yshean

def shear_and_rotate(image_path, img_w, img_h):
    from skimage.io import imread, imsave
    from skimage.transform import resize
    from skimage import transform as transf
    import numpy as np
    from skimage.filters import threshold_otsu
    from scipy.ndimage.interpolation import rotate
    import math

    image = imread(image_path)

yshean

n_in = 784
n_hid = 392 
n_out = n_in
batch_size = 64
nb_epoch = 10
learning_rate = 1e-3

from keras.datasets import mnist
import numpy as np
(X_train, y_train), (X_test, y_test) = mnist.load_data()

yshean

#!/bin/bash

# This is an example of loading test dataset for slice 1_01
# This will serve as a template for loading test dataset for other slices
# Require load-images-test.lua to be hosted on S3
# After this run load-test-slice.sh for each of the other slices

slice='1_01'

cd ~/demos/load-data