cnnclassification.py 文件源码

def build_model():
    model = Sequential()

    # ???????4????
    model.add(ZeroPadding2D((1, 1), dim_ordering='th', input_shape=(1, 20, 20)))
    model.add(Convolution2D(32, 3, 3, activation='relu'), dim_ordering='th')

    model.add(ZeroPadding2D((1, 1)))
    model.add(Convolution2D(32, 3, 3, activation='relu', dim_ordering='th'))
    model.add(MaxPooling2D((2, 2), dim_ordering='th'))

    model.add(ZeroPadding2D((1, 1)))
    model.add(Convolution2D(64, 3, 3, activation='relu', dim_ordering='th'))
    model.add(MaxPooling2D((2, 2), dim_ordering='th'))

    model.add(Flatten())
    model.add(Dense(64, activation='relu'))
    model.add(Dropout(0.2))
    model.add(Dense(64, activation='softmax'))

    start = time.time()

    # ??SGD + momentum
    # model.compile????loss??????(????)
    sgd = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=True)
    model.compile(optimizer=sgd, loss='categorical_crossentropy')
    # model.compile(loss="mse", optimizer="rmsprop") # mse kld # Nadam  rmsprop
    print "Compilation Time : ", time.time() - start
    return model