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Image colorization using conditional Generative Adversial Networks (cGANs) and Dual Decoders

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Automatic Image Colorization

This is a Deep Learning academic project, throughout this project we explored state of the art deep learning techniques for automatic colorization of gray scale images. For further details check this report.

Methods used

  • DDColor
  • Conditional Generative Adversial Networks (cGANS)

Dependancies

  • PyTorch
  • tqdm
  • pandas
  • dotenv
  • skimage
  • PIL
  • numpy

Dataset

The code expects the COCO-2017 dataset stored in the coco-2017-dataset directory . You can set the path for this and other directories in a .env file.

.env File

Follow the structure of .env.template

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Image colorization using conditional Generative Adversial Networks (cGANs) and Dual Decoders

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