How to Classify Images with DINOv2

In May 2023, James Gallagher published a guide on the Roboflow Blog detailing how to classify images using DINOv2 embeddings alongside a C-Support Vector Classification (SVC) linear classification model. The guide walks users through the process of setting up the necessary dependencies, downloading and preparing the MIT Indoor Scene Recognition dataset, computing embeddings for each image using the DINOv2 model, and ultimately training an SVC model with these embeddings to classify images. The tutorial emphasizes the use of GPU for efficiency and provides an interactive notebook for hands-on practice, suggesting alternatives like Google Colab for those without direct access to a GPU. The guide culminates in successfully classifying an image and highlights the comparable accuracy of the SVC model to CLIP's performance on the same dataset.

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