Loading Custom Dataset via Keras

Question

I’ve got a simple GAN model (Keras-based) that I use for handwritten digit image generation based on the MNIST dataset. I want to create a similar dataset for Keras using raw image data from the Sokoto Coventry Fingerprint Dataset (SOCOFing), which consists of 6000 different black and white fingerprint image samples, and apply it to the same GAN model. The problem is — I’m stuck with creating and loading/processing the custom dataset.

This is the code from the model that I use for MNIST:

import os
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
from keras.layers import Input
from keras.models import Model, Sequential
from keras.layers.core import Dense, Dropout
from keras.layers.advanced_activations import LeakyReLU
from keras.datasets import mnist
from tensorflow.keras.optimizers import Adam
from keras import initializers

os.environ["KERAS_BACKEND"] = "tensorflow"

np.random.seed(10)

random_dim = 100

def load_mnist_data():
    (x_train, y_train), (x_test, y_test) = mnist.load_data()
    x_train = (x_train.astype(np.float32) - 127.5)/127.5
    x_train = x_train.reshape(60000, 784)
    return (x_train, y_train, x_test, y_test)

For experimentation purposes, I’ve created a smaller version of the SOCOFing dataset that contains 500 samples only. The code for the dataset generator is as follows:

from PIL import Image
import os
import numpy as np

path_to_files = "./fingerprints/"    
vectorized_images_X = []
vectorized_images_Y = []

for _, file in enumerate(os.listdir(path_to_files)):
    image = Image.open(path_to_files + file)
    image_array = np.array(image)
    vectorized_images_X.append(image_array)
    vectorized_images_Y.append(image_array)
np.savez("./fingerprints.npz",DataX=vectorized_images_X,DataY=vectorized_images_Y)
import numpy as np

path = "./fingerprints.npz"
with np.load(path) as data:
    train_data = data['DataX']
    print(train_data)
    test_data = data['DataY']
    print(test_data)

So now I’ve got a *.npz file but don’t know how to inject it into the model. Please advise.

user_14290681 · Answer

Here is Sample code to insert any .npz file, You can refer this code.

DATA_URL = 'https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz'

path = tf.keras.utils.get_file('mnist.npz', DATA_URL)
with np.load(path) as data:
  train_examples = data['x_train']
  train_labels = data['y_train']
  test_examples = data['x_test']
  test_labels = data['y_test']

For more details,you can follow this link.

Loading Custom Dataset via Keras

1 Answers