coding_nn_init_load_data.py

# Loading packages
import sys

import h5py
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

sys.path.append("../scripts/")
from coding_neural_network_from_scratch import (L_model_forward,
                                                compute_cost,
                                                L_model_backward,
                                                update_parameters,
                                                accuracy)
from load_dataset import load_dataset_catvsdog

%matplotlib inline
sns.set_context("notebook")
plt.style.use("fivethirtyeight")

X, Y = load_dataset_catvsdog("../data")

# show a sample of of a cat and a dog image
index_cat = np.argmax(Y); index_dog = np.argmin(Y)
plt.subplot(1, 2, 1)
plt.imshow(X[:, index_cat].reshape(150, 150, 3))
plt.axis("off")
plt.subplot(1, 2, 2)
plt.imshow(X[:, index_dog].reshape(150, 150, 3))
plt.axis("off");

# standarize the data
X = X / 255