小编csw*_*wah的帖子

我有以下代码,我重写它来处理大型数据集.我正在使用Python生成器来为逐个批量生成的数据拟合模型.

def subtract_mean_gen(x_source,y_source,avg_image,batch):
    batch_list_x=[]
    batch_list_y=[]
    for line,y in zip(x_source,y_source):
        x=line.astype('float32')
        x=x-avg_image
        batch_list_x.append(x)
        batch_list_y.append(y)
        if len(batch_list_x) == batch:
            yield (np.array(batch_list_x),np.array(batch_list_y))
            batch_list_x=[]
            batch_list_y=[] 

model = resnet.ResnetBuilder.build_resnet_18((img_channels, img_rows, img_cols), nb_classes)
model.compile(loss='categorical_crossentropy',
              optimizer='adam',
              metrics=['accuracy'])

val = subtract_mean_gen(X_test,Y_test,avg_image_test,batch_size)
model.fit_generator(subtract_mean_gen(X_train,Y_train,avg_image_train,batch_size), steps_per_epoch=X_train.shape[0]//batch_size,epochs=nb_epoch,validation_data = val,
                    validation_steps = X_test.shape[0]//batch_size)

我收到以下错误:

239/249 [===========================>..] - ETA: 60s - loss: 1.3318 - acc: 0.8330Exception in thread Thread-1:
Traceback (most recent call last):
  File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
    self.run()
  File "/usr/lib/python2.7/threading.py", line 754, in run
    self.__target(*self.__args, **self.__kwargs)
  File "/usr/local/lib/python2.7/dist-packages/keras/utils/data_utils.py", line 560, in …

我正在尝试使用 .cifar10 数据集运行 Resnet 示例.flow_from_directory(directory)。下面的代码如下：

from __future__ import print_function
from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import np_utils
from keras.callbacks import ReduceLROnPlateau, CSVLogger, EarlyStopping

import numpy as np
import resnet
import os
import cv2
import csv
#import keras 

os.environ["CUDA_VISIBLE_DEVICES"] = "1"


# input image dimensions
img_rows, img_cols = 32, 32
# The CIFAR10 images are RGB.
img_channels = 3
nb_classes = 10


train_datagen = ImageDataGenerator(
        rescale=1./255,
        shear_range=0,
        zoom_range=0,
        horizontal_flip=False,
        width_shift_range=0.1,  # randomly shift images horizontally …