mirror of https://github.com/vladmandic/human
update typescript
parent
eb65cabf31
commit
7517ac2d8f
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@ -9,8 +9,9 @@
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## Changelog
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## Changelog
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### **HEAD -> main** 2021/11/16 mandic00@live.com
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### **HEAD -> main** 2021/11/17 mandic00@live.com
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- optimize centernet
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- cache frequent tf constants
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- cache frequent tf constants
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- add extra face rotation prior to mesh
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- add extra face rotation prior to mesh
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- release 2.5.2
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- release 2.5.2
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@ -331,7 +331,7 @@ For more info, see [**Configuration Details**](https://github.com/vladmandic/hum
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<br><hr><br>
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<br><hr><br>
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`Human` library is written in `TypeScript` [4.4](https://www.typescriptlang.org/docs/handbook/intro.html)
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`Human` library is written in `TypeScript` [4.5](https://www.typescriptlang.org/docs/handbook/intro.html)
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Conforming to latest `JavaScript` [ECMAScript version 2021](https://262.ecma-international.org/) standard
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Conforming to latest `JavaScript` [ECMAScript version 2021](https://262.ecma-international.org/) standard
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Build target is `JavaScript` [EMCAScript version 2018](https://262.ecma-international.org/11.0/)
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Build target is `JavaScript` [EMCAScript version 2018](https://262.ecma-international.org/11.0/)
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20
TODO.md
20
TODO.md
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@ -43,13 +43,14 @@ MoveNet MultiPose model does not work with WASM backend due to missing F32 broad
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## Pending Release Notes
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## Pending Release Notes
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New:
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New:
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- new demo `demos/faceid` that utilizes multiple algorithm to validate input before triggering face recognition
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- New type definitions rollup
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- new optional model `liveness`
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- New demo `demos/faceid` that utilizes multiple algorithm to validate input before triggering face recognition
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- New optional model `liveness`
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checks if input appears to be a real-world live image or a recording
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checks if input appears to be a real-world live image or a recording
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best used together with `antispoofing` that checks if input appears to have a realistic face
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best used together with `antispoofing` that checks if input appears to have a realistic face
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- new face masking option in `face.config.detector.mask`
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- New face masking option in `face.config.detector.mask`
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result is shading of face image outside of face area which is useful for increased sensitivity of other modules that rely on detected face as input
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result is shading of face image outside of face area which is useful for increased sensitivity of other modules that rely on detected face as input
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- new face crop option in `face.config.detector.cropFactor`
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- New face crop option in `face.config.detector.cropFactor`
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result is user-definable fine-tuning for other modules that rely on detected face as input
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result is user-definable fine-tuning for other modules that rely on detected face as input
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Other:
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Other:
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@ -60,14 +61,3 @@ Other:
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- Documentation overhaul
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- Documentation overhaul
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- Fix for optional `gear`, `ssrnet`, `mobilefacenet` modules
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- Fix for optional `gear`, `ssrnet`, `mobilefacenet` modules
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- Fix for Firefox WebGPU compatibility issue
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- Fix for Firefox WebGPU compatibility issue
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```
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cp tfjs/tfjs.esm.d.ts types/lib/dist/
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node_modules/.bin/api-extractor run --local --verbose
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cp types/human.d.ts dist/human.esm-nobundle.d.ts
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cp types/human.d.ts dist/human.esm.d.ts
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cp types/human.d.ts dist/human.d.ts
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cp types/human.d.ts dist/human.node-gpu.d.ts
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cp types/human.d.ts dist/human.node.d.ts
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cp types/human.d.ts dist/human.node-wasm.d.ts
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```
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@ -54,6 +54,7 @@
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],
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],
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"devDependencies": {
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"devDependencies": {
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"@microsoft/api-extractor": "^7.18.19",
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"@microsoft/api-extractor": "^7.18.19",
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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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@ -62,9 +63,8 @@
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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": "^16.11.7",
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"@types/node": "^16.11.7",
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"@typescript-eslint/eslint-plugin": "^5.4.0",
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"@typescript-eslint/eslint-plugin": "^5.4.0",
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"@typescript-eslint/parser": "^5.4.0",
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"@typescript-eslint/parser": "^5.4.0",
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@ -74,18 +74,18 @@
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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": "^0.13.14",
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"esbuild": "^0.13.14",
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"eslint": "8.2.0",
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"eslint-config-airbnb-base": "^15.0.0",
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"eslint-config-airbnb-base": "^15.0.0",
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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": "^2.25.3",
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"eslint-plugin-import": "^2.25.3",
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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": "8.2.0",
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"node-fetch": "^3.1.0",
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"node-fetch": "^3.1.0",
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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": "0.22.9",
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"typedoc": "0.22.9",
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"typescript": "4.4.4"
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"typescript": "4.5.2"
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}
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}
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}
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}
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@ -24,7 +24,7 @@ export async function load(config: Config): Promise<GraphModel> {
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return model;
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return model;
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}
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}
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export async function predict(image: Tensor, config: Config, idx, count): Promise<number> {
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export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {
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if (!model) return 0;
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if (!model) return 0;
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const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);
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const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);
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const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);
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const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);
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return model;
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return model;
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}
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}
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export async function predict(image: Tensor, config: Config, idx, count): Promise<number> {
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export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {
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if (!model) return 0;
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if (!model) return 0;
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const skipTime = (config.face.liveness?.skipTime || 0) > (now() - lastTime);
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const skipTime = (config.face.liveness?.skipTime || 0) > (now() - lastTime);
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const skipFrame = skipped < (config.face.liveness?.skipFrames || 0);
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const skipFrame = skipped < (config.face.liveness?.skipFrames || 0);
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return model;
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return model;
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}
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}
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export async function predict(image: Tensor, config: Config, idx, count): Promise<Array<{ score: number, emotion: string }>> {
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export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<Array<{ score: number, emotion: string }>> {
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if (!model) return [];
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if (!model) return [];
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const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);
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const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);
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const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);
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const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);
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}
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}
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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export async function predict(image: Tensor, config: Config, idx, count): Promise<{ age: number }> {
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export async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<{ age: number }> {
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if (!model) return { age: 0 };
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if (!model) return { age: 0 };
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const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);
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const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);
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const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);
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const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);
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* Gesture detection algorithm
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* Gesture detection algorithm
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*/
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*/
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import type { GestureResult } from '../result';
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import type { GestureResult, BodyResult, FaceResult, HandResult, Point } from '../result';
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import * as fingerPose from '../hand/fingerpose';
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import * as fingerPose from '../hand/fingerpose';
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/** face gesture type */
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/** face gesture type */
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| 'victory'
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| 'victory'
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| 'thumbs up';
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| 'thumbs up';
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export const body = (res): GestureResult[] => {
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export const body = (res: BodyResult[]): GestureResult[] => {
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if (!res) return [];
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if (!res) return [];
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const gestures: Array<{ body: number, gesture: BodyGesture }> = [];
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const gestures: Array<{ body: number, gesture: BodyGesture }> = [];
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for (let i = 0; i < res.length; i++) {
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for (let i = 0; i < res.length; i++) {
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return gestures;
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return gestures;
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};
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};
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export const face = (res): GestureResult[] => {
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export const face = (res: FaceResult[]): GestureResult[] => {
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if (!res) return [];
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if (!res) return [];
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const gestures: Array<{ face: number, gesture: FaceGesture }> = [];
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const gestures: Array<{ face: number, gesture: FaceGesture }> = [];
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for (let i = 0; i < res.length; i++) {
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for (let i = 0; i < res.length; i++) {
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if (res[i].mesh && res[i].mesh.length > 450) {
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if (res[i].mesh && res[i].mesh.length > 450) {
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const zDiff = res[i].mesh[33][2] - res[i].mesh[263][2];
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const zDiff = (res[i].mesh[33][2] || 0) - (res[i].mesh[263][2] || 0);
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const xDiff = res[i].mesh[33][0] - res[i].mesh[263][0];
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const xDiff = res[i].mesh[33][0] - res[i].mesh[263][0];
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if (Math.abs(zDiff / xDiff) <= 0.15) gestures.push({ face: i, gesture: 'facing center' });
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if (Math.abs(zDiff / xDiff) <= 0.15) gestures.push({ face: i, gesture: 'facing center' });
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else gestures.push({ face: i, gesture: `facing ${zDiff < 0 ? 'left' : 'right'}` });
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else gestures.push({ face: i, gesture: `facing ${zDiff < 0 ? 'left' : 'right'}` });
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if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });
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if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });
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const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));
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const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));
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if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });
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if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });
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const chinDepth = res[i].mesh[152][2];
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const chinDepth = res[i].mesh[152][2] || 0;
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if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });
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if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });
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}
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}
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}
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}
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return gestures;
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return gestures;
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};
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};
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export const iris = (res): GestureResult[] => {
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export const iris = (res: FaceResult[]): GestureResult[] => {
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if (!res) return [];
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if (!res) return [];
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const gestures: Array<{ iris: number, gesture: IrisGesture }> = [];
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const gestures: Array<{ iris: number, gesture: IrisGesture }> = [];
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for (let i = 0; i < res.length; i++) {
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for (let i = 0; i < res.length; i++) {
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return gestures;
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return gestures;
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};
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};
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export const hand = (res): GestureResult[] => {
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export const hand = (res: HandResult[]): GestureResult[] => {
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if (!res) return [];
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if (!res) return [];
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const gestures: Array<{ hand: number, gesture: HandGesture }> = [];
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const gestures: Array<{ hand: number, gesture: HandGesture }> = [];
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for (let i = 0; i < res.length; i++) {
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for (let i = 0; i < res.length; i++) {
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const fingers: Array<{ name: string, position: number }> = [];
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const fingers: Array<{ name: string, position: Point }> = [];
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if (res[i]['annotations']) {
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if (res[i]['annotations']) {
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for (const [finger, pos] of Object.entries(res[i]['annotations'])) {
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for (const [finger, pos] of Object.entries(res[i]['annotations'])) {
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if (finger !== 'palmBase' && Array.isArray(pos) && pos[0]) fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger
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if (finger !== 'palmBase' && Array.isArray(pos) && pos[0]) fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger
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}
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}
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}
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}
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if (fingers && fingers.length > 0) {
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if (fingers && fingers.length > 0) {
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const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));
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const closest = fingers.reduce((best, a) => ((best.position[2] || 0) < (a.position[2] || 0) ? best : a));
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gestures.push({ hand: i, gesture: `${closest.name} forward` as HandGesture });
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gestures.push({ hand: i, gesture: `${closest.name} forward` as HandGesture });
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const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));
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const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));
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gestures.push({ hand: i, gesture: `${highest.name} up` as HandGesture });
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gestures.push({ hand: i, gesture: `${highest.name} up` as HandGesture });
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if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;
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if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;
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else kernels[kernel.name] = kernel.kernelTimeMs;
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else kernels[kernel.name] = kernel.kernelTimeMs;
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}
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}
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const kernelArr: Array<{ name, ms }> = [];
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const kernelArr: Array<{ name: string, ms: number }> = [];
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Object.entries(kernels).forEach((key) => kernelArr.push({ name: key[0], ms: key[1] })); // convert to array
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Object.entries(kernels).forEach((key) => kernelArr.push({ name: key[0], ms: key[1] as unknown as number })); // convert to array
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kernelArr.sort((a, b) => b.ms - a.ms); // sort
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kernelArr.sort((a, b) => b.ms - a.ms); // sort
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kernelArr.length = 20; // crop
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kernelArr.length = 20; // crop
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const res: Record<string, number> = {};
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const res: Record<string, number> = {};
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let gestureRes: GestureResult[] = [];
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let gestureRes: GestureResult[] = [];
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if (this.config.gesture.enabled) {
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if (this.config.gesture.enabled) {
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timeStamp = now();
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timeStamp = now();
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gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];
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gestureRes = [...gesture.face(faceRes as FaceResult[]), ...gesture.body(bodyRes as BodyResult[]), ...gesture.hand(handRes as HandResult[]), ...gesture.iris(faceRes as FaceResult[])];
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if (!this.config.async) this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
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if (!this.config.async) this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);
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else if (this.performance.gesture) delete this.performance.gesture;
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else if (this.performance.gesture) delete this.performance.gesture;
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}
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}
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* TensorFlow Tensor type
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* TensorFlow Tensor type
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* @external
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* @external
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*/
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*/
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export { Tensor, TensorLike, Rank } from '@tensorflow/tfjs-core/dist/index';
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export type { Tensor, TensorLike, Rank } from '@tensorflow/tfjs-core/dist/index';
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/**
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/**
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* TensorFlow GraphModel type
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* TensorFlow GraphModel type
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* @external
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* @external
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*/
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*/
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export { GraphModel } from '@tensorflow/tfjs-converter/dist/index';
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export type { GraphModel } from '@tensorflow/tfjs-converter/dist/index';
|
||||||
|
|
||||||
/** Tensorflow Long type
|
/** Tensorflow Long type
|
||||||
* @external long
|
* @external long
|
||||||
*/
|
*/
|
||||||
// eslint-disable-next-line node/no-missing-import
|
// eslint-disable-next-line node/no-missing-import
|
||||||
export { Long } from 'long';
|
export type { Long } from 'long';
|
||||||
|
|
|
@ -149,6 +149,7 @@ export class Env {
|
||||||
const cpu = { model: '', flags: [] };
|
const cpu = { model: '', flags: [] };
|
||||||
if (this.node && this.platform.startsWith('linux')) {
|
if (this.node && this.platform.startsWith('linux')) {
|
||||||
// eslint-disable-next-line global-require
|
// eslint-disable-next-line global-require
|
||||||
|
/*
|
||||||
const fs = require('fs');
|
const fs = require('fs');
|
||||||
try {
|
try {
|
||||||
const data = fs.readFileSync('/proc/cpuinfo').toString();
|
const data = fs.readFileSync('/proc/cpuinfo').toString();
|
||||||
|
@ -160,7 +161,8 @@ export class Env {
|
||||||
cpu.flags = line.match(/:(.*)/g)[0].replace(':', '').trim().split(' ').sort();
|
cpu.flags = line.match(/:(.*)/g)[0].replace(':', '').trim().split(' ').sort();
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
} catch { /**/ }
|
} catch { }
|
||||||
|
*/
|
||||||
}
|
}
|
||||||
if (!this['cpu']) Object.defineProperty(this, 'cpu', { value: cpu });
|
if (!this['cpu']) Object.defineProperty(this, 'cpu', { value: cpu });
|
||||||
else this['cpu'] = cpu;
|
else this['cpu'] = cpu;
|
||||||
|
|
|
@ -65,7 +65,7 @@ export const minmax = (data: Array<number>) => data.reduce((acc: Array<number>,
|
||||||
}, []);
|
}, []);
|
||||||
|
|
||||||
// helper function: async wait
|
// helper function: async wait
|
||||||
export async function wait(time) {
|
export async function wait(time: number) {
|
||||||
const waiting = new Promise((resolve) => { setTimeout(() => resolve(true), time); });
|
const waiting = new Promise((resolve) => { setTimeout(() => resolve(true), time); });
|
||||||
await waiting;
|
await waiting;
|
||||||
}
|
}
|
||||||
|
|
|
@ -48,10 +48,11 @@ async function warmupCanvas(instance: Human) {
|
||||||
src = null;
|
src = null;
|
||||||
}
|
}
|
||||||
// src = encodeURI('../assets/human-sample-upper.jpg');
|
// src = encodeURI('../assets/human-sample-upper.jpg');
|
||||||
let img;
|
let img: HTMLImageElement;
|
||||||
if (typeof Image !== 'undefined') img = new Image();
|
if (typeof Image !== 'undefined') img = new Image();
|
||||||
// @ts-ignore env.image is an external monkey-patch
|
// @ts-ignore env.image is an external monkey-patch
|
||||||
else if (env.Image) img = new env.Image();
|
else if (env.Image) img = new env.Image();
|
||||||
|
else return;
|
||||||
img.onload = async () => {
|
img.onload = async () => {
|
||||||
const canvas = image.canvas(img.naturalWidth, img.naturalHeight);
|
const canvas = image.canvas(img.naturalWidth, img.naturalHeight);
|
||||||
if (!canvas) {
|
if (!canvas) {
|
||||||
|
@ -103,11 +104,13 @@ async function warmupNode(instance: Human) {
|
||||||
* - only used for `webgl` and `humangl` backends
|
* - only used for `webgl` and `humangl` backends
|
||||||
* @param userConfig?: Config
|
* @param userConfig?: Config
|
||||||
*/
|
*/
|
||||||
export async function warmup(instance: Human, userConfig?: Partial<Config>): Promise<Result | { error }> {
|
export async function warmup(instance: Human, userConfig?: Partial<Config>): Promise<Result> {
|
||||||
const t0 = now();
|
const t0 = now();
|
||||||
instance.state = 'warmup';
|
instance.state = 'warmup';
|
||||||
if (userConfig) instance.config = mergeDeep(instance.config, userConfig) as Config;
|
if (userConfig) instance.config = mergeDeep(instance.config, userConfig) as Config;
|
||||||
if (!instance.config.warmup || instance.config.warmup.length === 0 || instance.config.warmup === 'none') return { error: 'null' };
|
if (!instance.config.warmup || instance.config.warmup.length === 0 || instance.config.warmup === 'none') {
|
||||||
|
return { face: [], body: [], hand: [], gesture: [], object: [], performance: instance.performance, timestamp: now(), persons: [], error: null };
|
||||||
|
}
|
||||||
let res;
|
let res;
|
||||||
return new Promise(async (resolve) => {
|
return new Promise(async (resolve) => {
|
||||||
if (typeof createImageBitmap === 'function') res = await warmupBitmap(instance);
|
if (typeof createImageBitmap === 'function') res = await warmupBitmap(instance);
|
||||||
|
|
|
@ -6,7 +6,7 @@
|
||||||
"outDir": "types",
|
"outDir": "types",
|
||||||
"baseUrl": "./",
|
"baseUrl": "./",
|
||||||
"paths": { "tslib": ["./node_modules/tslib/tslib.d.ts"] },
|
"paths": { "tslib": ["./node_modules/tslib/tslib.d.ts"] },
|
||||||
"lib": ["esnext", "dom", "webworker"],
|
"lib": ["esnext", "dom"],
|
||||||
"allowJs": true,
|
"allowJs": true,
|
||||||
"allowSyntheticDefaultImports": false,
|
"allowSyntheticDefaultImports": false,
|
||||||
"allowUnreachableCode": false,
|
"allowUnreachableCode": false,
|
||||||
|
|
2
wiki
2
wiki
|
@ -1 +1 @@
|
||||||
Subproject commit 799273cb94e64d08280479435cc11daedabd5a60
|
Subproject commit 7b35db4dca9ba3a41b62ec11257a474b2d12c132
|
Loading…
Reference in New Issue