Photographs bind us to the past and remind us of people and emotions, but what if they are damaged? For repairing photos that have been damaged, many complex Machine Learning Models have been developed. Bringing ancient photos back to life is one such project that may be used to restore damaged images with practically enhanced high-resolution images.
Despite the fact that certain picture restoration approaches have been proposed in the literature, this challenge has yet to be satisfactorily solved. Due to vast amounts of modified data generated by picture editing tools, image inpainting is a critical task for computer vision applications. We can find image quality enhancement, image restoration, and other applications among these. The GAN model is used to do a quick picture inpainting evaluation.
The GAN model is proposed, and it is used to inpaint the regions that are missing. The image enhancement is also performed to the picture, resulting in a high-resolution image. Our project performs well when it comes to repairing ancient pictures that have become deteriorated.
The suggested Inpainting can be used to remove an undesired object from a picture while preserving the image's backdrop. Adding more functions or methods to the project in order to remove blurring on the boundaries of coherent inpainted patches. To summarise, there is no approach that can inpaint all sorts of picture distortion, although there are some promising outcomes for each category of examined scenarios employing learning techniques.
