# Copyright (C) 2018 Sergiu Deitsch
#
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# modification, are permitted provided that the following conditions are met:
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# 1. Redistributions of source code must retain the above copyright notice, this
#    list of conditions and the following disclaimer.
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#    this list of conditions and the following disclaimer in the documentation
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# 3. Neither the name of the copyright holder nor the names of its contributors
#    may be used to endorse or promote products derived from this software without
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from PIL import Image
import numpy as np
import os


def load_dataset(fname=None):
    if fname is None:
        # Assume we are in the utils folder and get the absolute path to the
        # parent directory.
        fname = os.path.abspath(os.path.join(os.path.dirname(__file__),
                                             os.path.pardir))
        fname = os.path.join(fname, 'labels.csv')

    data = np.genfromtxt(fname, dtype=['|S19', '<f8', '|S4'], names=[
                         'path', 'probability', 'type'])
    image_fnames = np.char.decode(data['path'])
    probs = data['probability']
    types = np.char.decode(data['type'])

    def load_cell_image(fname):
        with Image.open(fname) as image:
            return np.asarray(image)

    dir = os.path.dirname(fname)

    images = np.array([load_cell_image(os.path.join(dir, fn))
                       for fn in image_fnames])

    return images, probs, types
