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        "author": "Eugenio Nurrito",
        "author_email": "eugi90@gmail.com",
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        "description": "Description\n===========\n\n``scatnetgpu`` is a module to compute the Scattering Network\nrepresentation [1] of an image using the power of a CUDA capable GPU.\n\nThe output of the computation is compatible with the software\n`scatnet <https://github.com/scatnet/scatnet>`__.\n\nRequirements\n============\n\n-  Python 2.7 (not tested yet with Python 3.x)\n-  A CUDA capable GPU with `CUDA\n   toolkit <https://developer.nvidia.com/cuda-toolkit>`__ correctly\n   installed\n\nInstallation\n============\n\nJust run:\n\n.. code:: bash\n\n    $ pip install scatnetgpu\n\nAlternatively, clone the repository and run:\n\n.. code:: bash\n\n    $ pip install .\n\nQuickstart\n==========\n\nLoad or create an image as a Numpy's ndarray. Here we load an image with\nOpenCV:\n\n.. code:: python\n\n    import cv2\n    img = cv2.imread('image.png')\n\nCreate the ScatNet object:\n\n.. code:: python\n\n    from scatnetgpu import ScatNet\n    sn = ScatNet(M=2, J=4, L=6)\n\nPerform the actual transformation\n\n.. code:: python\n\n    out = sn.transform(img)\n\nNow ``out`` contains the features of the Scattering Network\nrepresentation of ``img``.\n\nReferences\n==========\n\n[1] Bruna, Joan, and St\u00e9phane Mallat. \"Invariant scattering convolution\nnetworks.\" IEEE transactions on pattern analysis and machine\nintelligence 35.8 (2013): 1872-1886.",
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