Age transformation tool

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Why use Blu Age? Proven Solutions Blu Age products have been successfully used in more than projects. PhotoShop : You probably will not be surprised to learn that PhotoShop offers the ability to show age progression. This handy tutorial shows you how to make it happen. Face of the Future : You can look and see how you might change over the years. Upload your own picture and see how you are likely to change in the future.

A great, free tool that provides you with interesting insight. MyWebFace : You can see your age progression with this animation. Turn yourself into a cartoon figure — and then watch that figure age. Also helps you turn it into an avatar that you can use on your profile pages. Upload your photo, and then get an idea of how you will look after 20 years have passed.

ThatsMyFace : Transform your face. See your face in 3D, see yourself as older and even create personalized gifts and merchandise using this web tool. One of the funnest options is creating a personalized action figure using your face. Face Transformer : Use this web tool from the Perception Laboratory to change how you look.

Cool tool also lets you change race or sex on top of age. You can also place yourself in a famous painting, or even see what you look like as a Manga character. GIMP : You can manipulate pictures, including based on age, using the GNU program that allows you to accomplish interesting feats with your face.

Helpful and fun Portrait Professional : Lets you change images and more. You can also add age, on top of being able to retouch and enhance photos. HourFace : This is actually an iPhone app that allows you to age an image. You can do even do it by the hour, to see how much older you can look in one day. Your Shape Picture Progress : Helps you take pictures over time, and then create a movie showing your progression. This code requires PyTorch and torchvision to be installed, please go to PyTorch.

We tested our code on PyTorch 1. If any of these packages are not installed on your computer, you can install them using the supplied requirements. You can either run the demo localy or explore it in Colab. Please refer to Using your own images for guidelines on what images are good to use. This parameter controls the number of interpolated frames between every 2 anchor classes.

Increasing it will reduce the length of the output video. If you wish to train the model on a new dataset, arange it in the following structure:. This code is inspired by pix2pix-HD and style-based-gan-pytorch.

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