CARTOONING OF IMAGES - USING PYTHON+CV

The project’s primary goal is to create a cartoon image generator that transforms real-world images into cartoons. To recognize a cartoon image’s edges, objects, proportions, and effects, a real image needs to be conversed with a real image. The photo cartooning process is carried out using a novel approach known as the Generative Adversarial Network (GAN). Machine learning frameworks like GAN, which we use in our computer code, may fall into this category. With this framework, real image inputs will be processed by removing noise and other effects. The cartoon image will be generated by applying cartoon effects to the generated losses, and the output will be the generated cartoon image. This project uses the Python OpenCV library. One of the Python libraries that enables image processing is OpenCV.It is mostly used for face recognition, object deduction, picture alteration, and some similar other operations. The real-world image used in this study is created by the CNN network through the GAN operation. This is where image processing operations such as the median filter, edge deduction, and application of RGB colors are performed. As a result, a cartoon image is created.