Question

我是keras和python的新手。我只是想知道如何将2d形输入转换为3d形输入。我的2d输入数据是192x192和3个图像。所以，使用这个2d形状输入数据，我想制作192x192x3输入形状。我的代码如下。

from __future__ import print_function

import os
from skimage.transform import resize
from skimage.io import imsave
import numpy as np
from keras.models import Model, load_model
from keras.layers import Input, concatenate, Conv2D, MaxPooling2D, Conv2DTranspose, Dropout, Conv3D, MaxPooling3D
from keras.optimizers import Adam
from keras.callbacks import ModelCheckpoint
from keras import backend as K

from data import load_train_data, load_test_data  #, load_test_validation_data
import matplotlib.pyplot as plt
from keras.preprocessing.image import ImageDataGenerator

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

K.set_image_data_format('channels_last')
image_rows = 192
image_cols = 192
total = 482

img_rows = 192  # 96
img_cols = 192   # 96

smooth = 1.

def dice_coef(y_true, y_pred):
    y_true_f = K.flatten(y_true)
    y_pred_f = K.flatten(y_pred)
    intersection = K.sum(y_true_f * y_pred_f)
    return (2. * intersection + smooth) / (K.sum(y_true_f) + K.sum(y_pred_f) + smooth)

def dice_coef_loss(y_true, y_pred):
    return -dice_coef(y_true, y_pred)


def get_unet():
    ## layer #1
    input1 = Input((img_rows, img_cols, 1), name='input1') ## (?, 192, 192,1)
    input2 = Input((img_rows, img_cols, 1), name='input2') ## (?, 192, 192,1)
    input3 = Input((img_rows, img_cols, 1), name='input3') ## (?, 192, 192,1)

    inputs = np.ndarray((total, img_rows, img_cols, 3), dtype=np.float32)
    inputs[:, :, :, 0] = input1
    inputs[:, :, :, 1] = input2
    inputs[:, :, :, 2] = input3

    conv1_1 = Conv3D(32, (3, 3, 3), activation='relu', padding='same')(inputs)
    conv1_1 = Conv3D(32, (3, 3, 3), activation='relu', padding='same')(conv1_1)
    pool1_1 = MaxPooling3D(pool_size=(2, 2, 1))(conv1_1)
    drop1_1 = Dropout(0.2)(pool1_1)
    ......

此行发生错误。

inputs[:, :, :, 0] = input1

错误信息如下。

输入[：，：，：，0] = input1 ValueError：使用序列设置数组元素。

是否有人可以建议我将三个2d输入组合到Keras的3d形输入中？感谢。

如何在keras中将2d输入转换为3d形状？

0 个答案: