Exemplos de MnistImageDataReader.ReadData em Python

Exemplo n.º 1

Arquivo: Level6_MnistConvNet.py Projeto: yeshrb/ai-edu

def LoadData(num_output):
    mdr = MnistImageDataReader("image")
    mdr.ReadData()
    mdr.NormalizeX()
    mdr.NormalizeY(NetType.MultipleClassifier, base=0)
    mdr.Shuffle()
    mdr.GenerateValidationSet(k=12)
    return mdr

Exemplo n.º 2

Arquivo: Level5_FashionMnist_DNN.py Projeto: microsoft/ai-edu

def LoadData(mode):
    mdr = MnistImageDataReader(train_x, train_y, test_x, test_y, mode)
    mdr.ReadData()
    mdr.NormalizeX()
    mdr.NormalizeY(NetType.MultipleClassifier, base=0)
    mdr.Shuffle()
    mdr.GenerateValidationSet(k=12)
    return mdr

Exemplo n.º 3

Arquivo: Level4_Base_MNIST.py Projeto: zeblooder/ai-edu

def load_data():
    dataReader = MnistImageDataReader(mode="timestep")
    #dataReader.ReadLessData(10000)
    dataReader.ReadData()
    dataReader.NormalizeX()
    dataReader.NormalizeY(NetType.MultipleClassifier, base=0)
    dataReader.Shuffle()
    dataReader.GenerateValidationSet(k=12)
    return dataReader

Exemplo n.º 4

Arquivo: MnistClassifier.py Projeto: Knowledge-Precipitation-Tribe/Neural-network

def LoadData():
    print("reading data...")
    dr = MnistImageDataReader(mode="vector")
    dr.ReadData()
    dr.NormalizeX()
    dr.NormalizeY(NetType.MultipleClassifier)
    dr.GenerateValidationSet(k=20)
    print(dr.num_validation, dr.num_example, dr.num_test, dr.num_train)
    return dr

Exemplo n.º 5

def LoadData():
    #读取时最好上锁
    lock.acquire()
    print("reading MNIST data...")
    dr = MnistImageDataReader(mode="vector")
    dr.ReadData()
    dr.NormalizeX()
    dr.NormalizeY(NetType.MultipleClassifier)
    dr.GenerateValidationSet(k=20)
    print(dr.num_validation, dr.num_example, dr.num_test, dr.num_train)
    #释放锁
    lock.release()
    return dr

Exemplo n.º 6

def load_data():
    dataReader = MnistImageDataReader(mode="vector")
    dataReader.ReadData()
    dataReader.NormalizeX()
    dataReader.NormalizeY(NetType.MultipleClassifier)
    dataReader.GenerateValidationSet(k=20)

    x_train, y_train = dataReader.XTrain, dataReader.YTrain
    x_test, y_test = dataReader.XTest, dataReader.YTest
    x_val, y_val = dataReader.XDev, dataReader.YDev

    x_train = x_train.reshape(x_train.shape[0], 28 * 28)
    x_test = x_test.reshape(x_test.shape[0], 28 * 28)
    x_val = x_val.reshape(x_val.shape[0], 28 * 28)

    return x_train, y_train, x_test, y_test, x_val, y_val

Exemplo n.º 7

Arquivo: Base_MNIST-keras.py Projeto: Knowledge-Precipitation-Tribe/Recurrent-neural-network

def load_data():
    dataReader = MnistImageDataReader(mode="timestep")
    dataReader.ReadData()
    dataReader.NormalizeX()
    dataReader.NormalizeY(NetType.MultipleClassifier, base=0)
    dataReader.Shuffle()
    dataReader.GenerateValidationSet(k=12)
    x_train, y_train = dataReader.XTrain, dataReader.YTrain
    x_test, y_test = dataReader.XTest, dataReader.YTest
    x_val, y_val = dataReader.XDev, dataReader.YDev
    x_train = x_train.squeeze()
    x_test = x_test.squeeze()
    x_val = x_val.squeeze()

    x_test_raw = dataReader.XTestRaw[0:64]
    y_test_raw = dataReader.YTestRaw[0:64]

    return x_train, y_train, x_test, y_test, x_val, y_val, x_test_raw, y_test_raw