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Tensorflow implementation of fisheye transformation, mimicking the spatial sampling properties in the primate retina

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dicarlolab/retinawarp

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Retina

Tensorflow implementation of fisheye transformation, mimicking the spatial sampling properties of the primate retina

Dependencies

  1. numpy

  2. scipy

  3. scikit-image

  4. tensorflow

How to install

  1. cd [retina_directory_containing_setup.py]

  2. pip install .

How to use

For numpy implementation:

# Import functions
from retina.retina import retina_warp

# read your image
img = imageio.imread('...')
# transform
warp_image(img, output_size=299)

For tensorflow implementation:

# Import functions
from retina.retina_tf import warp_image

# transform
with tf.Session() as sess:
    img = imageio.imread('...')
    retina_img = warp_image(img, output_size=299)
    retina_img = retina_img.eval()

Look here for more details.

Refernce

If you are using this code please refer to our publication:

@article{bashivan2019neural,
  title={Neural population control via deep image synthesis},
  author={Bashivan, Pouya and Kar, Kohitij and DiCarlo, James J},
  journal={Science},
  volume={364},
  number={6439},
  pages={eaav9436},
  year={2019},
  publisher={American Association for the Advancement of Science}
}

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Tensorflow implementation of fisheye transformation, mimicking the spatial sampling properties in the primate retina

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