How to Deploy a YOLOv8 Model Using Roboflow and Repl.it

Deploying a computer vision model to the browser offers the advantage of cross-device compatibility without the need for device-specific code and enhances accessibility, particularly for mobile use. The guide details deploying a YOLOv8 model using Roboflow and Repl.it, emphasizing its utility for testing and collaboration. A practical application, a money counting app beneficial for the visually impaired, is developed using a dataset from Roboflow Universe. The process involves collecting and uploading data to Roboflow, creating a dataset version, training a model on Google Colab, and deploying it using Repl.it. The guide also illustrates modifying a Repl.it demo project to use a custom model, enabling predictions via a webcam feed. Once configured, the model can be shared with the Repl.it community, showcasing its ability to identify US currency through a browser-based interface.