Aim of the project is to present a platform where scenery images of real-world are transformed into cartoon style images in different styles. Sceneries specifically as they are widely used in various media like games/movies/anime/manga. This project will provide at least two styles for image cartoon-ization. The dataset used will be a selection of images with same artist / same style for accurate transformation of images into the particular artist’s style. The referenced paper belongs to learning based methods, which has been popular recently to stylize images in artistic forms. Amongst all the techniques usable, the application of a Generative Adversarial Network (GAN) is be used for the styling real_x0002_world images that uses 2 loss functions namely content loss and adversarial loss for getting a sharp and clear image.