image-recognizer/data/mnist_loader.py

import struct

import numpy as np

from neural_net.neural_net import ModelData

class MNISTModelData(ModelData):
    def __init__(self, fn_train_inputs, fn_train_targets, fn_test_inputs, fn_test_targets):
        super().__init__(
            self._get_images_from_idx(fn_train_inputs),
            self._get_labels_from_idx(fn_train_targets),
            self._get_images_from_idx(fn_test_inputs),
            self._get_labels_from_idx(fn_test_targets)
        )
        print(np.array(self.test_inputs[0]).reshape((28, 28)))

    def _get_images_from_idx(self, file):
        with open(file, 'rb') as f:
            magic, size = struct.unpack(">II", f.read(8))
            nrows, ncols = struct.unpack(">II", f.read(8))

            data = np.fromfile(f, dtype=np.dtype(np.uint8).newbyteorder('>'))
            data = data.reshape((size, nrows * ncols)) / 255

            return 1 - data

    def _get_labels_from_idx(self, file):
        with open(file, 'rb') as f:
            magic, size = struct.unpack(">II", f.read(8))
            data = np.fromfile(f, dtype=np.dtype(np.uint8).newbyteorder('>'))
            return data