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Image Colorization Using GANs | Deep Learning | TensorFlow | Python
Other Creator:
Efshal Ahmed
Muhammad Hassan
Have you ever thought about colorizing an old black and white photo of your
parents, grandparents? Well doing it manually (using photoshop) is absolutely painstaking. In deep learning we have studied about Generative Adversarial Networks (GANs) which is an approach of generative modeling. We have made a Deep Learning Project “Image colorization using GANs” in which we input a grayscale image and the GAN will output the colorized image of it. We have used GANs because GANs are effective in learning the loss function. GANs have two major parts Generator and Discriminator. Generator takes b/w input images and generates a synthetic color image of it. Discriminator distinguish from the real data, which one is real and which one is generated/fake. When we trained our model, it gave us very promising results with a very slight difference between a real image and a synthetic image. This model can be used in the case of colorizing old photos as it is quite accurate and effective.
Thanks to GANs.
🔴 GitHub Link (Notebook): https://github.com/OvaizAli/Image-Col...
🔴 Dataset Link : https://drive.google.com/drive/folder...
🔴 Google Collab Link (Notebook): https://colab.research.google.com/dri...
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