Mckenzie  Osiki

Mckenzie Osiki

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Image Generation Using TensorFlow Keras - Analytics India Magazine

Computer Vision is a wide, deep learning field with enormous applications. Image Generation is one of the most curious applications in Computer Vision. Again, Image Generation has a great collection of tasks; to mention, a few can outperform humans. Most image generation tasks are common for videos, too, since a video is a sequence of images.

A few popular Image Generation tasks are:

  1. Image-to-Image translation (e.g. grayscale image to colour image)
  2. Text-to-Image translation
  3. Super-resolution
  4. Photo-to-Cartoon/Emoji translation
  5. Image inpainting
  6. Image dataset generation
  7. Medical Image generation
  8. Realistic photo generation
  9. Semantic-to-Photo translation
  10. Image blending
  11. Deepfake video generation
  12. 2D-to-3D image translation

One deep learning generative model can perform one or more tasks with a few configuration changes. Some famous image generative models are the original versions and the numerous variants of Variational Autoencoder (VAE), and Generative Adversarial Networks (GAN).

This article discusses the concepts behind image generation and the code implementation of Variational Autoencoder with a practical example using TensorFlow Keras. TensorFlow is one of the top preferred frameworks for deep learning processes. Keras is a high-level API built on top of TensorFlow, which is meant exclusively for deep learning.

The following articles may fulfil the prerequisites by giving an understanding of deep learning and computer vision.

  1. Getting Started With Deep Learning Using TensorFlow Keras
  2. Getting Started With Computer Vision Using TensorFlow Keras

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Image Generation Using TensorFlow Keras - Analytics India Magazine