mirror of https://github.com/vladmandic/human
build and docs cleanup
Vladimir Mandic
parent
a710ef88ec
commit
f3411437a0
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@ -9,11 +9,12 @@
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## Changelog
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## Changelog
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### **HEAD -> main** 2021/10/28 mandic00@live.com
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### **2.4.3** 2021/10/28 mandic00@live.com
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### **2.4.3** 2021/10/28 mandic00@live.com
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- additional human.performance counters
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### **origin/main** 2021/10/27 mandic00@live.com
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### **2.4.2** 2021/10/27 mandic00@live.com
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### **2.4.2** 2021/10/27 mandic00@live.com
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@ -58,8 +58,8 @@ Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) ap
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- [**Home**](https://github.com/vladmandic/human/wiki)
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- [**Home**](https://github.com/vladmandic/human/wiki)
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- [**Installation**](https://github.com/vladmandic/human/wiki/Install)
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- [**Installation**](https://github.com/vladmandic/human/wiki/Install)
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- [**Usage & Functions**](https://github.com/vladmandic/human/wiki/Usage)
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- [**Usage & Functions**](https://github.com/vladmandic/human/wiki/Usage)
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- [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration)
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- [**Configuration Details**](https://github.com/vladmandic/human/wiki/Config)
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- [**Output Details**](https://github.com/vladmandic/human/wiki/Outputs)
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- [**Result Details**](https://github.com/vladmandic/human/wiki/Result)
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- [**Caching & Smoothing**](https://github.com/vladmandic/human/wiki/Caching)
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- [**Caching & Smoothing**](https://github.com/vladmandic/human/wiki/Caching)
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- [**Face Recognition & Face Description**](https://github.com/vladmandic/human/wiki/Embedding)
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- [**Face Recognition & Face Description**](https://github.com/vladmandic/human/wiki/Embedding)
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- [**Gesture Recognition**](https://github.com/vladmandic/human/wiki/Gesture)
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- [**Gesture Recognition**](https://github.com/vladmandic/human/wiki/Gesture)
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17
TODO.md
17
TODO.md
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@ -14,21 +14,20 @@
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- TFLite Models: <https://js.tensorflow.org/api_tflite/0.0.1-alpha.4/>
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- TFLite Models: <https://js.tensorflow.org/api_tflite/0.0.1-alpha.4/>
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- Body segmentation: `robust-video-matting`
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- Body segmentation: `robust-video-matting`
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<br><hr><br>
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## Known Issues
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### Type Definitions
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- `tfjs.esm.d.ts` missing namespace `OptimizerConstructors`
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- exports from `match` are marked as private
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#### WebGPU
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#### WebGPU
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Experimental support only until support is officially added in Chromium
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Experimental support only until support is officially added in Chromium
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- Performance issues:
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- Performance issues:
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<https://github.com/tensorflow/tfjs/issues/5689>
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<https://github.com/tensorflow/tfjs/issues/5689>
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<br><hr><br>
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## Known Issues
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- `tfjs.esm.d.ts` missing namespace `OptimizerConstructors`
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- exports from `match` are marked as private
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<br>
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### Face Detection
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### Face Detection
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Enhanced rotation correction for face detection is not working in NodeJS due to missing kernel op in TFJS
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Enhanced rotation correction for face detection is not working in NodeJS due to missing kernel op in TFJS
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@ -44,9 +44,9 @@ async function webCam() {
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dom.canvas.width = dom.video.videoWidth;
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dom.canvas.width = dom.video.videoWidth;
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dom.canvas.height = dom.video.videoHeight;
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dom.canvas.height = dom.video.videoHeight;
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const track = stream.getVideoTracks()[0];
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const track = stream.getVideoTracks()[0];
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const capabilities = track.getCapabilities();
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const capabilities = track.getCapabilities ? track.getCapabilities() : "";
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const settings = track.getSettings();
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const settings = track.getSettings ? track.getSettings() : "";
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const constraints = track.getConstraints();
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const constraints = track.getConstraints ? track.getConstraints() : "";
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log("video:", dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities });
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log("video:", dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities });
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dom.canvas.onclick = () => {
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dom.canvas.onclick = () => {
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if (dom.video.paused)
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if (dom.video.paused)
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10
package.json
10
package.json
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"tensorflow"
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"tensorflow"
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],
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],
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"devDependencies": {
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"devDependencies": {
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"@tensorflow/tfjs": "^3.11.0",
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"@tensorflow/tfjs-backend-cpu": "^3.11.0",
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"@tensorflow/tfjs-backend-cpu": "^3.11.0",
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"@tensorflow/tfjs-backend-wasm": "^3.11.0",
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"@tensorflow/tfjs-backend-wasm": "^3.11.0",
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"@tensorflow/tfjs-backend-webgl": "^3.11.0",
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"@tensorflow/tfjs-backend-webgl": "^3.11.0",
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"@tensorflow/tfjs-core": "^3.11.0",
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"@tensorflow/tfjs-core": "^3.11.0",
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"@tensorflow/tfjs-data": "^3.11.0",
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"@tensorflow/tfjs-data": "^3.11.0",
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"@tensorflow/tfjs-layers": "^3.11.0",
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"@tensorflow/tfjs-layers": "^3.11.0",
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"@tensorflow/tfjs-node-gpu": "^3.11.0",
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"@tensorflow/tfjs-node": "^3.11.0",
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"@tensorflow/tfjs-node": "^3.11.0",
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"@tensorflow/tfjs": "^3.11.0",
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"@tensorflow/tfjs-node-gpu": "^3.11.0",
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"@types/node": "^16.11.6",
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"@types/node": "^16.11.6",
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"@typescript-eslint/eslint-plugin": "^5.2.0",
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"@typescript-eslint/eslint-plugin": "^5.2.0",
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"@typescript-eslint/parser": "^5.2.0",
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"@typescript-eslint/parser": "^5.2.0",
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"canvas": "^2.8.0",
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"canvas": "^2.8.0",
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"dayjs": "^1.10.7",
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"dayjs": "^1.10.7",
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"esbuild": "^0.13.10",
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"esbuild": "^0.13.10",
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"eslint": "8.1.0",
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"eslint-config-airbnb-base": "^14.2.1",
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"eslint-config-airbnb-base": "^14.2.1",
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"eslint-plugin-html": "^6.2.0",
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"eslint-plugin-html": "^6.2.0",
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"eslint-plugin-import": "^2.25.2",
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"eslint-plugin-import": "^2.25.2",
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"eslint-plugin-json": "^3.1.0",
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"eslint-plugin-json": "^3.1.0",
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"eslint-plugin-node": "^11.1.0",
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"eslint-plugin-node": "^11.1.0",
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"eslint-plugin-promise": "^5.1.1",
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"eslint-plugin-promise": "^5.1.1",
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"eslint": "8.1.0",
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"long": "4.0.0",
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"long": "4",
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"node-fetch": "^3.0.0",
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"node-fetch": "^3.0.0",
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"rimraf": "^3.0.2",
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"rimraf": "^3.0.2",
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"seedrandom": "^3.0.5",
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"seedrandom": "^3.0.5",
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"tslib": "^2.3.1",
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"tslib": "^2.3.1",
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"typedoc": "0.22.7",
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"typedoc": "0.22.7",
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"typescript": "4.4.4"
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"typescript": "4.4.4"
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},
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"dependencies": {
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}
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}
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}
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}
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244
src/config.ts
244
src/config.ts
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*/
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*/
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export interface Config {
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export interface Config {
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/** Backend used for TFJS operations
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/** Backend used for TFJS operations
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* Valid build-in backends are:
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* valid build-in backends are:
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* - Browser: `cpu`, `wasm`, `webgl`, `humangl`
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* - Browser: `cpu`, `wasm`, `webgl`, `humangl`, `webgpu`
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* - NodeJS: `cpu`, `wasm`, `tensorflow`
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* - NodeJS: `cpu`, `wasm`, `tensorflow`
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*
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* default: `humangl` for browser and `tensorflow` for nodejs
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* Experimental:
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* - Browser: `webgpu` - requires custom build of `tfjs-backend-webgpu`
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*
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* Defaults: `humangl` for browser and `tensorflow` for nodejs
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*/
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*/
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backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu',
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backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu',
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// backend: string;
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/** Path to *.wasm files if backend is set to `wasm`
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/** Path to *.wasm files if backend is set to `wasm`
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* - if not set, auto-detects to link to CDN `jsdelivr` when running in browser
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* default: auto-detects to link to CDN `jsdelivr` when running in browser
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*/
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*/
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wasmPath: string,
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wasmPath: string,
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/** Print debug statements to console */
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/** Print debug statements to console
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* default: `true`
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*/
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debug: boolean,
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debug: boolean,
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/** Perform model loading and inference concurrently or sequentially */
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/** Perform model loading and inference concurrently or sequentially
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* default: `true`
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*/
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async: boolean,
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async: boolean,
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/** What to use for `human.warmup()`
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/** What to use for `human.warmup()`
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* - warmup pre-initializes all models for faster inference but can take significant time on startup
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* - warmup pre-initializes all models for faster inference but can take significant time on startup
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* - used by `webgl`, `humangl` and `webgpu` backends
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* default: `full`
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*/
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*/
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warmup: 'none' | 'face' | 'full' | 'body',
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warmup: 'none' | 'face' | 'full' | 'body',
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// warmup: string;
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// warmup: string;
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/** Base model path (typically starting with file://, http:// or https://) for all models
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/** Base model path (typically starting with file://, http:// or https://) for all models
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* - individual modelPath values are relative to this path
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* - individual modelPath values are relative to this path
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* default: `../models/` for browsers and `file://models/` for nodejs
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*/
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*/
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modelBasePath: string,
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modelBasePath: string,
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/** Cache sensitivity
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/** Cache sensitivity
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* - values 0..1 where 0.01 means reset cache if input changed more than 1%
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* - values 0..1 where 0.01 means reset cache if input changed more than 1%
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* - set to 0 to disable caching
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* - set to 0 to disable caching
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* default: 0.7
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*/
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*/
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cacheSensitivity: number;
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cacheSensitivity: number;
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segmentation: Partial<SegmentationConfig>,
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segmentation: Partial<SegmentationConfig>,
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}
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}
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/** - [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L250) */
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/** - [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L253) */
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const config: Config = {
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const config: Config = {
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backend: '', // select tfjs backend to use, leave empty to use default backend
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backend: '',
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// for browser environments: 'webgl', 'wasm', 'cpu', or 'humangl' (which is a custom version of webgl)
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modelBasePath: '',
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// for nodejs environments: 'tensorflow', 'wasm', 'cpu'
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wasmPath: '',
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// default set to `humangl` for browsers and `tensorflow` for nodejs
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debug: true,
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modelBasePath: '', // base path for all models
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async: true,
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// default set to `../models/` for browsers and `file://models/` for nodejs
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warmup: 'full',
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wasmPath: '', // path for wasm binaries, only used for backend: wasm
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cacheSensitivity: 0.70,
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// default set to download from jsdeliv during Human class instantiation
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skipAllowed: false,
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debug: true, // print additional status messages to console
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filter: {
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async: true, // execute enabled models in parallel
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enabled: true,
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warmup: 'full', // what to use for human.warmup(), can be 'none', 'face', 'full'
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width: 0,
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// warmup pre-initializes all models for faster inference but can take
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height: 0,
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// significant time on startup
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flip: false,
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// only used for `webgl` and `humangl` backends
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return: true,
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cacheSensitivity: 0.70, // cache sensitivity
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brightness: 0,
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// values 0..1 where 0.01 means reset cache if input changed more than 1%
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contrast: 0,
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// set to 0 to disable caching
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sharpness: 0,
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skipAllowed: false, // internal & dynamic
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blur: 0,
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filter: { // run input through image filters before inference
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saturation: 0,
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// image filters run with near-zero latency as they are executed on the GPU
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hue: 0,
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enabled: true, // enable image pre-processing filters
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negative: false,
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width: 0, // resize input width
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sepia: false,
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height: 0, // resize input height
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vintage: false,
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// if both width and height are set to 0, there is no resizing
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kodachrome: false,
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// if just one is set, second one is scaled automatically
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technicolor: false,
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// if both are set, values are used as-is
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polaroid: false,
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flip: false, // flip input as mirror image
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pixelate: 0,
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return: true, // return processed canvas imagedata in result
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brightness: 0, // range: -1 (darken) to 1 (lighten)
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contrast: 0, // range: -1 (reduce contrast) to 1 (increase contrast)
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sharpness: 0, // range: 0 (no sharpening) to 1 (maximum sharpening)
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blur: 0, // range: 0 (no blur) to N (blur radius in pixels)
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saturation: 0, // range: -1 (reduce saturation) to 1 (increase saturation)
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hue: 0, // range: 0 (no change) to 360 (hue rotation in degrees)
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negative: false, // image negative
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sepia: false, // image sepia colors
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vintage: false, // image vintage colors
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kodachrome: false, // image kodachrome colors
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technicolor: false, // image technicolor colors
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polaroid: false, // image polaroid camera effect
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pixelate: 0, // range: 0 (no pixelate) to N (number of pixels to pixelate)
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},
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},
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gesture: {
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gesture: {
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enabled: true, // enable gesture recognition based on model results
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enabled: true,
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},
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},
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face: {
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face: {
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enabled: true, // controls if specified modul is enabled
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enabled: true,
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// face.enabled is required for all face models:
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// detector, mesh, iris, age, gender, emotion
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// (note: module is not loaded until it is required)
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detector: {
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detector: {
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modelPath: 'blazeface.json', // detector model, can be absolute path or relative to modelBasePath
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modelPath: 'blazeface.json',
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rotation: true, // use best-guess rotated face image or just box with rotation as-is
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rotation: true,
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// false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees
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maxDetected: 1,
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// this parameter is not valid in nodejs
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skipFrames: 99,
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maxDetected: 1, // maximum number of faces detected in the input
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skipTime: 2500,
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// should be set to the minimum number for performance
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minConfidence: 0.2,
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skipFrames: 99, // how many max frames to go without re-running the face bounding box detector
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iouThreshold: 0.1,
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// only used when cacheSensitivity is not zero
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return: false,
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skipTime: 2500, // how many ms to go without re-running the face bounding box detector
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// only used when cacheSensitivity is not zero
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minConfidence: 0.2, // threshold for discarding a prediction
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iouThreshold: 0.1, // ammount of overlap between two detected objects before one object is removed
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return: false, // return extracted face as tensor
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// in which case user is reponsible for disposing the tensor
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},
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},
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mesh: {
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mesh: {
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enabled: true,
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enabled: true,
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modelPath: 'facemesh.json', // facemesh model, can be absolute path or relative to modelBasePath
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modelPath: 'facemesh.json',
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},
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},
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iris: {
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iris: {
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enabled: true,
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enabled: true,
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modelPath: 'iris.json', // face iris model
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modelPath: 'iris.json',
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// can be either absolute path or relative to modelBasePath
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},
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},
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emotion: {
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emotion: {
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enabled: true,
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enabled: true,
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minConfidence: 0.1, // threshold for discarding a prediction
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minConfidence: 0.1,
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skipFrames: 99, // how max many frames to go without re-running the detector
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skipFrames: 99,
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// only used when cacheSensitivity is not zero
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skipTime: 1500,
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skipTime: 1500, // how many ms to go without re-running the face bounding box detector
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modelPath: 'emotion.json',
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// only used when cacheSensitivity is not zero
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modelPath: 'emotion.json', // face emotion model, can be absolute path or relative to modelBasePath
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},
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},
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description: {
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description: {
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enabled: true, // to improve accuracy of face description extraction it is
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enabled: true,
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// recommended to enable detector.rotation and mesh.enabled
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modelPath: 'faceres.json',
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modelPath: 'faceres.json', // face description model
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skipFrames: 99,
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// can be either absolute path or relative to modelBasePath
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skipTime: 3000,
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skipFrames: 99, // how many max frames to go without re-running the detector
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minConfidence: 0.1,
|
||||||
// only used when cacheSensitivity is not zero
|
|
||||||
skipTime: 3000, // how many ms to go without re-running the face bounding box detector
|
|
||||||
// only used when cacheSensitivity is not zero
|
|
||||||
minConfidence: 0.1, // threshold for discarding a prediction
|
|
||||||
},
|
},
|
||||||
|
|
||||||
antispoof: {
|
antispoof: {
|
||||||
enabled: false,
|
enabled: false,
|
||||||
skipFrames: 99, // how max many frames to go without re-running the detector
|
skipFrames: 99,
|
||||||
// only used when cacheSensitivity is not zero
|
skipTime: 4000,
|
||||||
skipTime: 4000, // how many ms to go without re-running the face bounding box detector
|
modelPath: 'antispoof.json',
|
||||||
// only used when cacheSensitivity is not zero
|
|
||||||
modelPath: 'antispoof.json', // face description model
|
|
||||||
// can be either absolute path or relative to modelBasePath
|
|
||||||
},
|
},
|
||||||
},
|
},
|
||||||
|
|
||||||
body: {
|
body: {
|
||||||
enabled: true,
|
enabled: true,
|
||||||
modelPath: 'movenet-lightning.json', // body model, can be absolute path or relative to modelBasePath
|
modelPath: 'movenet-lightning.json',
|
||||||
// can be 'posenet', 'blazepose', 'efficientpose', 'movenet-lightning', 'movenet-thunder'
|
|
||||||
detector: {
|
detector: {
|
||||||
modelPath: '', // optional body detector
|
modelPath: '',
|
||||||
},
|
},
|
||||||
maxDetected: -1, // maximum number of people detected in the input
|
maxDetected: -1,
|
||||||
// should be set to the minimum number for performance
|
minConfidence: 0.3,
|
||||||
// only valid for posenet and movenet-multipose as other models detects single pose
|
skipFrames: 1,
|
||||||
// set to -1 to autodetect based on number of detected faces
|
skipTime: 200,
|
||||||
minConfidence: 0.3, // threshold for discarding a prediction
|
},
|
||||||
skipFrames: 1, // how many max frames to go without re-running the detector
|
|
||||||
// only used when cacheSensitivity is not zero
|
|
||||||
skipTime: 200, // how many ms to go without re-running the face bounding box detector
|
|
||||||
// only used when cacheSensitivity is not zero
|
|
||||||
},
|
|
||||||
|
|
||||||
hand: {
|
hand: {
|
||||||
enabled: true,
|
enabled: true,
|
||||||
rotation: true, // use best-guess rotated hand image or just box with rotation as-is
|
rotation: true,
|
||||||
// false means higher performance, but incorrect finger mapping if hand is inverted
|
skipFrames: 99,
|
||||||
// only valid for `handdetect` variation
|
skipTime: 2000,
|
||||||
skipFrames: 99, // how many max frames to go without re-running the hand bounding box detector
|
minConfidence: 0.50,
|
||||||
// only used when cacheSensitivity is not zero
|
iouThreshold: 0.2,
|
||||||
skipTime: 2000, // how many ms to go without re-running the face bounding box detector
|
maxDetected: -1,
|
||||||
// only used when cacheSensitivity is not zero
|
landmarks: true,
|
||||||
minConfidence: 0.50, // threshold for discarding a prediction
|
|
||||||
iouThreshold: 0.2, // ammount of overlap between two detected objects before one object is removed
|
|
||||||
maxDetected: -1, // maximum number of hands detected in the input
|
|
||||||
// should be set to the minimum number for performance
|
|
||||||
// set to -1 to autodetect based on number of detected faces
|
|
||||||
landmarks: true, // detect hand landmarks or just hand boundary box
|
|
||||||
detector: {
|
detector: {
|
||||||
modelPath: 'handtrack.json', // hand detector model, can be absolute path or relative to modelBasePath
|
modelPath: 'handtrack.json',
|
||||||
// can be 'handdetect' or 'handtrack'
|
|
||||||
},
|
},
|
||||||
skeleton: {
|
skeleton: {
|
||||||
modelPath: 'handskeleton.json', // hand skeleton model, can be absolute path or relative to modelBasePath
|
modelPath: 'handskeleton.json',
|
||||||
},
|
},
|
||||||
},
|
},
|
||||||
|
|
||||||
object: {
|
object: {
|
||||||
enabled: false,
|
enabled: false,
|
||||||
modelPath: 'mb3-centernet.json', // experimental: object detection model, can be absolute path or relative to modelBasePath
|
modelPath: 'mb3-centernet.json',
|
||||||
// can be 'mb3-centernet' or 'nanodet'
|
minConfidence: 0.2,
|
||||||
minConfidence: 0.2, // threshold for discarding a prediction
|
iouThreshold: 0.4,
|
||||||
iouThreshold: 0.4, // ammount of overlap between two detected objects before one object is removed
|
maxDetected: 10,
|
||||||
maxDetected: 10, // maximum number of objects detected in the input
|
skipFrames: 99,
|
||||||
skipFrames: 99, // how many max frames to go without re-running the detector
|
skipTime: 1000,
|
||||||
// only used when cacheSensitivity is not zero
|
|
||||||
skipTime: 1000, // how many ms to go without re-running object detector
|
|
||||||
// only used when cacheSensitivity is not zero
|
|
||||||
},
|
},
|
||||||
|
|
||||||
segmentation: {
|
segmentation: {
|
||||||
enabled: false, // controlls and configures all body segmentation module
|
enabled: false,
|
||||||
// removes background from input containing person
|
modelPath: 'selfie.json',
|
||||||
// if segmentation is enabled it will run as preprocessing task before any other model
|
blur: 8,
|
||||||
// alternatively leave it disabled and use it on-demand using human.segmentation method which can
|
|
||||||
// remove background or replace it with user-provided background
|
|
||||||
modelPath: 'selfie.json', // experimental: object detection model, can be absolute path or relative to modelBasePath
|
|
||||||
// can be 'selfie' or 'meet'
|
|
||||||
blur: 8, // blur segmentation output by n pixels for more realistic image
|
|
||||||
},
|
},
|
||||||
};
|
};
|
||||||
|
|
||||||
|
|
|
||||||
2
wiki
2
wiki
|
|
@ -1 +1 @@
|
||||||
Subproject commit 5e874c076123f1c2b2821b1c37f6005e775465aa
|
Subproject commit 5e89af1004860ea9f302e516699b5e0b4e0a825f
|
||||||
Loading…
Reference in New Issue