SenseCraft AI Client

This is SenseCraft AI Client . It works in conjunction with SenseCraft-AI_Server ↗. It provides the necessary API endpoints and handles the business logic for the frontend application.

Getting Started

Environment & Dependencies

• Nodejs 16+
• Vite 3.x
• Typescript
• Vue3 + Pinia
• CSS framework : Tailwindcss
• UI Component Library: TDesign Web Vue UI

Install Dependencies

pnpm install

Development Mode

pnpm run dev

Open your browser and visit: http://localhost:1430

Building the App

pnpm run build 

By default, the build output will be placed at dist. You may deploy this dist folder to any of your preferred platforms.

Preview App Locally

Once you've built the app, you may preview it locally by running npm run preview command.

$ pnpm run build
$ pnpm run preview

The pnpm run preview command will boot up a local static web server that serves the files from dist at http://localhost:4173. It's an easy way to check if the production build looks OK in your local environment.

The project follows a standard structure to organize its files and folders:

├── index.html
├── frame.html
├── src
│   ├── App.vue
│   ├── api
│   ├── assets
│   ├── components
│   ├── i18n
│   ├── layout
│   ├── main.ts
│   ├── router
│   ├── store
│   ├── types
│   ├── utils
│   ├── view
│   └── vite-env.d.ts
├── public
│   ├── icon_aimodel.svg
│   └── vite.svg
├── README.md
├── auto-imports.d.ts
├── components.d.ts
├── tailwind.config.js
├── tsconfig.json
├── tsconfig.node.json
├── package.json
├── pnpm-lock.yaml
├── postcss.config.js
└── vite.config.ts

The public directory contains the static assets and the main index.html file. The src directory is where the application's source code resides. It includes folders for assets, reusable components, views, store (Pinia store modules), and the main application entry point (App.vue and main.js).

Demo Screenshots

Here are some screenshots showcasing the project's user interface:

• Main page

  

• Full screen

  

• Streams list

  

• Stream Config

  

  Argument	Notes
  Model	Model's Name, use which model for this stream.
  Video	Type Video Input Type [ VideoFile, IP-CAM, USB-CAM ].
  Video	Path Video Path, format decided by "Video Type", if wrong, default video will be used.
  FPS	Frame per second.
  Quality	output stream quality.
  Max	Det maximum number of detections per image.
  Conf	object confidence threshold for detection.
  Track	Track=True, use Tracking .
  Experimental	and lower performance
  Half	use half precision (FP16). improve performance and lower precision

• Settings

  

• About

  

License

This project is licensed under the MIT License.