darknet19的配置文件

[net]
batch=128
subdivisions=1
height=224
width=224
channels=3//图像的通道数
momentum=0.9//动量
decay=0.0005、、权重衰减正则项，防止过拟合
max_crop=448

learning_rate=0.1、、初始学习率
policy=poly、、随着迭代次数的增加不断调整
power=4、、pow开方的次数
max_batches=1600000、、最大迭代次数

[convolutional]
batch_normalize=1、、是否做bn处理
filters=32、、输出多少个特征图
size=3、、卷积核的尺寸
stride=1、、做卷积运算的步长
pad=1、、如果pad为0,padding由 padding参数指定。如果pad为1，padding大小为size/2
activation=leaky

[maxpool]
size=2、、池化的尺寸
stride=2、、池化的步长

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

[convolutional]
filters=1000
size=1
stride=1
pad=1
activation=linear

[avgpool]

[softmax]
groups=1

[cost]
type=sse//拟合数据和真实数据对应的误差平方和