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name: "Colornet" | ||
layer { | ||
name: "img_lab" | ||
top: "img_lab" # Lab color space | ||
type: "Input" | ||
input_param { shape { dim: 1 dim: 3 dim: 227 dim: 227 } } | ||
} | ||
# ************************** | ||
# ***** PROCESS COLORS ***** | ||
# ************************** | ||
# layer { # Convert to lab | ||
# name: "img_lab" | ||
# type: "ColorConv" | ||
# bottom: "data" | ||
# top: "img_lab" | ||
# propagate_down: false | ||
# color_conv_param { | ||
# input: 0 # BGR | ||
# output: 3 # Lab | ||
# } | ||
# } | ||
layer { | ||
name: "img_slice" | ||
type: "Slice" | ||
bottom: "img_lab" | ||
top: "img_l" # [0,100] | ||
top: "data_ab" # [-110,110] | ||
propagate_down: false | ||
slice_param { | ||
axis: 1 | ||
slice_point: 1 | ||
} | ||
} | ||
layer { | ||
name: "silence_ab" | ||
type: "Silence" | ||
bottom: "data_ab" | ||
} | ||
layer { # 0-center lightness channel | ||
name: "data_l" | ||
type: "Convolution" | ||
bottom: "img_l" | ||
top: "data_l" # scaled and centered lightness value | ||
propagate_down: false | ||
param {lr_mult: 0 decay_mult: 0} | ||
param {lr_mult: 0 decay_mult: 0} | ||
convolution_param { | ||
kernel_size: 1 | ||
num_output: 1 | ||
} | ||
} | ||
layer { | ||
name: "conv1" | ||
type: "Convolution" | ||
bottom: "data_l" | ||
top: "conv1" | ||
param { lr_mult: 1 decay_mult: 1 } | ||
param { lr_mult: 2 decay_mult: 0 } | ||
convolution_param { | ||
num_output: 96 | ||
kernel_size: 11 | ||
stride: 4 | ||
weight_filler { | ||
type: "gaussian" | ||
std: 0.01 | ||
} | ||
bias_filler { | ||
type: "constant" | ||
value: 0 | ||
} | ||
} | ||
} | ||
layer { | ||
name: "relu1" | ||
type: "ReLU" | ||
bottom: "conv1" | ||
top: "conv1" | ||
} | ||
layer { | ||
name: "pool1" | ||
type: "Pooling" | ||
bottom: "conv1" | ||
top: "pool1" | ||
pooling_param { | ||
pool: MAX | ||
kernel_size: 3 | ||
stride: 2 | ||
} | ||
} | ||
layer { | ||
name: "conv2" | ||
type: "Convolution" | ||
bottom: "pool1" | ||
top: "conv2" | ||
param { lr_mult: 1 decay_mult: 1 } | ||
param { lr_mult: 2 decay_mult: 0 } | ||
convolution_param { | ||
num_output: 256 | ||
pad: 2 | ||
kernel_size: 5 | ||
group: 2 | ||
weight_filler { | ||
type: "gaussian" | ||
std: 0.01 | ||
} | ||
bias_filler { | ||
type: "constant" | ||
value: 1 | ||
} | ||
} | ||
} | ||
layer { | ||
name: "relu2" | ||
type: "ReLU" | ||
bottom: "conv2" | ||
top: "conv2" | ||
} | ||
layer { | ||
name: "pool2" | ||
type: "Pooling" | ||
bottom: "conv2" | ||
top: "pool2" | ||
pooling_param { | ||
pool: MAX | ||
kernel_size: 3 | ||
stride: 2 | ||
} | ||
} | ||
layer { | ||
name: "conv3" | ||
type: "Convolution" | ||
bottom: "pool2" | ||
top: "conv3" | ||
param { lr_mult: 1 decay_mult: 1 } | ||
param { lr_mult: 2 decay_mult: 0 } | ||
convolution_param { | ||
num_output: 384 | ||
pad: 1 | ||
kernel_size: 3 | ||
weight_filler { | ||
type: "gaussian" | ||
std: 0.01 | ||
} | ||
bias_filler { | ||
type: "constant" | ||
value: 0 | ||
} | ||
} | ||
} | ||
layer { | ||
name: "relu3" | ||
type: "ReLU" | ||
bottom: "conv3" | ||
top: "conv3" | ||
} | ||
layer { | ||
name: "conv4" | ||
type: "Convolution" | ||
bottom: "conv3" | ||
top: "conv4" | ||
param { lr_mult: 1 decay_mult: 1 } | ||
param { lr_mult: 2 decay_mult: 0 } | ||
convolution_param { | ||
num_output: 384 | ||
pad: 1 | ||
kernel_size: 3 | ||
group: 2 | ||
weight_filler { | ||
type: "gaussian" | ||
std: 0.01 | ||
} | ||
bias_filler { | ||
type: "constant" | ||
value: 1 | ||
} | ||
} | ||
} | ||
layer { | ||
name: "relu4" | ||
type: "ReLU" | ||
bottom: "conv4" | ||
top: "conv4" | ||
} | ||
layer { | ||
name: "conv5" | ||
type: "Convolution" | ||
bottom: "conv4" | ||
top: "conv5" | ||
param { lr_mult: 1 decay_mult: 1 } | ||
param { lr_mult: 2 decay_mult: 0 } | ||
convolution_param { | ||
num_output: 256 | ||
pad: 1 | ||
kernel_size: 3 | ||
group: 2 | ||
weight_filler { | ||
type: "gaussian" | ||
std: 0.01 | ||
} | ||
bias_filler { | ||
type: "constant" | ||
value: 1 | ||
} | ||
} | ||
} | ||
layer { | ||
name: "relu5" | ||
type: "ReLU" | ||
bottom: "conv5" | ||
top: "conv5" | ||
} | ||
layer { | ||
name: "pool5" | ||
type: "Pooling" | ||
bottom: "conv5" | ||
top: "pool5" | ||
pooling_param { | ||
pool: MAX | ||
kernel_size: 3 | ||
stride: 2 | ||
} | ||
} | ||
layer { | ||
name: "fc6" | ||
type: "InnerProduct" | ||
bottom: "pool5" | ||
top: "fc6" | ||
param { lr_mult: 1 decay_mult: 1 } | ||
param { lr_mult: 2 decay_mult: 0 } | ||
inner_product_param { | ||
num_output: 4096 | ||
} | ||
} | ||
layer { | ||
name: "relu6" | ||
type: "ReLU" | ||
bottom: "fc6" | ||
top: "fc6" | ||
} | ||
layer { | ||
name: "drop6" | ||
type: "Dropout" | ||
bottom: "fc6" | ||
top: "fc6" | ||
dropout_param { | ||
dropout_ratio: 0.5 | ||
} | ||
} | ||
layer { | ||
name: "fc7" | ||
type: "InnerProduct" | ||
bottom: "fc6" | ||
top: "fc7" | ||
param { lr_mult: 1 decay_mult: 1 } | ||
param { lr_mult: 2 decay_mult: 0 } | ||
inner_product_param { | ||
num_output: 4096 | ||
} | ||
} | ||
layer { | ||
name: "relu7" | ||
type: "ReLU" | ||
bottom: "fc7" | ||
top: "fc7" | ||
} | ||
layer { | ||
name: "drop7" | ||
type: "Dropout" | ||
bottom: "fc7" | ||
top: "fc7" | ||
dropout_param { | ||
dropout_ratio: 0.5 | ||
} | ||
} |
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