
The NextJS ONNX Runtime Web Template serves as an outstanding foundation for developers looking to leverage ONNX Runtime for machine learning inferencing directly in the browser. This template, built on Next.js, integrates seamlessly with PyTorch, enabling the processing of images using popular models such as SqueezeNet, ResNet, and MobileNet. It offers a robust platform for testing and deploying applications with diverse machine-learning capabilities.
Equipped with essential tools such as webpack and typescript, this template streamlines the development process, making it easy to get started with real-time inferencing. Its user-friendly approach caters not only to seasoned developers but also provides an engaging environment for newcomers to experiment with machine learning in web applications.

Next.js is a React-based web framework that enables server-side rendering, static site generation, and other powerful features for building modern web applications.
React is a widely used JavaScript library for building user interfaces and single-page applications. It follows a component-based architecture and uses a virtual DOM to efficiently update and render UI components
ESLint is a linter for JavaScript that analyzes code to detect and report on potential problems and errors, as well as enforce consistent code style and best practices, helping developers to write cleaner, more maintainable code.
TypeScript is a superset of JavaScript, providing optional static typing, classes, interfaces, and other features that help developers write more maintainable and scalable code. TypeScript's static typing system can catch errors at compile-time, making it easier to build and maintain large applications.