Image classification is one of the most exciting applications of computer vision. It powers technologies in sports analytics, autonomous driving, healthcare diagnostics, and more. In this project, we’re going to take you through a complete, end-to-end workflow for classifying Olympic sports images — from raw data to real-time predictions — using EfficientNetV2, a state-of-the-art deep learning model.
Our journey is divided into three clear steps: dataset preparation, model training, and model inference. We’ll explore how to organize and split images into training and testing sets, fine-tune EfficientNetV2S on the Olympics dataset, and run real-time predictions on new images.
If you’re interested in learning more, you can find the link to the code in the blog post, as well as more tutorials and a newsletter to stay updated. There’s also a full tutorial video available on YouTube.
So, are you ready to dive into the world of image classification and explore its many possibilities?