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bendangnuksung / Image Outpainting

🏖 Keras Implementation of Painting outside the box

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Keras implementation of Image OutPainting

This is an implementation of Painting Outside the Box: Image Outpainting paper from Standford University. Some changes have been made to work with 256*256 image:

  • Added Identity loss i.e from generated image to the original image
  • Removed patches from training data. (training pipeline)
  • Replaced masking with cropping. (training pipeline)
  • Added convolution layers.

Results

The model was train with 3500 scrapped beach data with agumentation totalling upto 10500 images for 25 epochs. Demo

Recursive painting

Demo

Install Requirements

sudo apt-get install curl
sudo pip3 install -r requirements.txt

Get Started

  1. Prepare Data:
    # Downloads the beach data and converts to numpy batch data
    # saves the Numpy batch data to 'data/prepared_data/'
    sh prepare_data.sh
    
  2. Build Model
    • To build Model from scratch you can directly run 'outpaint.ipynb'
      OR
    • You can Download my trained model and move it to 'checkpoint/' and run it.

References

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