Method, system and apparatus for image orientation correction

Abstract

Broadly speaking, the present techniques generally relates to methods, systems and apparatuses for performing image orientation correction, i.e. correcting or adjusting images that are tilted. In particular, the present application relates to a computer-implemented method for generating a training dataset for training a machine learning, ML, model using federated learning to perform image orientation correction, and methods for training the ML model using the generated training dataset. Advantageously, the method to generate a training dataset enables a diverse training dataset to be generated while maintaining user data privacy, where the diversity refers to the range of image tilt angles represented by the dataset. The present application also provides methods for training the ML model using the generated training dataset.