基于CIFAR数据集的卷积网络训练
CIFAR-10, CIFAR-100 数据集介绍
CIFAR-10和CIFAR-100是分类标记的小图像数据集。它在研究界被广泛用于简单的图像分类任务基准。
官方网站：
在Chainer中，CIFAR-10和CIFAR-100数据集可以通过内置函数获得。
from __future__ import print_function
import os
import matplotlib.pyplot as plt
import numpy as np
import chainer
%matplotlib inline
basedir = './images'
CIFAR-10
在Chainer中准备chainer.datasets.get_cifar10方法来获取CIFAR-10数据集。数据集仅自动从 https://www.cs.toronto.edu 下载，第二次使用缓存。
CIFAR10_LABELS_LIST = [
'airplane',
'automobile',
'bird',
'cat',
'deer',
'dog',
'frog',
'horse',
'ship',
'truck'
]
train, test = chainer.datasets.get_cifar10()
Downloading from https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz...
数据集结构与MNIST数据集完全相同，即TupleDataset。train[i] 代表第i个数据，有50000个训练数据。测试数据结构相同，有10000个测试数据。
print('len(train), type ', len(train), type(train))
print('len(test), type ', len(test), type(test))
len(train), type 50000 <class 'chainer.datasets.tuple_dataset.TupleDataset'>
len(test), type 10000 <class 'chainer.datasets.tuple_dataset.TupleDataset'>
train[i] 表示第i个数据，type=tuple ($x_i,y_i$), 其中$x_i$是图像数据，$y_i$是标签数据.
train[i][0] 表示CIFAR-10图像数据$x_i$,，这是3维阵列（3,32,32），分别表示RGB通道，宽度32px，高度32px。
train[i][1] 表示CIFAR-10图像数据（标量）的标签$y_i$，这是标量值，其实际标签可以被LABELS_LIST转换。ted by LABELS_LIST.
我们来看看第0个数据，train[0]的细节。
print('train[0]', type(train[0]), len(train[0]))
x0, y0 = train[0]
print('train[0][0]', x0.shape, x0)
print('train[0][1]', y0.shape, y0, '->', CIFAR10_LABELS_LIST[y0])
train[0] <class 'tuple'> 2
train[0][0] (3, 32, 32) [[[ 0.23137257 0.16862746 0.19607845 ..., 0.61960787 0.59607846
0.58039218]
[ 0.0627451 0. 0.07058824 ..., 0.48235297 0.4666667
0.4784314 ]
[ 0.09803922 0.0627451 0.19215688 ..., 0.46274513 0.47058827
0.42745101]
...,
[ 0.81568635 0.78823537 0.77647066 ..., 0.627451 0.21960786
0.20784315]
[ 0.70588237 0.67843139 0.72941178 ..., 0.72156864 0.38039219
0.32549021]
[ 0.69411767 0.65882355 0.7019608 ..., 0.84705889 0.59215689
0.48235297]]
[[ 0.24313727 0.18039216 0.18823531 ..., 0.51764709 0.49019611
0.48627454]
[ 0.07843138 0. 0.03137255 ..., 0.34509805 0.32549021
0.34117648]
[ 0.09411766 0.02745098 0.10588236 ..., 0.32941177 0.32941177
0.28627452]
...,
[ 0.66666669 0.60000002 0.63137257 ..., 0.52156866 0.12156864
0.13333334]
[ 0.54509807 0.48235297 0.56470591 ..., 0.58039218 0.24313727
0.20784315]
[ 0.56470591 0.50588238 0.55686277 ..., 0.72156864 0.46274513
0.36078432]]
[[ 0.24705884 0.17647059 0.16862746 ..., 0.42352945 0.40000004
0.4039216 ]
[ 0.07843138 0. 0. ..., 0.21568629 0.19607845
0.22352943]
[ 0.08235294 0. 0.03137255 ..., 0.19607845 0.19607845
0.16470589]
...,
[ 0.37647063 0.13333334 0.10196079 ..., 0.27450982 0.02745098
0.07843138]
[ 0.37647063 0.16470589 0.11764707 ..., 0.36862746 0.13333334
0.13333334]
[ 0.45490199 0.36862746 0.34117648 ..., 0.54901963 0.32941177
0.28235295]]]
train[0][1] () 6 -> frog
def plot_cifar(filepath, data, row, col, scale=3., label_list=None):
fig_width = data[0][0].shape[1] / 80 * row * scale
fig_height = data[0][0].shape[2] / 80 * col * scale
fig, axes = plt.subplots(row,
col,
figsize=(fig_height, fig_width))
for i in range(row * col):
# train[i][0] is i-th image data with size 32x32
image, label_index = data[i]
image = image.transpose(1, 2, 0)
r, c = divmod(i, col)
axes[r][c].imshow(image) # cmap='gray' is for black and white picture.
if label_list is None:
axes[r][c].set_title('label {}'.format(label_index))
else:
axes[r][c].set_title('{}: {}'.format(label_index, label_list[label_index]))
axes[r][c].axis('off') # do not show axis value
plt.tight_layout() # automatic padding between subplots
plt.savefig(filepath)
plot_cifar(os.path.join(basedir, 'cifar10_plot.png'), train, 4, 5,
scale=4., label_list=CIFAR10_LABELS_LIST)
plot_cifar(os.path.join(basedir, 'cifar10_plot_more.png'), train, 10, 10,
scale=4., label_list=CIFAR10_LABELS_LIST)
CIFAR-100
CIFAR-100与CIFAR-10非常相似。 chainer.datasets.get_cifar100方法在Chainer中准备得到CIFAR-100数据集。
CIFAR100_LABELS_LIST = [
'apple', 'aquarium_fish', 'baby', 'bear', 'beaver', 'bed', 'bee', 'beetle',
'bicycle', 'bottle', 'bowl', 'boy', 'bridge', 'bus', 'butterfly', 'camel',
'can', 'castle', 'caterpillar', 'cattle', 'chair', 'chimpanzee', 'clock',
'cloud', 'cockroach', 'couch', 'crab', 'crocodile', 'cup', 'dinosaur',
'dolphin', 'elephant', 'flatfish', 'forest', 'fox', 'girl', 'hamster',
'house', 'kangaroo', 'keyboard', 'lamp', 'lawn_mower', 'leopard', 'lion',
'lizard', 'lobster', 'man', 'maple_tree', 'motorcycle', 'mountain', 'mouse',
'mushroom', 'oak_tree', 'orange', 'orchid', 'otter', 'palm_tree', 'pear',
'pickup_truck', 'pine_tree', 'plain', 'plate', 'poppy', 'porcupine',
'possum', 'rabbit', 'raccoon', 'ray', 'road', 'rocket', 'rose',
'sea', 'seal', 'shark', 'shrew', 'skunk', 'skyscraper', 'snail', 'snake',
'spider', 'squirrel', 'streetcar', 'sunflower', 'sweet_pepper', 'table',
'tank', 'telephone', 'television', 'tiger', 'tractor', 'train', 'trout',
'tulip', 'turtle', 'wardrobe', 'whale', 'willow_tree', 'wolf', 'woman',
'worm'
]
train_cifar100, test_cifar100 = chainer.datasets.get_cifar100()
Downloading from https://www.cs.toronto.edu/~kriz/cifar-100-python.tar.gz...
数据集结构与MNIST数据集完全相同，即TupleDataset。
train[i]代表第i个数据，有50000个训练数据。列车数据总量相同，班级标签数量增加。所以每个类别标签的训练数据少于CIFAR-10数据集。
测试数据结构相同，有10000个测试数据。
print('len(train_cifar100), type ', len(train_cifar100), type(train_cifar100))
print('len(test_cifar100), type ', len(test_cifar100), type(test_cifar100))
print('train_cifar100[0]', type(train_cifar100[0]), len(train_cifar100[0]))
x0, y0 = train_cifar100[0]
print('train_cifar100[0][0]', x0.shape) # , x0
print('train_cifar100[0][1]', y0.shape, y0)
len(train_cifar100), type 50000 <class 'chainer.datasets.tuple_dataset.TupleDataset'>
len(test_cifar100), type 10000 <class 'chainer.datasets.tuple_dataset.TupleDataset'>
train_cifar100[0] <class 'tuple'> 2
train_cifar100[0][0] (3, 32, 32)
train_cifar100[0][1] () 19
plot_cifar(os.path.join(basedir, 'cifar100_plot_more.png'), train_cifar100,
10, 10, scale=4., label_list=CIFAR100_LABELS_LIST)
定义一个CNN架构的神经网络
import chainer
import chainer.functions as F
import chainer.links as L
class CNNMedium(chainer.Chain):
def __init__(self, n_out):
super(CNNMedium, self).__init__()
with self.init_scope():
self.conv1 = L.Convolution2D(None, 16, 3, 1)
self.conv2 = L.Convolution2D(16, 32, 3, 2)
self.conv3 = L.Convolution2D(32, 32, 3, 1)
self.conv4 = L.Convolution2D(32, 64, 3, 2)
self.conv5 = L.Convolution2D(64, 64, 3, 1)
self.conv6 = L.Convolution2D(64, 128, 3, 2)
self.fc7 = L.Linear(None, 100)
self.fc8 = L.Linear(100, n_out)
def __call__(self, x):
h = F.relu(self.conv1(x))
h = F.relu(self.conv2(h))
h = F.relu(self.conv3(h))
h = F.relu(self.conv4(h))
h = F.relu(self.conv5(h))
h = F.relu(self.conv6(h))
h = F.relu(self.fc7(h))
h = self.fc8(h)
return h
卷积层的计算代价近似为，
$H_I \times W_I \times CH_I \times CH_O \times k^2$
$CH_I$ : 输入图像通道数 $CH_O$ : 输出图像通道数 $H_I$ : 输入图像高度 $W_I$ : 输入图像宽度 $k$ : 内核大小（假设宽度和高度相同）
在以上的CNN定义中，对于更深的层来说，通道的尺寸更大。这可以通过计算每层的计算成本来理解。
当采用stride=2的L.Convolution2D时，图像的大小几乎变成了一半。这意味着$H_I$和$W_I$变得很小，所以$CH_I$和$CH_O$可以选择更大的数值。
训练 CIFAR-10
一旦你写了CNN，很容易训练这个模型
from __future__ import print_function
import argparse
import chainer
import chainer.functions as F
import chainer.links as L
from chainer import training, iterators, serializers, optimizers
from chainer.training import extensions
archs = {
'cnnmedium': CNNMedium,
}
parser = argparse.ArgumentParser(description='Cifar-10 CNN example')
parser.add_argument('--arch', '-a', choices=archs.keys(),
default='cnnmedium', help='Convnet architecture')
parser.add_argument('--batchsize', '-b', type=int, default=64,
help='Number of images in each mini-batch')
parser.add_argument('--epoch', '-e', type=int, default=20,
help='Number of sweeps over the dataset to train')
parser.add_argument('--gpu', '-g', type=int, default=-1,
help='GPU ID (negative value indicates CPU)')
parser.add_argument('--out', '-o', default='result-cifar10',
help='Directory to output the result')
parser.add_argument('--resume', '-r', default='',
help='Resume the training from snapshot')
args = parser.parse_args(['-g','0'])
print('GPU: {}'.format(args.gpu))
print('# Minibatch-size: {}'.format(args.batchsize))
print('# epoch: {}'.format(args.epoch))
print('')
GPU: 0
# Minibatch-size: 64
# epoch: 20
# 1. Setup model
class_num = 10
model = archs[args.arch](n_out=class_num)
classifier_model = L.Classifier(model)
if args.gpu >= 0:
chainer.cuda.get_device(args.gpu).use() # Make a specified GPU current
classifier_model.to_gpu() # Copy the model to the GPU
# 2. Setup an optimizer
optimizer = optimizers.Adam()
optimizer.setup(classifier_model)
# 3. Load the CIFAR-10 dataset
train, test = chainer.datasets.get_cifar10()
# 4. Setup an Iterator
train_iter = iterators.SerialIterator(train, args.batchsize)
test_iter = iterators.SerialIterator(test, args.batchsize,
repeat=False, shuffle=False)
# 5. Setup an Updater
updater = training.StandardUpdater(train_iter, optimizer, device=args.gpu)
# 6. Setup a trainer (and extensions)
trainer = training.Trainer(updater, (args.epoch, 'epoch'), out=args.out)
# Evaluate the model with the test dataset for each epoch
trainer.extend(extensions.Evaluator(test_iter, classifier_model, device=args.gpu))
trainer.extend(extensions.dump_graph('main/loss'))
trainer.extend(extensions.snapshot(), trigger=(1, 'epoch'))
trainer.extend(extensions.LogReport())
trainer.extend(extensions.PrintReport(
['epoch', 'main/loss', 'validation/main/loss',
'main/accuracy', 'validation/main/accuracy', 'elapsed_time']))
trainer.extend(extensions.PlotReport(
['main/loss', 'validation/main/loss'],
x_key='epoch', file_name='loss.png'))
trainer.extend(extensions.PlotReport(
['main/accuracy', 'validation/main/accuracy'],
x_key='epoch',
file_name='accuracy.png'))
trainer.extend(extensions.ProgressBar())
# Resume from a snapshot
if args.resume:
serializers.load_npz(args.resume, trainer)
# Run the training
trainer.run()
epoch main/loss validation/main/loss main/accuracy validation/main/accuracy elapsed_time
[J total [..................................................] 0.64%
this epoch [######............................................] 12.80%
100 iter, 0 epoch / 20 epochs
inf iters/sec. Estimated time to finish: 0:00:00.
[4A[J total [..................................................] 1.28%
this epoch [############......................................] 25.60%
200 iter, 0 epoch / 20 epochs
125.61 iters/sec. Estimated time to finish: 0:02:02.799182.
[4A[J total [..................................................] 1.92%
this epoch [###################...............................] 38.40%
300 iter, 0 epoch / 20 epochs
126.41 iters/sec. Estimated time to finish: 0:02:01.228643.
[4A[J total [#.................................................] 2.56%
this epoch [#########################.........................] 51.20%
400 iter, 0 epoch / 20 epochs
126.96 iters/sec. Estimated time to finish: 0:01:59.915494.
[4A[J total [#.................................................] 3.20%
this epoch [################################..................] 64.00%
500 iter, 0 epoch / 20 epochs
127.31 iters/sec. Estimated time to finish: 0:01:58.799905.
[4A[J total [#.................................................] 3.84%
this epoch [######################################............] 76.80%
600 iter, 0 epoch / 20 epochs
127.5 iters/sec. Estimated time to finish: 0:01:57.844706.
[4A[J total [##................................................] 4.48%
this epoch [############################################......] 89.60%
700 iter, 0 epoch / 20 epochs
127.62 iters/sec. Estimated time to finish: 0:01:56.947000.
[4A[J1 1.63966 1.37119 0.391584 0.497811 7.3451
[J total [##................................................] 5.12%
this epoch [#.................................................] 2.40%
800 iter, 1 epoch / 20 epochs
112.44 iters/sec. Estimated time to finish: 0:02:11.847638.
[4A[J total [##................................................] 5.76%
this epoch [#######...........................................] 15.20%
900 iter, 1 epoch / 20 epochs
114.07 iters/sec. Estimated time to finish: 0:02:09.084668.
[4A[J total [###...............................................] 6.40%
this epoch [##############....................................] 28.00%
1000 iter, 1 epoch / 20 epochs
115.23 iters/sec. Estimated time to finish: 0:02:06.920558.
[4A[J total [###...............................................] 7.04%
this epoch [####################..............................] 40.80%
1100 iter, 1 epoch / 20 epochs
116.3 iters/sec. Estimated time to finish: 0:02:04.891163.
[4A[J total [###...............................................] 7.68%
this epoch [##########################........................] 53.60%
1200 iter, 1 epoch / 20 epochs
117.24 iters/sec. Estimated time to finish: 0:02:03.035187.
[4A[J total [####..............................................] 8.32%
this epoch [#################################.................] 66.40%
1300 iter, 1 epoch / 20 epochs
118.1 iters/sec. Estimated time to finish: 0:02:01.294570.
[4A[J total [####..............................................] 8.96%
this epoch [#######################################...........] 79.20%
1400 iter, 1 epoch / 20 epochs
118.83 iters/sec. Estimated time to finish: 0:01:59.703835.
[4A[J total [####..............................................] 9.60%
this epoch [##############################################....] 92.00%
1500 iter, 1 epoch / 20 epochs
119.39 iters/sec. Estimated time to finish: 0:01:58.311100.
[4A[J2 1.27853 1.19743 0.540013 0.573646 14.2082
[J total [#####.............................................] 10.24%
this epoch [##................................................] 4.80%
1600 iter, 2 epoch / 20 epochs
113.3 iters/sec. Estimated time to finish: 0:02:03.789080.
[4A[J total [#####.............................................] 10.88%
this epoch [########..........................................] 17.60%
1700 iter, 2 epoch / 20 epochs
114.13 iters/sec. Estimated time to finish: 0:02:02.007898.
[4A[J total [#####.............................................] 11.52%
this epoch [###############...................................] 30.40%
1800 iter, 2 epoch / 20 epochs
114.76 iters/sec. Estimated time to finish: 0:02:00.466795.
[4A[J total [######............................................] 12.16%
this epoch [#####################.............................] 43.20%
1900 iter, 2 epoch / 20 epochs
115.41 iters/sec. Estimated time to finish: 0:01:58.924804.
[4A[J total [######............................................] 12.80%
this epoch [############################......................] 56.00%
2000 iter, 2 epoch / 20 epochs
116.07 iters/sec. Estimated time to finish: 0:01:57.383023.
[4A[J total [######............................................] 13.44%
this epoch [##################################................] 68.80%
2100 iter, 2 epoch / 20 epochs
116.61 iters/sec. Estimated time to finish: 0:01:55.984400.
[4A[J total [#######...........................................] 14.08%
this epoch [########################################..........] 81.60%
2200 iter, 2 epoch / 20 epochs
117.11 iters/sec. Estimated time to finish: 0:01:54.632769.
[4A[J total [#######...........................................] 14.72%
this epoch [###############################################...] 94.40%
2300 iter, 2 epoch / 20 epochs
117.56 iters/sec. Estimated time to finish: 0:01:53.342540.
[4A[J3 1.11089 1.09346 0.604273 0.616143 21.0442
[J total [#######...........................................] 15.36%
this epoch [###...............................................] 7.20%
2400 iter, 3 epoch / 20 epochs
113.63 iters/sec. Estimated time to finish: 0:01:56.384466.
[4A[J total [########..........................................] 16.00%
this epoch [##########........................................] 20.00%
2500 iter, 3 epoch / 20 epochs
114.14 iters/sec. Estimated time to finish: 0:01:54.990394.
[4A[J total [########..........................................] 16.64%
this epoch [################..................................] 32.80%
2600 iter, 3 epoch / 20 epochs
114.61 iters/sec. Estimated time to finish: 0:01:53.649835.
[4A[J total [########..........................................] 17.28%
this epoch [######################............................] 45.60%
2700 iter, 3 epoch / 20 epochs
115.06 iters/sec. Estimated time to finish: 0:01:52.328166.
[4A[J total [########..........................................] 17.92%
this epoch [#############################.....................] 58.40%
2800 iter, 3 epoch / 20 epochs
115.5 iters/sec. Estimated time to finish: 0:01:51.043157.
[4A[J total [#########.........................................] 18.56%
this epoch [###################################...............] 71.20%
2900 iter, 3 epoch / 20 epochs
115.91 iters/sec. Estimated time to finish: 0:01:49.781270.
[4A[J total [#########.........................................] 19.20%
this epoch [#########################################.........] 84.00%
3000 iter, 3 epoch / 20 epochs
116.28 iters/sec. Estimated time to finish: 0:01:48.571255.
[4A[J total [#########.........................................] 19.84%
this epoch [################################################..] 96.80%
3100 iter, 3 epoch / 20 epochs
116.63 iters/sec. Estimated time to finish: 0:01:47.391292.
[4A[J4 0.993067 1.0149 0.645947 0.640625 27.909
[J total [##########........................................] 20.48%
this epoch [####..............................................] 9.60%
3200 iter, 4 epoch / 20 epochs
113.76 iters/sec. Estimated time to finish: 0:01:49.218342.
[4A[J total [##########........................................] 21.12%
this epoch [###########.......................................] 22.40%
3300 iter, 4 epoch / 20 epochs
114.13 iters/sec. Estimated time to finish: 0:01:47.991799.
[4A[J total [##########........................................] 21.76%
this epoch [#################.................................] 35.20%
3400 iter, 4 epoch / 20 epochs
114.48 iters/sec. Estimated time to finish: 0:01:46.784048.
[4A[J total [###########.......................................] 22.40%
this epoch [########################..........................] 48.00%
3500 iter, 4 epoch / 20 epochs
114.84 iters/sec. Estimated time to finish: 0:01:45.585070.
[4A[J total [###########.......................................] 23.04%
this epoch [##############################....................] 60.80%
3600 iter, 4 epoch / 20 epochs
115.15 iters/sec. Estimated time to finish: 0:01:44.426766.
[4A[J total [###########.......................................] 23.68%
this epoch [####################################..............] 73.60%
3700 iter, 4 epoch / 20 epochs
115.47 iters/sec. Estimated time to finish: 0:01:43.271093.
[4A[J total [############......................................] 24.32%
this epoch [###########################################.......] 86.40%
3800 iter, 4 epoch / 20 epochs
115.69 iters/sec. Estimated time to finish: 0:01:42.215823.
[4A[J total [############......................................] 24.96%
this epoch [#################################################.] 99.20%
3900 iter, 4 epoch / 20 epochs
115.94 iters/sec. Estimated time to finish: 0:01:41.131895.
[4A[J5 0.906105 0.981679 0.679028 0.65834 34.8258
[J total [############......................................] 25.60%
this epoch [######............................................] 12.00%
4000 iter, 5 epoch / 20 epochs
113.09 iters/sec. Estimated time to finish: 0:01:42.796864.
[4A[J total [#############.....................................] 26.24%
this epoch [############......................................] 24.80%
4100 iter, 5 epoch / 20 epochs
113.24 iters/sec. Estimated time to finish: 0:01:41.777657.
[4A[J total [#############.....................................] 26.88%
this epoch [##################................................] 37.60%
4200 iter, 5 epoch / 20 epochs
113.41 iters/sec. Estimated time to finish: 0:01:40.744638.
[4A[J total [#############.....................................] 27.52%
this epoch [#########################.........................] 50.40%
4300 iter, 5 epoch / 20 epochs
113.73 iters/sec. Estimated time to finish: 0:01:39.575979.
[4A[J total [##############....................................] 28.16%
this epoch [###############################...................] 63.20%
4400 iter, 5 epoch / 20 epochs
114.02 iters/sec. Estimated time to finish: 0:01:38.447348.
[4A[J total [##############....................................] 28.80%
this epoch [#####################################.............] 76.00%
4500 iter, 5 epoch / 20 epochs
114.3 iters/sec. Estimated time to finish: 0:01:37.333849.
[4A[J total [##############....................................] 29.44%
this epoch [############################################......] 88.80%
4600 iter, 5 epoch / 20 epochs
114.56 iters/sec. Estimated time to finish: 0:01:36.234988.
[4A[J6 0.829003 0.962217 0.706646 0.663018 41.9501
[J total [###############...................................] 30.08%
this epoch [..................................................] 1.60%
4700 iter, 6 epoch / 20 epochs
112.76 iters/sec. Estimated time to finish: 0:01:36.888072.
[4A[J total [###############...................................] 30.72%
this epoch [#######...........................................] 14.40%
4800 iter, 6 epoch / 20 epochs
113.02 iters/sec. Estimated time to finish: 0:01:35.775456.
[4A[J total [###############...................................] 31.36%
this epoch [#############.....................................] 27.20%
4900 iter, 6 epoch / 20 epochs
113.29 iters/sec. Estimated time to finish: 0:01:34.666533.
[4A[J total [################..................................] 32.00%
this epoch [####################..............................] 40.00%
5000 iter, 6 epoch / 20 epochs
113.54 iters/sec. Estimated time to finish: 0:01:33.582794.
[4A[J total [################..................................] 32.64%
this epoch [##########################........................] 52.80%
5100 iter, 6 epoch / 20 epochs
113.79 iters/sec. Estimated time to finish: 0:01:32.496581.
[4A[J total [################..................................] 33.28%
this epoch [################################..................] 65.60%
5200 iter, 6 epoch / 20 epochs
114.06 iters/sec. Estimated time to finish: 0:01:31.402953.
[4A[J total [################..................................] 33.92%
this epoch [#######################################...........] 78.40%
5300 iter, 6 epoch / 20 epochs
114.29 iters/sec. Estimated time to finish: 0:01:30.342284.
[4A[J total [#################.................................] 34.56%
this epoch [#############################################.....] 91.20%
5400 iter, 6 epoch / 20 epochs
114.52 iters/sec. Estimated time to finish: 0:01:29.285742.
[4A[J7 0.762821 0.922659 0.729133 0.682922 48.8031
[J total [#################.................................] 35.20%
this epoch [##................................................] 4.00%
5500 iter, 7 epoch / 20 epochs
112.99 iters/sec. Estimated time to finish: 0:01:29.610861.
[4A[J total [#################.................................] 35.84%
this epoch [########..........................................] 16.80%
5600 iter, 7 epoch / 20 epochs
113.22 iters/sec. Estimated time to finish: 0:01:28.540957.
[4A[J total [##################................................] 36.48%
this epoch [##############....................................] 29.60%
5700 iter, 7 epoch / 20 epochs
113.42 iters/sec. Estimated time to finish: 0:01:27.504411.
[4A[J total [##################................................] 37.12%
this epoch [#####################.............................] 42.40%
5800 iter, 7 epoch / 20 epochs
113.64 iters/sec. Estimated time to finish: 0:01:26.454301.
[4A[J total [##################................................] 37.76%
this epoch [###########################.......................] 55.20%
5900 iter, 7 epoch / 20 epochs
113.87 iters/sec. Estimated time to finish: 0:01:25.401434.
[4A[J total [###################...............................] 38.40%
this epoch [#################################.................] 68.00%
6000 iter, 7 epoch / 20 epochs
114.07 iters/sec. Estimated time to finish: 0:01:24.380654.
[4A[J total [###################...............................] 39.04%
this epoch [########################################..........] 80.80%
6100 iter, 7 epoch / 20 epochs
114.28 iters/sec. Estimated time to finish: 0:01:23.346596.
[4A[J total [###################...............................] 39.68%
this epoch [##############################################....] 93.60%
6200 iter, 7 epoch / 20 epochs
114.48 iters/sec. Estimated time to finish: 0:01:22.328793.
[4A[J8 0.698332 0.957248 0.753661 0.672671 55.6596
[J total [####################..............................] 40.32%
this epoch [###...............................................] 6.40%
6300 iter, 8 epoch / 20 epochs
113.13 iters/sec. Estimated time to finish: 0:01:22.426493.
[4A[J total [####################..............................] 40.96%
this epoch [#########.........................................] 19.20%
6400 iter, 8 epoch / 20 epochs
113.34 iters/sec. Estimated time to finish: 0:01:21.394052.
[4A[J total [####################..............................] 41.60%
this epoch [################..................................] 32.00%
6500 iter, 8 epoch / 20 epochs
113.53 iters/sec. Estimated time to finish: 0:01:20.372562.
[4A[J total [#####################.............................] 42.24%
this epoch [######################............................] 44.80%
6600 iter, 8 epoch / 20 epochs
113.73 iters/sec. Estimated time to finish: 0:01:19.354827.
[4A[J total [#####################.............................] 42.88%
this epoch [############################......................] 57.60%
6700 iter, 8 epoch / 20 epochs
113.93 iters/sec. Estimated time to finish: 0:01:18.340858.
[4A[J total [#####################.............................] 43.52%
this epoch [###################################...............] 70.40%
6800 iter, 8 epoch / 20 epochs
114.1 iters/sec. Estimated time to finish: 0:01:17.342524.
[4A[J total [######################............................] 44.16%
this epoch [#########################################.........] 83.20%
6900 iter, 8 epoch / 20 epochs
114.28 iters/sec. Estimated time to finish: 0:01:16.346479.
[4A[J total [######################............................] 44.80%
this epoch [################################################..] 96.00%
7000 iter, 8 epoch / 20 epochs
114.46 iters/sec. Estimated time to finish: 0:01:15.350704.
[4A[J9 0.65115 0.937813 0.768942 0.682325 62.5173
[J total [######################............................] 45.44%
this epoch [####..............................................] 8.80%
7100 iter, 9 epoch / 20 epochs
113.15 iters/sec. Estimated time to finish: 0:01:15.342457.
[4A[J total [#######################...........................] 46.08%
this epoch [##########........................................] 21.60%
7200 iter, 9 epoch / 20 epochs
113.33 iters/sec. Estimated time to finish: 0:01:14.342647.
[4A[J total [#######################...........................] 46.72%
this epoch [#################.................................] 34.40%
7300 iter, 9 epoch / 20 epochs
113.51 iters/sec. Estimated time to finish: 0:01:13.340419.
[4A[J total [#######################...........................] 47.36%
this epoch [#######################...........................] 47.20%
7400 iter, 9 epoch / 20 epochs
113.69 iters/sec. Estimated time to finish: 0:01:12.346160.
[4A[J total [########################..........................] 48.00%
this epoch [#############################.....................] 60.00%
7500 iter, 9 epoch / 20 epochs
113.87 iters/sec. Estimated time to finish: 0:01:11.353393.
[4A[J total [########################..........................] 48.64%
this epoch [####################################..............] 72.80%
7600 iter, 9 epoch / 20 epochs
114.02 iters/sec. Estimated time to finish: 0:01:10.382495.
[4A[J total [########################..........................] 49.28%
this epoch [##########################################........] 85.60%
7700 iter, 9 epoch / 20 epochs
114.19 iters/sec. Estimated time to finish: 0:01:09.404675.
[4A[J total [########################..........................] 49.92%
this epoch [#################################################.] 98.40%
7800 iter, 9 epoch / 20 epochs
114.34 iters/sec. Estimated time to finish: 0:01:08.434026.
[4A[J10 0.601723 0.937862 0.786852 0.688296 69.4373
[J total [#########################.........................] 50.56%
this epoch [#####.............................................] 11.20%
7900 iter, 10 epoch / 20 epochs
113.26 iters/sec. Estimated time to finish: 0:01:08.208386.
[4A[J total [#########################.........................] 51.20%
this epoch [############......................................] 24.00%
8000 iter, 10 epoch / 20 epochs
113.41 iters/sec. Estimated time to finish: 0:01:07.235866.
[4A[J total [#########################.........................] 51.84%
this epoch [##################................................] 36.80%
8100 iter, 10 epoch / 20 epochs
113.57 iters/sec. Estimated time to finish: 0:01:06.261301.
[4A[J total [##########################........................] 52.48%
this epoch [########################..........................] 49.60%
8200 iter, 10 epoch / 20 epochs
113.72 iters/sec. Estimated time to finish: 0:01:05.289734.
[4A[J total [##########################........................] 53.12%
this epoch [###############################...................] 62.40%
8300 iter, 10 epoch / 20 epochs
113.86 iters/sec. Estimated time to finish: 0:01:04.330680.
[4A[J total [##########################........................] 53.76%
this epoch [#####################################.............] 75.20%
8400 iter, 10 epoch / 20 epochs
114.01 iters/sec. Estimated time to finish: 0:01:03.374040.
[4A[J total [###########################.......................] 54.40%
this epoch [############################################......] 88.00%
8500 iter, 10 epoch / 20 epochs
114.14 iters/sec. Estimated time to finish: 0:01:02.421317.
[4A[J11 0.544254 0.994541 0.806358 0.699343 76.3034
[J total [###########################.......................] 55.04%
this epoch [..................................................] 0.80%
8600 iter, 11 epoch / 20 epochs
113.19 iters/sec. Estimated time to finish: 0:01:02.064211.
[4A[J total [###########################.......................] 55.68%
this epoch [######............................................] 13.60%
8700 iter, 11 epoch / 20 epochs
113.33 iters/sec. Estimated time to finish: 0:01:01.102122.
[4A[J total [############################......................] 56.32%
this epoch [#############.....................................] 26.40%
8800 iter, 11 epoch / 20 epochs
113.48 iters/sec. Estimated time to finish: 0:01:00.143439.
[4A[J total [############################......................] 56.96%
this epoch [###################...............................] 39.20%
8900 iter, 11 epoch / 20 epochs
113.62 iters/sec. Estimated time to finish: 0:00:59.190595.
[4A[J total [############################......................] 57.60%
this epoch [#########################.........................] 52.00%
9000 iter, 11 epoch / 20 epochs
113.76 iters/sec. Estimated time to finish: 0:00:58.235956.
[4A[J total [#############################.....................] 58.24%
this epoch [################################..................] 64.80%
9100 iter, 11 epoch / 20 epochs
113.89 iters/sec. Estimated time to finish: 0:00:57.291026.
[4A[J total [#############################.....................] 58.88%
this epoch [######################################............] 77.60%
9200 iter, 11 epoch / 20 epochs
114.03 iters/sec. Estimated time to finish: 0:00:56.345303.
[4A[J total [#############################.....................] 59.52%
this epoch [#############################################.....] 90.40%
9300 iter, 11 epoch / 20 epochs
114.17 iters/sec. Estimated time to finish: 0:00:55.401445.
[4A[J12 0.501473 1.00326 0.821763 0.687898 83.1545
[J total [##############################....................] 60.16%
this epoch [#.................................................] 3.20%
9400 iter, 12 epoch / 20 epochs
113.28 iters/sec. Estimated time to finish: 0:00:54.952157.
[4A[J total [##############################....................] 60.80%
this epoch [########..........................................] 16.00%
9500 iter, 12 epoch / 20 epochs
113.41 iters/sec. Estimated time to finish: 0:00:54.007632.
[4A[J total [##############################....................] 61.44%
this epoch [##############....................................] 28.80%
9600 iter, 12 epoch / 20 epochs
113.54 iters/sec. Estimated time to finish: 0:00:53.065726.
[4A[J total [###############################...................] 62.08%
this epoch [####################..............................] 41.60%
9700 iter, 12 epoch / 20 epochs
113.66 iters/sec. Estimated time to finish: 0:00:52.126871.
[4A[J total [###############################...................] 62.72%
this epoch [###########################.......................] 54.40%
9800 iter, 12 epoch / 20 epochs
113.79 iters/sec. Estimated time to finish: 0:00:51.189483.
[4A[J total [###############################...................] 63.36%
this epoch [#################################.................] 67.20%
9900 iter, 12 epoch / 20 epochs
113.91 iters/sec. Estimated time to finish: 0:00:50.256781.
[4A[J total [################################..................] 64.00%
this epoch [########################################..........] 80.00%
10000 iter, 12 epoch / 20 epochs
114.04 iters/sec. Estimated time to finish: 0:00:49.326404.
[4A[J total [################################..................] 64.64%
this epoch [##############################################....] 92.80%
10100 iter, 12 epoch / 20 epochs
114.15 iters/sec. Estimated time to finish: 0:00:48.401125.
[4A[J13 0.458805 1.0016 0.835478 0.69586 90.0334
[J total [################################..................] 65.28%
this epoch [##................................................] 5.60%
10200 iter, 13 epoch / 20 epochs
113.16 iters/sec. Estimated time to finish: 0:00:47.938875.
[4A[J total [################################..................] 65.92%
this epoch [#########.........................................] 18.40%
10300 iter, 13 epoch / 20 epochs
113.16 iters/sec. Estimated time to finish: 0:00:47.056687.
[4A[J total [#################################.................] 66.56%
this epoch [###############...................................] 31.20%
10400 iter, 13 epoch / 20 epochs
113.15 iters/sec. Estimated time to finish: 0:00:46.178907.
[4A[J total [#################################.................] 67.20%
this epoch [#####################.............................] 44.00%
10500 iter, 13 epoch / 20 epochs
113.13 iters/sec. Estimated time to finish: 0:00:45.300128.
[4A[J total [#################################.................] 67.84%
this epoch [############################......................] 56.80%
10600 iter, 13 epoch / 20 epochs
113.12 iters/sec. Estimated time to finish: 0:00:44.423722.
[4A[J total [##################################................] 68.48%
this epoch [##################################................] 69.60%
10700 iter, 13 epoch / 20 epochs
113.11 iters/sec. Estimated time to finish: 0:00:43.541908.
[4A[J total [##################################................] 69.12%
this epoch [#########################################.........] 82.40%
10800 iter, 13 epoch / 20 epochs
114.05 iters/sec. Estimated time to finish: 0:00:42.304912.
[4A[J total [##################################................] 69.76%
this epoch [###############################################...] 95.20%
10900 iter, 13 epoch / 20 epochs
114.06 iters/sec. Estimated time to finish: 0:00:41.427012.
[4A[J14 0.41086 1.0577 0.855374 0.688993 96.974
[J total [###################################...............] 70.40%
this epoch [####..............................................] 8.00%
11000 iter, 14 epoch / 20 epochs
113.12 iters/sec. Estimated time to finish: 0:00:40.885069.
[4A[J total [###################################...............] 71.04%
this epoch [##########........................................] 20.80%
11100 iter, 14 epoch / 20 epochs
113.13 iters/sec. Estimated time to finish: 0:00:39.999143.
[4A[J total [###################################...............] 71.68%
this epoch [################..................................] 33.60%
11200 iter, 14 epoch / 20 epochs
113.13 iters/sec. Estimated time to finish: 0:00:39.114540.
[4A[J total [####################################..............] 72.32%
this epoch [#######################...........................] 46.40%
11300 iter, 14 epoch / 20 epochs
113.12 iters/sec. Estimated time to finish: 0:00:38.235042.
[4A[J total [####################################..............] 72.96%
this epoch [#############################.....................] 59.20%
11400 iter, 14 epoch / 20 epochs
113.12 iters/sec. Estimated time to finish: 0:00:37.351202.
[4A[J total [####################################..............] 73.60%
this epoch [####################################..............] 72.00%
11500 iter, 14 epoch / 20 epochs
113.12 iters/sec. Estimated time to finish: 0:00:36.465431.
[4A[J total [#####################################.............] 74.24%
this epoch [##########################################........] 84.80%
11600 iter, 14 epoch / 20 epochs
114.07 iters/sec. Estimated time to finish: 0:00:35.286180.
[4A[J total [#####################################.............] 74.88%
this epoch [################################################..] 97.60%
11700 iter, 14 epoch / 20 epochs
114.06 iters/sec. Estimated time to finish: 0:00:34.412155.
[4A[J15 0.379527 1.12376 0.864497 0.684713 103.831
[J total [#####################################.............] 75.52%
this epoch [#####.............................................] 10.40%
11800 iter, 15 epoch / 20 epochs
113.11 iters/sec. Estimated time to finish: 0:00:33.815536.
[4A[J total [######################################............] 76.16%
this epoch [###########.......................................] 23.20%
11900 iter, 15 epoch / 20 epochs
113.1 iters/sec. Estimated time to finish: 0:00:32.934948.
[4A[J total [######################################............] 76.80%
this epoch [#################.................................] 36.00%
12000 iter, 15 epoch / 20 epochs
113.09 iters/sec. Estimated time to finish: 0:00:32.054541.
[4A[J total [######################################............] 77.44%
this epoch [########################..........................] 48.80%
12100 iter, 15 epoch / 20 epochs
113.08 iters/sec. Estimated time to finish: 0:00:31.171342.
[4A[J total [#######################################...........] 78.08%
this epoch [##############################....................] 61.60%
12200 iter, 15 epoch / 20 epochs
113.08 iters/sec. Estimated time to finish: 0:00:30.288670.
[4A[J total [#######################################...........] 78.72%
this epoch [#####################################.............] 74.40%
12300 iter, 15 epoch / 20 epochs
113.08 iters/sec. Estimated time to finish: 0:00:29.404697.
[4A[J total [#######################################...........] 79.36%
this epoch [###########################################.......] 87.20%
12400 iter, 15 epoch / 20 epochs
114.03 iters/sec. Estimated time to finish: 0:00:28.282535.
[4A[J16 0.353034 1.18041 0.87418 0.68949 110.713
[J total [########################################..........] 80.00%
this epoch [..................................................] 0.00%
12500 iter, 16 epoch / 20 epochs
113.25 iters/sec. Estimated time to finish: 0:00:27.594325.
[4A[J total [########################################..........] 80.64%
this epoch [######............................................] 12.80%
12600 iter, 16 epoch / 20 epochs
113.07 iters/sec. Estimated time to finish: 0:00:26.753266.
[4A[J total [########################################..........] 81.28%
this epoch [############......................................] 25.60%
12700 iter, 16 epoch / 20 epochs
113.07 iters/sec. Estimated time to finish: 0:00:25.869927.
[4A[J total [########################################..........] 81.92%
this epoch [###################...............................] 38.40%
12800 iter, 16 epoch / 20 epochs
112.98 iters/sec. Estimated time to finish: 0:00:25.003462.
[4A[J total [#########################################.........] 82.56%
this epoch [#########################.........................] 51.20%
12900 iter, 16 epoch / 20 epochs
112.98 iters/sec. Estimated time to finish: 0:00:24.120367.
[4A[J total [#########################################.........] 83.20%
this epoch [################################..................] 64.00%
13000 iter, 16 epoch / 20 epochs
112.97 iters/sec. Estimated time to finish: 0:00:23.236801.
[4A[J total [#########################################.........] 83.84%
this epoch [######################################............] 76.80%
13100 iter, 16 epoch / 20 epochs
112.97 iters/sec. Estimated time to finish: 0:00:22.350168.
[4A[J total [##########################################........] 84.48%
this epoch [############################################......] 89.60%
13200 iter, 16 epoch / 20 epochs
113.93 iters/sec. Estimated time to finish: 0:00:21.284692.
[4A[J17 0.328672 1.24946 0.882133 0.682623 117.647
[J total [##########################################........] 85.12%
this epoch [#.................................................] 2.40%
13300 iter, 17 epoch / 20 epochs
112.99 iters/sec. Estimated time to finish: 0:00:20.577064.
[4A[J total [##########################################........] 85.76%
this epoch [#######...........................................] 15.20%
13400 iter, 17 epoch / 20 epochs
112.99 iters/sec. Estimated time to finish: 0:00:19.692789.
[4A[J total [###########################################.......] 86.40%
this epoch [##############....................................] 28.00%
13500 iter, 17 epoch / 20 epochs
112.97 iters/sec. Estimated time to finish: 0:00:18.810314.
[4A[J total [###########################################.......] 87.04%
this epoch [####################..............................] 40.80%
13600 iter, 17 epoch / 20 epochs
112.98 iters/sec. Estimated time to finish: 0:00:17.924269.
[4A[J total [###########################################.......] 87.68%
this epoch [##########################........................] 53.60%
13700 iter, 17 epoch / 20 epochs
112.97 iters/sec. Estimated time to finish: 0:00:17.039640.
[4A[J total [############################################......] 88.32%
this epoch [#################################.................] 66.40%
13800 iter, 17 epoch / 20 epochs
113 iters/sec. Estimated time to finish: 0:00:16.150847.
[4A[J total [############################################......] 88.96%
this epoch [#######################################...........] 79.20%
13900 iter, 17 epoch / 20 epochs
113.01 iters/sec. Estimated time to finish: 0:00:15.263648.
[4A[J total [############################################......] 89.60%
this epoch [##############################################....] 92.00%
14000 iter, 17 epoch / 20 epochs
114.21 iters/sec. Estimated time to finish: 0:00:14.228447.
[4A[J18 0.293841 1.30144 0.895387 0.682325 124.524
[J total [#############################################.....] 90.24%
this epoch [##................................................] 4.80%
14100 iter, 18 epoch / 20 epochs
113.33 iters/sec. Estimated time to finish: 0:00:13.456653.
[4A[J total [#############################################.....] 90.88%
this epoch [########..........................................] 17.60%
14200 iter, 18 epoch / 20 epochs
113.4 iters/sec. Estimated time to finish: 0:00:12.566670.
[4A[J total [#############################################.....] 91.52%
this epoch [###############...................................] 30.40%
14300 iter, 18 epoch / 20 epochs
113.38 iters/sec. Estimated time to finish: 0:00:11.686217.
[4A[J total [##############################################....] 92.16%
this epoch [#####################.............................] 43.20%
14400 iter, 18 epoch / 20 epochs
113.38 iters/sec. Estimated time to finish: 0:00:10.804028.
[4A[J total [##############################################....] 92.80%
this epoch [###########################.......................] 56.00%
14500 iter, 18 epoch / 20 epochs
113.39 iters/sec. Estimated time to finish: 0:00:09.921756.
[4A[J total [##############################################....] 93.44%
this epoch [##################################................] 68.80%
14600 iter, 18 epoch / 20 epochs
113.38 iters/sec. Estimated time to finish: 0:00:09.040132.
[4A[J total [###############################################...] 94.08%
this epoch [########################################..........] 81.60%
14700 iter, 18 epoch / 20 epochs
114.32 iters/sec. Estimated time to finish: 0:00:08.091500.
[4A[J total [###############################################...] 94.72%
this epoch [###############################################...] 94.40%
14800 iter, 18 epoch / 20 epochs
114.33 iters/sec. Estimated time to finish: 0:00:07.215960.
[4A[J19 0.274091 1.40398 0.901248 0.678344 131.382
[J total [###############################################...] 95.36%
this epoch [###...............................................] 7.20%
14900 iter, 19 epoch / 20 epochs
113.36 iters/sec. Estimated time to finish: 0:00:06.395292.
[4A[J total [################################################..] 96.00%
this epoch [#########.........................................] 20.00%
15000 iter, 19 epoch / 20 epochs
113.37 iters/sec. Estimated time to finish: 0:00:05.512862.
[4A[J total [################################################..] 96.64%
this epoch [################..................................] 32.80%
15100 iter, 19 epoch / 20 epochs
113.36 iters/sec. Estimated time to finish: 0:00:04.631149.
[4A[J total [################################################..] 97.28%
this epoch [######################............................] 45.60%
15200 iter, 19 epoch / 20 epochs
113.34 iters/sec. Estimated time to finish: 0:00:03.749654.
[4A[J total [################################################..] 97.92%
this epoch [#############################.....................] 58.40%
15300 iter, 19 epoch / 20 epochs
113.34 iters/sec. Estimated time to finish: 0:00:02.867473.
[4A[J total [#################################################.] 98.56%
this epoch [###################################...............] 71.20%
15400 iter, 19 epoch / 20 epochs
113.34 iters/sec. Estimated time to finish: 0:00:01.985093.
[4A[J total [#################################################.] 99.20%
this epoch [#########################################.........] 84.00%
15500 iter, 19 epoch / 20 epochs
114.3 iters/sec. Estimated time to finish: 0:00:01.093661.
[4A[J total [#################################################.] 99.84%
this epoch [################################################..] 96.80%
15600 iter, 19 epoch / 20 epochs
114.3 iters/sec. Estimated time to finish: 0:00:00.218720.
[4A[J20 0.263402 1.40445 0.90505 0.683519 138.239
[J
serializers.save_npz('{}/{}-cifar10.model'
.format(args.out, args.arch), model)
Chainer将训练过程抽象化，因此代码可以与其他深度学习训练一起重复使用。
CIFAR-10推断部分代码:
CIFAR10_LABELS_LIST = [
'airplane',
'automobile',
'bird',
'cat',
'deer',
'dog',
'frog',
'horse',
'ship',
'truck'
]
def plot_predict_cifar(filepath, model, data, row, col,
scale=3., label_list=None):
fig_width = data[0][0].shape[1] / 80 * row * scale
fig_height = data[0][0].shape[2] / 80 * col * scale
fig, axes = plt.subplots(row,
col,
figsize=(fig_height, fig_width))
for i in range(row * col):
# train[i][0] is i-th image data with size 32x32
image, label_index = data[i]
xp = cuda.cupy
x = Variable(xp.asarray(image.reshape(1, 3, 32, 32))) # test data
#t = Variable(xp.asarray([test[i][1]])) # labels
y = model(x) # Inference result
prediction = y.data.argmax(axis=1)
image = image.transpose(1, 2, 0)
print('Predicted {}-th image, prediction={}, actual={}'
.format(i, prediction[0], label_index))
r, c = divmod(i, col)
axes[r][c].imshow(image) # cmap='gray' is for black and white picture.
if label_list is None:
axes[r][c].set_title('Predict:{}, Answer: {}'
.format(label_index, prediction[0]))
else:
pred = int(prediction[0])
axes[r][c].set_title('Predict:{} {}\nAnswer:{} {}'
.format(label_index, label_list[label_index],
pred, label_list[pred]))
axes[r][c].axis('off') # do not show axis value
plt.tight_layout(pad=0.01) # automatic padding between subplots
plt.savefig(filepath)
print('Result saved to {}'.format(filepath))
from chainer import training, iterators, serializers, optimizers, Variable, cuda
basedir = 'images'
plot_predict_cifar(os.path.join(basedir, 'cifar10_predict.png'), model,
train, 4, 5, scale=5., label_list=CIFAR10_LABELS_LIST)
Predicted 0-th image, prediction=6, actual=6
Predicted 1-th image, prediction=9, actual=9
Predicted 2-th image, prediction=9, actual=9
Predicted 3-th image, prediction=4, actual=4
Predicted 4-th image, prediction=1, actual=1
Predicted 5-th image, prediction=1, actual=1
Predicted 6-th image, prediction=2, actual=2
Predicted 7-th image, prediction=7, actual=7
Predicted 8-th image, prediction=8, actual=8
Predicted 9-th image, prediction=5, actual=3
Predicted 10-th image, prediction=4, actual=4
Predicted 11-th image, prediction=7, actual=7
Predicted 12-th image, prediction=7, actual=7
Predicted 13-th image, prediction=2, actual=2
Predicted 14-th image, prediction=9, actual=9
Predicted 15-th image, prediction=9, actual=9
Predicted 16-th image, prediction=9, actual=9
Predicted 17-th image, prediction=4, actual=3
Predicted 18-th image, prediction=2, actual=2
Predicted 19-th image, prediction=6, actual=6
Result saved to images/cifar10_predict.png
你可以看到，我们定义的CNN，它能成功分类大部分图像。当然，这只是一个简单的例子，您可以通过调整深度神经网络来提高模型精度！