activation='relu',
pooling=True,
name='conv2')
net.add_conv(patch_size=3,
in_depth=16,
out_depth=16,
activation='relu',
pooling=False,
name='conv3')
net.add_conv(patch_size=3,
in_depth=16,
out_depth=16,
activation='relu',
pooling=True,
name='conv4')
# 4 = 两次 pooling, 每一次缩小为 1/2
# 16 = conv4 out_depth
net.add_fc(in_num_nodes=(image_size // 4) * (image_size // 4) * 16,
out_num_nodes=16,
activation='relu',
name='fc1')
net.add_fc(in_num_nodes=16, out_num_nodes=10, activation=None, name='fc2')
net.define_model()
net.run(get_chunk, train_samples, train_labels, test_samples, test_labels)
else:
raise Exception(
'main.py: Should Not Be Imported!!! Must Run by "python main.py"')
net.add_conv(patch_size=3,
in_depth=64,
out_depth=128,
activation='relu',
pooling=False,
name='conv4')
net.add_conv(patch_size=3,
in_depth=128,
out_depth=128,
activation='relu',
pooling=True,
name='conv5')
# 4 = 两次 pooling, 每一次缩小为 1/2
# 64 = conv4 out_depth
net.add_fc(in_num_nodes=(48 // 8) * (48 // 8) * 128,
out_num_nodes=1024,
activation='relu',
name='fc1')
net.add_fc(in_num_nodes=1024,
out_num_nodes=256,
activation='relu',
name='fc2')
net.add_fc(in_num_nodes=256, out_num_nodes=7, activation=None, name='fc3')
net.define_model()
#net.run(train_samples, train_labels, test_samples, test_labels, train_data_iterator=train_data_iterator, iteration_steps=3000, test_data_iterator=test_data_iterator)
net.train(train_samples,
train_labels,
data_iterator=train_data_iterator,
iteration_steps=3000)
net.test(test_samples, test_labels, data_iterator=test_data_iterator)
#net.test(val_samples, val_labels, data_iterator=test_data_iterator)
net = Network(
train_batch_size=64, test_batch_size=500, pooling_scale=2,
dropout_rate=0.9,
base_learning_rate=0.001, decay_rate=0.99)
net.define_inputs(
train_samples_shape=(64, image_size, image_size, num_channels),
train_labels_shape=(64, num_labels),
test_samples_shape=(500, image_size, image_size, num_channels),
)
#
net.add_conv(patch_size=3, in_depth=num_channels, out_depth=32, activation='relu', pooling=False, name='conv1')
net.add_conv(patch_size=3, in_depth=32, out_depth=32, activation='relu', pooling=True, name='conv2')
net.add_conv(patch_size=3, in_depth=32, out_depth=32, activation='relu', pooling=False, name='conv3')
net.add_conv(patch_size=3, in_depth=32, out_depth=32, activation='relu', pooling=True, name='conv4')
# 4 = 两次 pooling, 每一次缩小为 1/2
# 32 = conv4 out_depth
net.add_fc(in_num_nodes=(image_size // 4) * (image_size // 4) * 32, out_num_nodes=128, activation='relu',
name='fc1')
net.add_fc(in_num_nodes=128, out_num_nodes=10, activation=None, name='fc2')
net.define_model()
# net.run(train_samples, train_labels, test_samples, test_labels, train_data_iterator=train_data_iterator,
# iteration_steps=3000, test_data_iterator=test_data_iterator)
net.train(train_samples, train_labels, data_iterator=train_data_iterator, iteration_steps=2000)
net.test(test_samples, test_labels, data_iterator=test_data_iterator)
else:
raise Exception('main.py: Should Not Be Imported!!! Must Run by "python main.py"')