contrastive-unpaired-translation

The 'contrastive-unpaired-translation' tool is a machine learning model designed for image-to-image translation tasks. It leverages a contrastive learning approach to translate images from one domain to another without paired data. This is particularly useful in scenarios where direct correspondences between images are not available. For example, it can be used to translate satellite images into maps or to convert sketches into realistic images. The model is trained using a contrastive loss function that encourages similar images to be mapped to similar representations, even in the absence of paired data.