How to Deploy a Roboflow Model to Lens Studio

Roboflow offers a comprehensive suite of tools for developing computer vision models, facilitating tasks such as data annotation, model training, evaluation, and deployment. This guide outlines the process of deploying a computer vision model to SnapML via Roboflow, starting with creating a Roboflow account and project, uploading and annotating images, and preparing data for training. The guide emphasizes using Roboflow's Label Assist for automatic annotation and recommends a typical 70/20/10 data split for training, validation, and testing. Once the dataset is ready, users can train their model using Roboflow with pre-trained checkpoints like MS COCO, and after training, the model can be exported to SnapML and configured in Lens Studio to create interactive AR experiences. The guide also details the final steps of configuring classes in Lens Studio to ensure the application interprets the model's outputs correctly, allowing users to leverage the capabilities of augmented reality in their applications effectively.