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A concept on how Machine Learning (ML) can be integrated on Web apps

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nzuqi/tensorflow-handpose-drag

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Tensorflow-handpose-drag

This is a concept on how Machine Learning (ML) can be integrated on Web apps.

It uses a pre-trained Tensorflow.js model, Hand Pose Detection

Here's a list of available pre-trained models for you to play with; https://github.com/tensorflow/tfjs-models

This project was generated with Angular CLI version 15.2.10.

Development server

Run ng serve for a dev server. Navigate to http://localhost:4200/. The application will automatically reload if you change any of the source files.

Code scaffolding

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.

Build

Run ng build to build the project. The build artifacts will be stored in the dist/ directory.

Running unit tests

Run ng test to execute the unit tests via Karma.

Running end-to-end tests

Run ng e2e to execute the end-to-end tests via a platform of your choice. To use this command, you need to first add a package that implements end-to-end testing capabilities.

Further help

To get more help on the Angular CLI use ng help or go check out the Angular CLI Overview and Command Reference page.