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orn.prototxt
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orn.prototxt
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name: "ORN"
layer {
name: "mnist"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
scale: 0.00390625
}
data_param {
source: "dataset/mnist_rot_train_lmdb"
batch_size: 128
backend: LMDB
}
}
layer {
name: "mnist"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
scale: 0.00390625
}
data_param {
source: "dataset/mnist_rot_test_lmdb"
batch_size: 1000
backend: LMDB
}
}
#-------------------------------------
layer {
type: "Extend"
name: "Extend" bottom: "data" top: "Extend"
orn_param {orientations: 8}
}
layer {
type: "Convolution"
name: "ORConv1" bottom: "Extend" top: "ORConv1"
orn_param {orientations: 8}
param { lr_mult: 1 decay_mult: 2}
convolution_param {
num_output: 80
kernel_size: 3
stride: 1
pad: 0
weight_filler { type: "msra"}
bias_filler { type: "constant" value: 0}
}
}
layer {
type: "ReLU"
name: "ReLU1" bottom: "ORConv1" top: "ORConv1"
}
layer {
type: "Pooling"
name: "Pool1" bottom: "ORConv1" top: "Pool1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
type: "Convolution"
name: "ORConv2" bottom: "Pool1" top: "ORConv2"
orn_param {orientations: 8}
param { lr_mult: 1 decay_mult: 2}
convolution_param {
num_output: 160
kernel_size: 3
stride: 1
pad: 0
weight_filler { type: "msra"}
bias_filler { type: "constant" value: 0}
}
}
layer {
type: "ReLU"
name: "ReLU2" bottom: "ORConv2" top: "ORConv2"
}
layer {
type: "Pooling"
name: "Pool2" bottom: "ORConv2" top: "Pool2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
type: "Convolution"
name: "ORConv3" bottom: "Pool2" top: "ORConv3"
orn_param {orientations: 8}
param { lr_mult: 1 decay_mult: 2}
convolution_param {
num_output: 320
kernel_size: 3
stride: 1
pad: 1
weight_filler { type: "msra"}
bias_filler { type: "constant" value: 0}
}
}
layer {
type: "ReLU"
name: "ReLU3" bottom: "ORConv3" top: "ORConv3"
}
layer {
type: "Pooling"
name: "Pool3" bottom: "ORConv3" top: "Pool3"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
type: "Convolution"
name: "ORConv4" bottom: "Pool3" top: "ORConv4"
orn_param {orientations: 8}
param { lr_mult: 1 decay_mult: 2}
convolution_param {
num_output: 640
kernel_size: 3
stride: 1
pad: 0
weight_filler { type: "msra"}
bias_filler { type: "constant" value: 0}
}
}
layer {
type: "ReLU"
name: "ReLU4" bottom: "ORConv4" top: "ORConv4"
}
#-------------------------------------
layer {
type: "ORPooling"
name: "ORPool" bottom: "ORConv4" top: "ORPool"
orn_param {orientations: 8}
}
#-------------------------------------
layer {
type: "InnerProduct"
name: "FC1" bottom: "ORPool" top: "FC1"
param { lr_mult: 1 decay_mult: 1 }
param { lr_mult: 2 decay_mult: 0 }
inner_product_param {
num_output: 1024
weight_filler { type: "gaussian" std: 0.01 }
bias_filler { type: "constant" value: 0 }
}
}
layer {
type: "ReLU"
name: "ReLU5" bottom: "FC1" top: "FC1"
}
layer {
type: "Dropout"
name: "Dropout" bottom: "FC1" top: "FC1"
dropout_param { dropout_ratio: 0.5 }
}
layer {
type: "InnerProduct"
name: "FC2" bottom: "FC1" top: "FC2"
param { lr_mult: 1 decay_mult: 1 }
param { lr_mult: 2 decay_mult: 0 }
inner_product_param {
num_output: 10
weight_filler { type: "gaussian" std: 0.01 }
bias_filler { type: "constant" value: 0 }
}
}
#-------------------------------------
layer {
type: "Accuracy"
name: "accuracy" bottom: "FC2" bottom: "label" top: "accuracy"
include { phase: TEST }
}
layer {
type: "SoftmaxWithLoss"
name: "loss" bottom: "FC2" bottom: "label" top: "loss"
}