Welcome to our UA-cam video! In this tutorial, we dive into the exciting realm of video classification using MoViNet models. With their efficiency and lightweight nature, MoViNet models are perfect for real-time and resource-constrained applications.
Our comprehensive guide takes you through the entire process of video classification using MoViNet models. We cover everything from data preparation to model training, evaluation, and even inference on new videos.
To train and test the MoViNet model, we utilize a subset of the UCF101 dataset. This diverse dataset contains a wide range of video clips across multiple action categories, making it ideal for training and evaluating video classification models.
Github link for project: github.com/PranayLendave/video_classification
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