
}, },
contrast: (amount) => { contrast: (amount: number) => {
const v = (amount || 0) + 1; const v = (amount || 0) + 1;
const o = -128 * (v - 1); const o = -128 * (v - 1);
filter.colorMatrix([ filter.colorMatrix([
@ -229,7 +229,7 @@ export function GLImageFilter() {
filter.contrast(-2); filter.contrast(-2);
}, },
hue: (rotation) => { hue: (rotation: number) => {
rotation = (rotation || 0) / 180 * Math.PI; rotation = (rotation || 0) / 180 * Math.PI;
const cos = Math.cos(rotation); const cos = Math.cos(rotation);
const sin = Math.sin(rotation); const sin = Math.sin(rotation);
@ -316,7 +316,7 @@ export function GLImageFilter() {
]); ]);
}, },
convolution: (matrix) => { // general convolution Filter convolution: (matrix: number[]) => { // general convolution Filter
const m = new Float32Array(matrix); const m = new Float32Array(matrix);
const pixelSizeX = 1 / fxcanvas.width; const pixelSizeX = 1 / fxcanvas.width;
const pixelSizeY = 1 / fxcanvas.height; const pixelSizeY = 1 / fxcanvas.height;
@ -364,7 +364,7 @@ export function GLImageFilter() {
]); ]);
}, },
emboss: (size) => { emboss: (size: number) => {
const s = size || 1; const s = size || 1;
// @ts-ignore this // @ts-ignore this
filter.convolution.call(this, [ filter.convolution.call(this, [
@ -374,7 +374,7 @@ export function GLImageFilter() {
]); ]);
}, },
blur: (size) => { blur: (size: number) => {
const blurSizeX = (size / 7) / fxcanvas.width; const blurSizeX = (size / 7) / fxcanvas.width;
const blurSizeY = (size / 7) / fxcanvas.height; const blurSizeY = (size / 7) / fxcanvas.height;
const program = compileShader(shaders.blur); const program = compileShader(shaders.blur);
@ -387,7 +387,7 @@ export function GLImageFilter() {
draw(); draw();
}, },
pixelate: (size) => { pixelate: (size: number) => {
const blurSizeX = (size) / fxcanvas.width; const blurSizeX = (size) / fxcanvas.width;
const blurSizeY = (size) / fxcanvas.height; const blurSizeY = (size) / fxcanvas.height;
const program = compileShader(shaders.pixelate); const program = compileShader(shaders.pixelate);

2
src/models.ts
View File

@ -158,7 +158,7 @@ export function validateModel(newInstance: Human | null, model: GraphModel | nul
interface Op { name: string, category: string, op: string } interface Op { name: string, category: string, op: string }
const url = model['modelUrl'] as string; const url = model['modelUrl'] as string;
const executor = model['executor']; const executor = model['executor'];
if (executor && executor.graph.nodes) { if (executor?.graph?.nodes) {
for (const kernel of Object.values(executor.graph.nodes)) { for (const kernel of Object.values(executor.graph.nodes)) {
const op = (kernel as Op).op.toLowerCase(); const op = (kernel as Op).op.toLowerCase();
if (!ops.includes(op)) ops.push(op); if (!ops.includes(op)) ops.push(op);

12
src/tfjs/backend.ts
View File

@ -21,7 +21,7 @@ function registerCustomOps() {
const kernelMod = { const kernelMod = {
kernelName: 'FloorMod', kernelName: 'FloorMod',
backendName: tf.getBackend(), backendName: tf.getBackend(),
kernelFunc: (op) => tf.tidy(() => tf.floorDiv(op.inputs.a / op.inputs.b) * op.inputs.b + tf.mod(op.inputs.a, op.inputs.b)), kernelFunc: (op) => tf.tidy(() => tf.add(tf.mul(tf.floorDiv(op.inputs.a / op.inputs.b), op.inputs.b), tf.mod(op.inputs.a, op.inputs.b))),
}; };
tf.registerKernel(kernelMod); tf.registerKernel(kernelMod);
env.kernels.push('floormod'); env.kernels.push('floormod');
@ -71,8 +71,8 @@ export async function check(instance: Human, force = false) {
} }
// check available backends // check available backends
if (instance.config.backend === 'humangl') await humangl.register(instance); if (instance.config.backend === 'humangl') humangl.register(instance);
const available = Object.keys(tf.engine().registryFactory); const available = Object.keys(tf.engine().registryFactory as Record<string, unknown>);
if (instance.config.debug) log('available backends:', available); if (instance.config.debug) log('available backends:', available);
if (!available.includes(instance.config.backend)) { if (!available.includes(instance.config.backend)) {
@ -87,7 +87,7 @@ export async function check(instance: Human, force = false) {
if (instance.config.backend === 'wasm') { if (instance.config.backend === 'wasm') {
if (tf.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY) tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true); if (tf.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY) tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);
if (instance.config.debug) log('wasm path:', instance.config.wasmPath); if (instance.config.debug) log('wasm path:', instance.config.wasmPath);
if (typeof tf.setWasmPaths !== 'undefined') await tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch); if (typeof tf.setWasmPaths !== 'undefined') tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch);
else throw new Error('backend error: attempting to use wasm backend but wasm path is not set'); else throw new Error('backend error: attempting to use wasm backend but wasm path is not set');
let mt = false; let mt = false;
let simd = false; let simd = false;
@ -127,7 +127,7 @@ export async function check(instance: Human, force = false) {
} }
if (tf.backend().getGPGPUContext) { if (tf.backend().getGPGPUContext) {
const gl = await tf.backend().getGPGPUContext().gl; const gl = await tf.backend().getGPGPUContext().gl;
if (instance.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`); if (instance.config.debug) log(`gl version:${gl.getParameter(gl.VERSION) as string} renderer:${gl.getParameter(gl.RENDERER) as string}`);
} }
} }
@ -165,5 +165,5 @@ export function fakeOps(kernelNames: string[], config) {
}; };
tf.registerKernel(kernelConfig); tf.registerKernel(kernelConfig);
} }
env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase()); // re-scan registered ops env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => (kernel.kernelName as string).toLowerCase()); // re-scan registered ops
} }

14
src/tfjs/humangl.ts
View File

@ -11,9 +11,9 @@ import type { AnyCanvas } from '../exports';
export const config = { export const config = {
name: 'humangl', name: 'humangl',
priority: 999, priority: 999,
canvas: <null | AnyCanvas>null, canvas: null as null | AnyCanvas,
gl: <null | WebGL2RenderingContext>null, gl: null as null | WebGL2RenderingContext,
extensions: <string[] | null> [], extensions: [] as string[] | null,
webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2 webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2
alpha: false, alpha: false,
antialias: false, antialias: false,
@ -42,7 +42,7 @@ function extensions(): void {
* *
* @returns void * @returns void
*/ */
export async function register(instance: Human): Promise<void> { export function register(instance: Human): void {
// force backend reload if gl context is not valid // force backend reload if gl context is not valid
if (instance.config.backend !== 'humangl') return; if (instance.config.backend !== 'humangl') return;
if ((config.name in tf.engine().registry) && (!config.gl || !config.gl.getParameter(config.gl.VERSION))) { if ((config.name in tf.engine().registry) && (!config.gl || !config.gl.getParameter(config.gl.VERSION))) {
@ -56,7 +56,7 @@ export async function register(instance: Human): Promise<void> {
} }
if (!tf.findBackend(config.name)) { if (!tf.findBackend(config.name)) {
try { try {
config.canvas = await image.canvas(100, 100); config.canvas = image.canvas(100, 100);
} catch (err) { } catch (err) {
log('error: cannot create canvas:', err); log('error: cannot create canvas:', err);
return; return;
@ -74,7 +74,7 @@ export async function register(instance: Human): Promise<void> {
return; return;
} }
if (config.canvas) { if (config.canvas) {
config.canvas.addEventListener('webglcontextlost', async (e) => { config.canvas.addEventListener('webglcontextlost', (e) => {
log('error: humangl:', e.type); log('error: humangl:', e.type);
log('possible browser memory leak using webgl or conflict with multiple backend registrations'); log('possible browser memory leak using webgl or conflict with multiple backend registrations');
instance.emit('error'); instance.emit('error');
@ -121,7 +121,7 @@ export async function register(instance: Human): Promise<void> {
} }
const current = tf.backend().getGPGPUContext ? tf.backend().getGPGPUContext().gl : null; const current = tf.backend().getGPGPUContext ? tf.backend().getGPGPUContext().gl : null;
if (current) { if (current) {
log(`humangl webgl version:${current.getParameter(current.VERSION)} renderer:${current.getParameter(current.RENDERER)}`); log(`humangl webgl version:${current.getParameter(current.VERSION) as string} renderer:${current.getParameter(current.RENDERER) as string}`);
} else { } else {
log('error: no current gl context:', current, config.gl); log('error: no current gl context:', current, config.gl);
return; return;

6
src/tfjs/load.ts
View File

@ -23,7 +23,7 @@ export interface ModelInfo {
export const modelStats: Record<string, ModelInfo> = {}; export const modelStats: Record<string, ModelInfo> = {};
async function httpHandler(url, init?): Promise<Response | null> { async function httpHandler(url: string, init?: RequestInit): Promise<Response | null> {
if (options.debug) log('load model fetch:', url, init); if (options.debug) log('load model fetch:', url, init);
return fetch(url, init); return fetch(url, init);
} }
@ -55,7 +55,7 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
options.cacheSupported = false; options.cacheSupported = false;
} }
modelStats[shortModelName].inCache = (options.cacheSupported && options.cacheModels) && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache modelStats[shortModelName].inCache = (options.cacheSupported && options.cacheModels) && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache
const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url, init?) => httpHandler(url, init) }; const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url: string, init?: RequestInit) => httpHandler(url, init) };
const model: GraphModel = new tf.GraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl const model: GraphModel = new tf.GraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl
let loaded = false; let loaded = false;
try { try {
@ -81,6 +81,6 @@ export async function loadModel(modelPath: string | undefined): Promise<GraphMod
log('error saving model:', modelUrl, err); log('error saving model:', modelUrl, err);
} }
} }
validateModel(null, model, `${modelPath}`); validateModel(null, model, `${modelPath || ''}`);
return model; return model;
} }

6
src/util/env.ts
View File

@ -97,9 +97,9 @@ export class Env {
this.worker = this.browser && this.offscreen ? (typeof WorkerGlobalScope !== 'undefined') : undefined; this.worker = this.browser && this.offscreen ? (typeof WorkerGlobalScope !== 'undefined') : undefined;
if (typeof navigator !== 'undefined') { if (typeof navigator !== 'undefined') {
const raw = navigator.userAgent.match(/\(([^()]+)\)/g); const raw = navigator.userAgent.match(/\(([^()]+)\)/g);
if (raw && raw[0]) { if (raw?.[0]) {
const platformMatch = raw[0].match(/\(([^()]+)\)/g); const platformMatch = raw[0].match(/\(([^()]+)\)/g);
this.platform = (platformMatch && platformMatch[0]) ? platformMatch[0].replace(/\(|\)/g, '') : ''; this.platform = (platformMatch?.[0]) ? platformMatch[0].replace(/\(|\)/g, '') : '';
this.agent = navigator.userAgent.replace(raw[0], ''); this.agent = navigator.userAgent.replace(raw[0], '');
if (this.platform[1]) this.agent = this.agent.replace(raw[1], ''); if (this.platform[1]) this.agent = this.agent.replace(raw[1], '');
this.agent = this.agent.replace(/ /g, ' '); this.agent = this.agent.replace(/ /g, ' ');
@ -156,7 +156,7 @@ export class Env {
this.webgpu.supported = false; this.webgpu.supported = false;
} }
try { try {
this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase()); this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => (kernel.kernelName as string).toLowerCase());
} catch { /**/ } } catch { /**/ }
} }

6
src/util/interpolate.ts
View File

@ -2,7 +2,7 @@
* Results interpolation for smoothening of video detection results inbetween detected frames * Results interpolation for smoothening of video detection results inbetween detected frames
*/ */
import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point, BodyLandmark, BodyAnnotation } from '../result'; import type { Result, FaceResult, BodyResult, HandResult, ObjectResult, PersonResult, Box, Point, BodyLandmark, BodyAnnotation } from '../result';
import type { Config } from '../config'; import type { Config } from '../config';
import * as moveNetCoords from '../body/movenetcoords'; import * as moveNetCoords from '../body/movenetcoords';
@ -103,7 +103,7 @@ export function calc(newResult: Result, config: Config): Result {
annotations = bufferedResult.hand[i].annotations; annotations = bufferedResult.hand[i].annotations;
} else if (newResult.hand[i].annotations) { } else if (newResult.hand[i].annotations) {
for (const key of Object.keys(newResult.hand[i].annotations)) { // update annotations for (const key of Object.keys(newResult.hand[i].annotations)) { // update annotations
annotations[key] = newResult.hand[i].annotations[key] && newResult.hand[i].annotations[key][0] annotations[key] = newResult.hand[i]?.annotations?.[key]?.[0]
? newResult.hand[i].annotations[key] ? newResult.hand[i].annotations[key]
.map((val, j: number) => val .map((val, j: number) => val
.map((coord: number, k: number) => ((bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / bufferedFactor)) .map((coord: number, k: number) => ((bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / bufferedFactor))
@ -173,7 +173,7 @@ export function calc(newResult: Result, config: Config): Result {
} }
// just copy latest gestures without interpolation // just copy latest gestures without interpolation
if (newResult.gesture) bufferedResult.gesture = newResult.gesture as GestureResult[]; if (newResult.gesture) bufferedResult.gesture = newResult.gesture;
// append interpolation performance data // append interpolation performance data
const t1 = now(); const t1 = now();

2
src/util/persons.ts
View File

@ -59,7 +59,7 @@ export function join(faces: FaceResult[], bodies: BodyResult[], hands: HandResul
person.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY]; // create new overarching box person.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY]; // create new overarching box
// shape is known so we calculate boxRaw as well // shape is known so we calculate boxRaw as well
if (shape && shape[1] && shape[2]) person.boxRaw = [person.box[0] / shape[2], person.box[1] / shape[1], person.box[2] / shape[2], person.box[3] / shape[1]]; if (shape?.[1] && shape?.[2]) person.boxRaw = [person.box[0] / shape[2], person.box[1] / shape[1], person.box[2] / shape[2], person.box[3] / shape[1]];
persons.push(person); persons.push(person);
} }

6
src/util/profile.ts
View File

@ -7,15 +7,15 @@ import { log } from './util';
export const data = {}; export const data = {};
export type ProfileData = { export interface ProfileData {
newBytes: number, newBytes: number,
peakBytes: number, peakBytes: number,
newTensors: number, newTensors: number,
kernels: Array<{ kernels: {
id: number, id: number,
kernelTimeMs: number, kernelTimeMs: number,
totalBytesSnapshot: number, totalBytesSnapshot: number,
}>, }[],
} }
export function run(modelName: string, profileData: ProfileData): void { // profileData is tfjs internal type export function run(modelName: string, profileData: ProfileData): void { // profileData is tfjs internal type

12
src/warmup.ts
View File

@ -10,6 +10,7 @@ import { env } from './util/env';
import type { Config } from './config'; import type { Config } from './config';
import type { Result } from './result'; import type { Result } from './result';
import type { Human, Models } from './human'; import type { Human, Models } from './human';
import type { Tensor } from './exports';
async function warmupBitmap(instance: Human): Promise<Result | undefined> { async function warmupBitmap(instance: Human): Promise<Result | undefined> {
const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob()); const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());
@ -76,10 +77,10 @@ async function warmupNode(instance: Human): Promise<Result | undefined> {
let img; let img;
if (instance.config.warmup === 'face') img = atob(sample.face); if (instance.config.warmup === 'face') img = atob(sample.face);
else img = atob(sample.body); else img = atob(sample.body);
let res; let res: Result;
if (('node' in tf) && (tf.getBackend() === 'tensorflow')) { if (('node' in tf) && (tf.getBackend() === 'tensorflow')) {
const data = tf['node'].decodeJpeg(img); // eslint-disable-line import/namespace const data: Tensor = tf['node'].decodeJpeg(img); // eslint-disable-line import/namespace
const expanded = data.expandDims(0); const expanded: Tensor = tf.expandDims(data, 0);
instance.tf.dispose(data); instance.tf.dispose(data);
// log('Input:', expanded); // log('Input:', expanded);
res = await instance.detect(expanded, instance.config); res = await instance.detect(expanded, instance.config);
@ -94,6 +95,7 @@ async function warmupNode(instance: Human): Promise<Result | undefined> {
res = await instance.detect(input, instance.config); res = await instance.detect(input, instance.config);
*/ */
} }
// @ts-ignore
return res; return res;
} }
@ -118,8 +120,8 @@ export async function runCompile(allModels: Models) {
const numTensorsStart = tf.engine().state.numTensors; const numTensorsStart = tf.engine().state.numTensors;
const compiledModels: string[] = []; const compiledModels: string[] = [];
for (const [modelName, model] of Object.entries(allModels).filter(([key, val]) => (key !== null && val !== null))) { for (const [modelName, model] of Object.entries(allModels).filter(([key, val]) => (key !== null && val !== null))) {
const shape = (model.inputs && model.inputs[0] && model.inputs[0].shape) ? [...model.inputs[0].shape] : [1, 64, 64, 3]; const shape = (model.inputs?.[0]?.shape) ? [...model.inputs[0].shape] : [1, 64, 64, 3];
const dtype = (model.inputs && model.inputs[0] && model.inputs[0].dtype) ? model.inputs[0].dtype : 'float32'; const dtype: string = (model.inputs?.[0]?.dtype) ? model.inputs[0].dtype : 'float32';
for (let dim = 0; dim < shape.length; dim++) { for (let dim = 0; dim < shape.length; dim++) {
if (shape[dim] === -1) shape[dim] = dim === 0 ? 1 : 64; // override batch number and any dynamic dimensions if (shape[dim] === -1) shape[dim] = dim === 0 ? 1 : 64; // override batch number and any dynamic dimensions
} }

78
test/build.log
View File

@ -1,39 +1,39 @@
2022-08-21 13:32:23 DATA:  Build {"name":"@vladmandic/human","version":"2.9.4"} 2022-08-21 15:21:09 DATA:  Build {"name":"@vladmandic/human","version":"2.9.4"}
2022-08-21 13:32:23 INFO:  Application: {"name":"@vladmandic/human","version":"2.9.4"} 2022-08-21 15:21:09 INFO:  Application: {"name":"@vladmandic/human","version":"2.9.4"}
2022-08-21 13:32:23 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 2022-08-21 15:21:09 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true}
2022-08-21 13:32:23 INFO:  Toolchain: {"build":"0.7.10","esbuild":"0.15.5","typescript":"4.7.4","typedoc":"0.23.10","eslint":"8.22.0"} 2022-08-21 15:21:09 INFO:  Toolchain: {"build":"0.7.10","esbuild":"0.15.5","typescript":"4.7.4","typedoc":"0.23.10","eslint":"8.22.0"}
2022-08-21 13:32:23 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 2022-08-21 15:21:09 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]}
2022-08-21 13:32:23 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 2022-08-21 15:21:09 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]}
2022-08-21 13:32:23 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":159,"outputBytes":608} 2022-08-21 15:21:09 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":159,"outputBytes":608}
2022-08-21 13:32:23 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":75,"inputBytes":652939,"outputBytes":306172} 2022-08-21 15:21:09 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":75,"inputBytes":653284,"outputBytes":306632}
2022-08-21 13:32:23 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":167,"outputBytes":612} 2022-08-21 15:21:09 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":167,"outputBytes":612}
2022-08-21 13:32:23 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":75,"inputBytes":652943,"outputBytes":306176} 2022-08-21 15:21:09 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":75,"inputBytes":653288,"outputBytes":306636}
2022-08-21 13:32:23 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":206,"outputBytes":664} 2022-08-21 15:21:09 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":206,"outputBytes":664}
2022-08-21 13:32:23 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":75,"inputBytes":652995,"outputBytes":306226} 2022-08-21 15:21:09 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":75,"inputBytes":653340,"outputBytes":306686}
2022-08-21 13:32:23 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1125,"outputBytes":358} 2022-08-21 15:21:09 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1125,"outputBytes":358}
2022-08-21 13:32:23 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1088,"outputBytes":583} 2022-08-21 15:21:09 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1088,"outputBytes":583}
2022-08-21 13:32:23 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":75,"inputBytes":652914,"outputBytes":305046} 2022-08-21 15:21:09 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":75,"inputBytes":653259,"outputBytes":305505}
2022-08-21 13:32:23 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":11,"inputBytes":1344,"outputBytes":2787569} 2022-08-21 15:21:09 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":11,"inputBytes":1344,"outputBytes":2787569}
2022-08-21 13:32:23 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":75,"inputBytes":3439900,"outputBytes":1667925} 2022-08-21 15:21:09 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":75,"inputBytes":3440245,"outputBytes":1668404}
2022-08-21 13:32:23 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":75,"inputBytes":3439900,"outputBytes":3070714} 2022-08-21 15:21:09 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":75,"inputBytes":3440245,"outputBytes":3071598}
2022-08-21 13:32:28 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":30} 2022-08-21 15:21:14 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":30}
2022-08-21 13:32:29 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":77,"generated":true} 2022-08-21 15:21:16 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":77,"generated":true}
2022-08-21 13:32:29 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6699,"outputBytes":3141} 2022-08-21 15:21:16 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6714,"outputBytes":3134}
2022-08-21 13:32:29 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15549,"outputBytes":7741} 2022-08-21 15:21:16 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15501,"outputBytes":7733}
2022-08-21 13:32:39 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":111,"errors":0,"warnings":0} 2022-08-21 15:21:27 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":111,"errors":0,"warnings":0}
2022-08-21 13:32:39 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 2022-08-21 15:21:27 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"}
2022-08-21 13:32:39 STATE: Copy: {"input":"tfjs/tfjs.esm.d.ts"} 2022-08-21 15:21:27 STATE: Copy: {"input":"tfjs/tfjs.esm.d.ts"}
2022-08-21 13:32:39 INFO:  Done... 2022-08-21 15:21:27 INFO:  Done...
2022-08-21 13:32:40 STATE: API-Extractor: {"succeeeded":true,"errors":0,"warnings":198} 2022-08-21 15:21:27 STATE: API-Extractor: {"succeeeded":true,"errors":0,"warnings":198}
2022-08-21 13:32:40 STATE: Copy: {"input":"types/human.d.ts"} 2022-08-21 15:21:27 STATE: Copy: {"input":"types/human.d.ts"}
2022-08-21 13:32:40 INFO:  Analyze models: {"folders":8,"result":"models/models.json"} 2022-08-21 15:21:27 INFO:  Analyze models: {"folders":8,"result":"models/models.json"}
2022-08-21 13:32:40 STATE: Models {"folder":"./models","models":13} 2022-08-21 15:21:27 STATE: Models {"folder":"./models","models":13}
2022-08-21 13:32:40 STATE: Models {"folder":"../human-models/models","models":42} 2022-08-21 15:21:27 STATE: Models {"folder":"../human-models/models","models":42}
2022-08-21 13:32:40 STATE: Models {"folder":"../blazepose/model/","models":4} 2022-08-21 15:21:27 STATE: Models {"folder":"../blazepose/model/","models":4}
2022-08-21 13:32:40 STATE: Models {"folder":"../anti-spoofing/model","models":1} 2022-08-21 15:21:27 STATE: Models {"folder":"../anti-spoofing/model","models":1}
2022-08-21 13:32:40 STATE: Models {"folder":"../efficientpose/models","models":3} 2022-08-21 15:21:27 STATE: Models {"folder":"../efficientpose/models","models":3}
2022-08-21 13:32:40 STATE: Models {"folder":"../insightface/models","models":5} 2022-08-21 15:21:27 STATE: Models {"folder":"../insightface/models","models":5}
2022-08-21 13:32:40 STATE: Models {"folder":"../movenet/models","models":3} 2022-08-21 15:21:27 STATE: Models {"folder":"../movenet/models","models":3}
2022-08-21 13:32:40 STATE: Models {"folder":"../nanodet/models","models":4} 2022-08-21 15:21:27 STATE: Models {"folder":"../nanodet/models","models":4}
2022-08-21 13:32:40 STATE: Models: {"count":57,"totalSize":383017442} 2022-08-21 15:21:28 STATE: Models: {"count":57,"totalSize":383017442}
2022-08-21 13:32:40 INFO:  Human Build complete... {"logFile":"test/build.log"} 2022-08-21 15:21:28 INFO:  Human Build complete... {"logFile":"test/build.log"}

1940
test/test.log
View File

File diff suppressed because it is too large Load Diff

44
typedoc/classes/Human.html
View File

File diff suppressed because one or more lines are too long

4
typedoc/functions/draw.canvas.html
View File

@ -16,7 +16,7 @@
<h1>Function canvas</h1></div> <h1>Function canvas</h1></div>
<section class="tsd-panel"> <section class="tsd-panel">
<ul class="tsd-signatures tsd-kind-function tsd-parent-kind-namespace"> <ul class="tsd-signatures tsd-kind-function tsd-parent-kind-namespace">
<li class="tsd-signature tsd-anchor-link" id="canvas">canvas<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLImageElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLVideoElement</span>, output<span class="tsd-signature-symbol">: </span><a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span><a href="#canvas" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none" id="icon-anchor-a"></path><path d="M10 14a3.5 3.5 0 0 0 5 0l4 -4a3.5 3.5 0 0 0 -5 -5l-.5 .5" id="icon-anchor-b"></path><path d="M14 10a3.5 3.5 0 0 0 -5 0l-4 4a3.5 3.5 0 0 0 5 5l.5 -.5" id="icon-anchor-c"></path></svg></a></li> <li class="tsd-signature tsd-anchor-link" id="canvas">canvas<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLImageElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLVideoElement</span>, output<span class="tsd-signature-symbol">: </span><a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">void</span><a href="#canvas" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none" id="icon-anchor-a"></path><path d="M10 14a3.5 3.5 0 0 0 5 0l4 -4a3.5 3.5 0 0 0 -5 -5l-.5 .5" id="icon-anchor-b"></path><path d="M14 10a3.5 3.5 0 0 0 -5 0l-4 4a3.5 3.5 0 0 0 5 5l.5 -.5" id="icon-anchor-c"></path></svg></a></li>
<li class="tsd-description"> <li class="tsd-description">
<div class="tsd-comment tsd-typography"><p>draw processed canvas</p> <div class="tsd-comment tsd-typography"><p>draw processed canvas</p>
</div> </div>
@ -27,7 +27,7 @@
<h5>input: <a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLImageElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLVideoElement</span></h5></li> <h5>input: <a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLImageElement</span><span class="tsd-signature-symbol"> | </span><span class="tsd-signature-type">HTMLVideoElement</span></h5></li>
<li> <li>
<h5>output: <a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a></h5></li></ul></div> <h5>output: <a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources"> <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul> <ul>
<li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/draw/draw.ts#L55">src/draw/draw.ts:55</a></li></ul></aside></li></ul></section></div> <li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/draw/draw.ts#L55">src/draw/draw.ts:55</a></li></ul></aside></li></ul></section></div>
<div class="col-4 col-menu menu-sticky-wrap menu-highlight"> <div class="col-4 col-menu menu-sticky-wrap menu-highlight">

4
typedoc/functions/draw.person.html
View File

@ -16,7 +16,7 @@
<h1>Function person</h1></div> <h1>Function person</h1></div>
<section class="tsd-panel"> <section class="tsd-panel">
<ul class="tsd-signatures tsd-kind-function tsd-parent-kind-namespace"> <ul class="tsd-signatures tsd-kind-function tsd-parent-kind-namespace">
<li class="tsd-signature tsd-anchor-link" id="person">person<span class="tsd-signature-symbol">(</span>inCanvas<span class="tsd-signature-symbol">: </span><a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a>, result<span class="tsd-signature-symbol">: </span><a href="../interfaces/PersonResult.html" class="tsd-signature-type" data-tsd-kind="Interface">PersonResult</a><span class="tsd-signature-symbol">[]</span>, drawOptions<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span><a href="#person" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none" id="icon-anchor-a"></path><path d="M10 14a3.5 3.5 0 0 0 5 0l4 -4a3.5 3.5 0 0 0 -5 -5l-.5 .5" id="icon-anchor-b"></path><path d="M14 10a3.5 3.5 0 0 0 -5 0l-4 4a3.5 3.5 0 0 0 5 5l.5 -.5" id="icon-anchor-c"></path></svg></a></li> <li class="tsd-signature tsd-anchor-link" id="person">person<span class="tsd-signature-symbol">(</span>inCanvas<span class="tsd-signature-symbol">: </span><a href="../types/AnyCanvas.html" class="tsd-signature-type" data-tsd-kind="Type alias">AnyCanvas</a>, result<span class="tsd-signature-symbol">: </span><a href="../interfaces/PersonResult.html" class="tsd-signature-type" data-tsd-kind="Interface">PersonResult</a><span class="tsd-signature-symbol">[]</span>, drawOptions<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">void</span><a href="#person" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none" id="icon-anchor-a"></path><path d="M10 14a3.5 3.5 0 0 0 5 0l4 -4a3.5 3.5 0 0 0 -5 -5l-.5 .5" id="icon-anchor-b"></path><path d="M14 10a3.5 3.5 0 0 0 -5 0l-4 4a3.5 3.5 0 0 0 5 5l.5 -.5" id="icon-anchor-c"></path></svg></a></li>
<li class="tsd-description"> <li class="tsd-description">
<div class="tsd-comment tsd-typography"><p>draw combined person results instead of individual detection result objects</p> <div class="tsd-comment tsd-typography"><p>draw combined person results instead of individual detection result objects</p>
</div> </div>
@ -29,7 +29,7 @@
<h5>result: <a href="../interfaces/PersonResult.html" class="tsd-signature-type" data-tsd-kind="Interface">PersonResult</a><span class="tsd-signature-symbol">[]</span></h5></li> <h5>result: <a href="../interfaces/PersonResult.html" class="tsd-signature-type" data-tsd-kind="Interface">PersonResult</a><span class="tsd-signature-symbol">[]</span></h5></li>
<li> <li>
<h5><code class="tsd-tag ts-flagOptional">Optional</code> drawOptions: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></div> <h5><code class="tsd-tag ts-flagOptional">Optional</code> drawOptions: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/DrawOptions.html" class="tsd-signature-type" data-tsd-kind="Interface">DrawOptions</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></div>
<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">void</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources"> <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">void</span></h4><aside class="tsd-sources">
<ul> <ul>
<li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/draw/draw.ts#L27">src/draw/draw.ts:27</a></li></ul></aside></li></ul></section></div> <li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/draw/draw.ts#L27">src/draw/draw.ts:27</a></li></ul></aside></li></ul></section></div>
<div class="col-4 col-menu menu-sticky-wrap menu-highlight"> <div class="col-4 col-menu menu-sticky-wrap menu-highlight">

14
types/human.d.ts vendored
View File

@ -28,7 +28,7 @@ declare interface ArrayMap {
export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu']; export declare type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];
/** draw detected bodies */ /** draw detected bodies */
declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function body(inCanvas: AnyCanvas, result: BodyResult[], drawOptions?: Partial<DrawOptions>): void;
export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose; export declare type BodyAnnotation = BodyAnnotationBlazePose | BodyAnnotationEfficientPose;
@ -140,7 +140,7 @@ declare function browserFiles(files: File[]): IOHandler;
declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler; declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;
/** draw processed canvas */ /** draw processed canvas */
declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): Promise<void>; declare function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas): void;
/** /**
* Concatenate a number of ArrayBuffers into one. * Concatenate a number of ArrayBuffers into one.
@ -509,7 +509,7 @@ export declare type Events = 'create' | 'load' | 'image' | 'result' | 'warmup' |
export declare type ExternalCanvas = typeof env.Canvas; export declare type ExternalCanvas = typeof env.Canvas;
/** draw detected faces */ /** draw detected faces */
declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function face(inCanvas: AnyCanvas, result: FaceResult[], drawOptions?: Partial<DrawOptions>): void;
/** Anti-spoofing part of face configuration */ /** Anti-spoofing part of face configuration */
export declare interface FaceAntiSpoofConfig extends GenericConfig { export declare interface FaceAntiSpoofConfig extends GenericConfig {
@ -780,7 +780,7 @@ export declare interface GenericConfig {
} }
/** draw detected gestures */ /** draw detected gestures */
declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function gesture(inCanvas: AnyCanvas, result: GestureResult[], drawOptions?: Partial<DrawOptions>): void;
/** Controlls gesture detection */ /** Controlls gesture detection */
export declare interface GestureConfig { export declare interface GestureConfig {
@ -1038,7 +1038,7 @@ export declare class GraphModel<ModelURL extends Url = string | io.IOHandler> im
} }
/** draw detected hands */ /** draw detected hands */
declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function hand(inCanvas: AnyCanvas, result: HandResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all hand detection specific options */ /** Configures all hand detection specific options */
export declare interface HandConfig extends GenericConfig { export declare interface HandConfig extends GenericConfig {
@ -2022,7 +2022,7 @@ declare type NamedTensorsMap = {
declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64'; declare type NumericDataType = 'float32' | 'int32' | 'bool' | 'complex64';
/** draw detected objects */ /** draw detected objects */
declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function object(inCanvas: AnyCanvas, result: ObjectResult[], drawOptions?: Partial<DrawOptions>): void;
/** Configures all object detection specific options */ /** Configures all object detection specific options */
export declare interface ObjectConfig extends GenericConfig { export declare interface ObjectConfig extends GenericConfig {
@ -2065,7 +2065,7 @@ declare type OnProgressCallback = (fraction: number) => void;
declare const options: DrawOptions; declare const options: DrawOptions;
/** draw combined person results instead of individual detection result objects */ /** draw combined person results instead of individual detection result objects */
declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): Promise<void>; declare function person(inCanvas: AnyCanvas, result: PersonResult[], drawOptions?: Partial<DrawOptions>): void;
/** Person getter /** Person getter
* - Triggers combining all individual results into a virtual person object * - Triggers combining all individual results into a virtual person object