我在Keras(我是一个新手)创建了一个模型,并设法很好地训练它.它需要300x300图像,并尝试将它们分为两组.
# size of image in pixel
img_rows, img_cols = 300, 300
# number of classes (here digits 1 to 10)
nb_classes = 2
# number of convolutional filters to use
nb_filters = 16
# size of pooling area for max pooling
nb_pool = 20
# convolution kernel size
nb_conv = 20
X = np.vstack([X_train, X_test]).reshape(-1, 1, img_rows, img_cols)
y = np_utils.to_categorical(np.concatenate([y_train, y_test]), nb_classes)
# build model
model = Sequential()
model.add(Convolution2D(nb_filters, nb_conv, nb_conv, border_mode='valid', input_shape=(1, img_rows, img_cols)))
model.add(Activation('relu'))
model.add(Convolution2D(nb_filters, nb_conv, …