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import numpy as np
import pandas as pd
import keras
img_rows, img_cols = 30, 20
num_classes = 36
def data_prep(raw):
num_images = raw.shape[0]
x_as_array = raw.values[:,1:]
x_shaped_array = x_as_array.reshape(num_images, img_rows, img_cols, 1)
out_x = x_shaped_array / 255
def load_data():
df = pd.read_csv("data/Mercosul_56_30x20.csv")
df = df.sample(frac=1, random_state=10)
x, y = data_prep(df)
train_samples = int(y.shape[0] * 0.75)
x_train, x_test = x[:train_samples, :], x[train_samples:, :]