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dataset ( data.h5 ) containing cat or non-cat images download

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import numpy as np
import h5py
 
    # Loading the data (cat/non-cat)
train_dataset = h5py.File('../datasets/train_catvnoncat.h5', "r")
train_set_x_orig = np.array(train_dataset["train_set_x"][:]) # train set features
train_set_y_orig = np.array(train_dataset["train_set_y"][:]) # train set labels
 
test_dataset = h5py.File('../datasets/test_catvnoncat.h5', "r")
test_set_x_orig = np.array(test_dataset["test_set_x"][:]) # test set features
test_set_y_orig = np.array(test_dataset["test_set_y"][:]) # test set labels
 
classes = np.array(test_dataset["list_classes"][:]) # the list of classes
 
train_set_y = train_set_y_orig.reshape((1, train_set_y_orig.shape[0]))
test_set_y = test_set_y_orig.reshape((1, test_set_y_orig.shape[0]))

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dataset ( data.h5 ) containing cat or non-cat images download

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