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unet_tests.prototxt
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unet_tests.prototxt
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layer {
name: "radar"
type: "HDF5Data"
top: "radar"
top: "image"
hdf5_data_param {
source: "test.txt"
batch_size: 1
}
}
layer {
name: "Convolution1"
type: "Convolution"
bottom: "radar"
top: "Convolution1"
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm1"
type: "BatchReNorm"
bottom: "Convolution1"
top: "BatchReNorm1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale1"
type: "Scale"
bottom: "BatchReNorm1"
top: "BatchReNorm1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU1"
type: "ReLU"
bottom: "BatchReNorm1"
top: "BatchReNorm1"
}
layer {
name: "Convolution2"
type: "Convolution"
bottom: "BatchReNorm1"
top: "Convolution2"
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm2"
type: "BatchReNorm"
bottom: "Convolution2"
top: "BatchReNorm2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale2"
type: "Scale"
bottom: "BatchReNorm2"
top: "BatchReNorm2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU2"
type: "ReLU"
bottom: "BatchReNorm2"
top: "BatchReNorm2"
}
layer {
name: "Pooling1"
type: "Pooling"
bottom: "BatchReNorm2"
top: "Pooling1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
pad: 0
}
}
layer {
name: "Convolution3"
type: "Convolution"
bottom: "Pooling1"
top: "Convolution3"
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm3"
type: "BatchReNorm"
bottom: "Convolution3"
top: "BatchReNorm3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale3"
type: "Scale"
bottom: "BatchReNorm3"
top: "BatchReNorm3"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU3"
type: "ReLU"
bottom: "BatchReNorm3"
top: "BatchReNorm3"
}
layer {
name: "Convolution4"
type: "Convolution"
bottom: "BatchReNorm3"
top: "Convolution4"
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm4"
type: "BatchReNorm"
bottom: "Convolution4"
top: "BatchReNorm4"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale4"
type: "Scale"
bottom: "BatchReNorm4"
top: "BatchReNorm4"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU4"
type: "ReLU"
bottom: "BatchReNorm4"
top: "BatchReNorm4"
}
layer {
name: "Pooling2"
type: "Pooling"
bottom: "BatchReNorm4"
top: "Pooling2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
pad: 0
}
}
layer {
name: "Convolution5"
type: "Convolution"
bottom: "Pooling2"
top: "Convolution5"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm5"
type: "BatchReNorm"
bottom: "Convolution5"
top: "BatchReNorm5"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale5"
type: "Scale"
bottom: "BatchReNorm5"
top: "BatchReNorm5"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU5"
type: "ReLU"
bottom: "BatchReNorm5"
top: "BatchReNorm5"
}
layer {
name: "Convolution6"
type: "Convolution"
bottom: "BatchReNorm5"
top: "Convolution6"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm6"
type: "BatchReNorm"
bottom: "Convolution6"
top: "BatchReNorm6"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale6"
type: "Scale"
bottom: "BatchReNorm6"
top: "BatchReNorm6"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU6"
type: "ReLU"
bottom: "BatchReNorm6"
top: "BatchReNorm6"
}
layer {
name: "Pooling3"
type: "Pooling"
bottom: "BatchReNorm6"
top: "Pooling3"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
pad: 0
}
}
layer {
name: "Convolution7"
type: "Convolution"
bottom: "Pooling3"
top: "Convolution7"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm7"
type: "BatchReNorm"
bottom: "Convolution7"
top: "BatchReNorm7"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale7"
type: "Scale"
bottom: "BatchReNorm7"
top: "BatchReNorm7"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU7"
type: "ReLU"
bottom: "BatchReNorm7"
top: "BatchReNorm7"
}
layer {
name: "Convolution8"
type: "Convolution"
bottom: "BatchReNorm7"
top: "Convolution8"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm8"
type: "BatchReNorm"
bottom: "Convolution8"
top: "BatchReNorm8"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale8"
type: "Scale"
bottom: "BatchReNorm8"
top: "BatchReNorm8"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU8"
type: "ReLU"
bottom: "BatchReNorm8"
top: "BatchReNorm8"
}
layer {
name: "Dropout1"
type: "Dropout"
bottom: "BatchReNorm8"
top: "BatchReNorm8"
}
layer {
name: "Pooling4"
type: "Pooling"
bottom: "BatchReNorm8"
top: "Pooling4"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
pad: 0
}
}
layer {
name: "Convolution9"
type: "Convolution"
bottom: "Pooling4"
top: "Convolution9"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm9"
type: "BatchReNorm"
bottom: "Convolution9"
top: "BatchReNorm9"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale9"
type: "Scale"
bottom: "BatchReNorm9"
top: "BatchReNorm9"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU9"
type: "ReLU"
bottom: "BatchReNorm9"
top: "BatchReNorm9"
}
layer {
name: "Convolution10"
type: "Convolution"
bottom: "BatchReNorm9"
top: "Convolution10"
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm10"
type: "BatchReNorm"
bottom: "Convolution10"
top: "BatchReNorm10"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale10"
type: "Scale"
bottom: "BatchReNorm10"
top: "BatchReNorm10"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU10"
type: "ReLU"
bottom: "BatchReNorm10"
top: "BatchReNorm10"
}
layer {
name: "Dropout2"
type: "Dropout"
bottom: "BatchReNorm10"
top: "BatchReNorm10"
}
layer {
name: "Deconvolution1"
type: "Deconvolution"
bottom: "BatchReNorm10"
top: "Deconvolution1"
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 2
group: 256
stride: 2
weight_filler {
type: "bilinear"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm11"
type: "BatchReNorm"
bottom: "Deconvolution1"
top: "BatchReNorm11"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale11"
type: "Scale"
bottom: "BatchReNorm11"
top: "BatchReNorm11"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU11"
type: "ReLU"
bottom: "BatchReNorm11"
top: "BatchReNorm11"
}
layer {
name: "Crop1"
type: "Crop"
bottom: "BatchReNorm8"
bottom: "BatchReNorm11"
top: "Crop1"
crop_param {
axis: 2
offset: 0
}
}
layer {
name: "Concat1"
type: "Concat"
bottom: "BatchReNorm11"
bottom: "Crop1"
top: "Concat1"
}
layer {
name: "Convolution11"
type: "Convolution"
bottom: "Concat1"
top: "Convolution11"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm12"
type: "BatchReNorm"
bottom: "Convolution11"
top: "BatchReNorm12"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale12"
type: "Scale"
bottom: "BatchReNorm12"
top: "BatchReNorm12"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU12"
type: "ReLU"
bottom: "BatchReNorm12"
top: "BatchReNorm12"
}
layer {
name: "Convolution12"
type: "Convolution"
bottom: "BatchReNorm12"
top: "Convolution12"
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm13"
type: "BatchReNorm"
bottom: "Convolution12"
top: "BatchReNorm13"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale13"
type: "Scale"
bottom: "BatchReNorm13"
top: "BatchReNorm13"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU13"
type: "ReLU"
bottom: "BatchReNorm13"
top: "BatchReNorm13"
}
layer {
name: "Deconvolution2"
type: "Deconvolution"
bottom: "BatchReNorm13"
top: "Deconvolution2"
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 2
group: 128
stride: 2
weight_filler {
type: "bilinear"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm14"
type: "BatchReNorm"
bottom: "Deconvolution2"
top: "BatchReNorm14"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale14"
type: "Scale"
bottom: "BatchReNorm14"
top: "BatchReNorm14"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU14"
type: "ReLU"
bottom: "BatchReNorm14"
top: "BatchReNorm14"
}
layer {
name: "Crop2"
type: "Crop"
bottom: "BatchReNorm6"
bottom: "BatchReNorm14"
top: "Crop2"
crop_param {
axis: 2
offset: 0
}
}
layer {
name: "Concat2"
type: "Concat"
bottom: "BatchReNorm14"
bottom: "Crop2"
top: "Concat2"
}
layer {
name: "Convolution13"
type: "Convolution"
bottom: "Concat2"
top: "Convolution13"
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchReNorm15"
type: "BatchReNorm"
bottom: "Convolution13"
top: "BatchReNorm15"