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caffe image recognization model and prototxt for transfer learning (fine-tuning)
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name: "GoogleNet" | |
layer { | |
name: "data" | |
type: "Input" | |
top: "data" | |
input_param { shape: { dim: 10 dim: 3 dim: 224 dim: 224 } } | |
} | |
layer { | |
name: "conv1/7x7_s2" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1/7x7_s2" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 3 | |
kernel_size: 7 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "conv1/relu_7x7" | |
type: "ReLU" | |
bottom: "conv1/7x7_s2" | |
top: "conv1/7x7_s2" | |
} | |
layer { | |
name: "pool1/3x3_s2" | |
type: "Pooling" | |
bottom: "conv1/7x7_s2" | |
top: "pool1/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "pool1/norm1" | |
type: "LRN" | |
bottom: "pool1/3x3_s2" | |
top: "pool1/norm1" | |
lrn_param { | |
local_size: 5 | |
alpha: 0.0001 | |
beta: 0.75 | |
} | |
} | |
layer { | |
name: "conv2/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool1/norm1" | |
top: "conv2/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "conv2/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "conv2/3x3_reduce" | |
top: "conv2/3x3_reduce" | |
} | |
layer { | |
name: "conv2/3x3" | |
type: "Convolution" | |
bottom: "conv2/3x3_reduce" | |
top: "conv2/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "conv2/relu_3x3" | |
type: "ReLU" | |
bottom: "conv2/3x3" | |
top: "conv2/3x3" | |
} | |
layer { | |
name: "conv2/norm2" | |
type: "LRN" | |
bottom: "conv2/3x3" | |
top: "conv2/norm2" | |
lrn_param { | |
local_size: 5 | |
alpha: 0.0001 | |
beta: 0.75 | |
} | |
} | |
layer { | |
name: "pool2/3x3_s2" | |
type: "Pooling" | |
bottom: "conv2/norm2" | |
top: "pool2/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "inception_3a/1x1" | |
type: "Convolution" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_3a/1x1" | |
top: "inception_3a/1x1" | |
} | |
layer { | |
name: "inception_3a/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 96 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_3a/3x3_reduce" | |
top: "inception_3a/3x3_reduce" | |
} | |
layer { | |
name: "inception_3a/3x3" | |
type: "Convolution" | |
bottom: "inception_3a/3x3_reduce" | |
top: "inception_3a/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_3a/3x3" | |
top: "inception_3a/3x3" | |
} | |
layer { | |
name: "inception_3a/5x5_reduce" | |
type: "Convolution" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_3a/5x5_reduce" | |
top: "inception_3a/5x5_reduce" | |
} | |
layer { | |
name: "inception_3a/5x5" | |
type: "Convolution" | |
bottom: "inception_3a/5x5_reduce" | |
top: "inception_3a/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_3a/5x5" | |
top: "inception_3a/5x5" | |
} | |
layer { | |
name: "inception_3a/pool" | |
type: "Pooling" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_3a/pool_proj" | |
type: "Convolution" | |
bottom: "inception_3a/pool" | |
top: "inception_3a/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_3a/pool_proj" | |
top: "inception_3a/pool_proj" | |
} | |
layer { | |
name: "inception_3a/output" | |
type: "Concat" | |
bottom: "inception_3a/1x1" | |
bottom: "inception_3a/3x3" | |
bottom: "inception_3a/5x5" | |
bottom: "inception_3a/pool_proj" | |
top: "inception_3a/output" | |
} | |
layer { | |
name: "inception_3b/1x1" | |
type: "Convolution" | |
bottom: "inception_3a/output" | |
top: "inception_3b/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_3b/1x1" | |
top: "inception_3b/1x1" | |
} | |
layer { | |
name: "inception_3b/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_3a/output" | |
top: "inception_3b/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_3b/3x3_reduce" | |
top: "inception_3b/3x3_reduce" | |
} | |
layer { | |
name: "inception_3b/3x3" | |
type: "Convolution" | |
bottom: "inception_3b/3x3_reduce" | |
top: "inception_3b/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_3b/3x3" | |
top: "inception_3b/3x3" | |
} | |
layer { | |
name: "inception_3b/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_3a/output" | |
top: "inception_3b/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_3b/5x5_reduce" | |
top: "inception_3b/5x5_reduce" | |
} | |
layer { | |
name: "inception_3b/5x5" | |
type: "Convolution" | |
bottom: "inception_3b/5x5_reduce" | |
top: "inception_3b/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 96 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_3b/5x5" | |
top: "inception_3b/5x5" | |
} | |
layer { | |
name: "inception_3b/pool" | |
type: "Pooling" | |
bottom: "inception_3a/output" | |
top: "inception_3b/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_3b/pool_proj" | |
type: "Convolution" | |
bottom: "inception_3b/pool" | |
top: "inception_3b/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_3b/pool_proj" | |
top: "inception_3b/pool_proj" | |
} | |
layer { | |
name: "inception_3b/output" | |
type: "Concat" | |
bottom: "inception_3b/1x1" | |
bottom: "inception_3b/3x3" | |
bottom: "inception_3b/5x5" | |
bottom: "inception_3b/pool_proj" | |
top: "inception_3b/output" | |
} | |
layer { | |
name: "pool3/3x3_s2" | |
type: "Pooling" | |
bottom: "inception_3b/output" | |
top: "pool3/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "inception_4a/1x1" | |
type: "Convolution" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4a/1x1" | |
top: "inception_4a/1x1" | |
} | |
layer { | |
name: "inception_4a/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 96 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4a/3x3_reduce" | |
top: "inception_4a/3x3_reduce" | |
} | |
layer { | |
name: "inception_4a/3x3" | |
type: "Convolution" | |
bottom: "inception_4a/3x3_reduce" | |
top: "inception_4a/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 208 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4a/3x3" | |
top: "inception_4a/3x3" | |
} | |
layer { | |
name: "inception_4a/5x5_reduce" | |
type: "Convolution" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4a/5x5_reduce" | |
top: "inception_4a/5x5_reduce" | |
} | |
layer { | |
name: "inception_4a/5x5" | |
type: "Convolution" | |
bottom: "inception_4a/5x5_reduce" | |
top: "inception_4a/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 48 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4a/5x5" | |
top: "inception_4a/5x5" | |
} | |
layer { | |
name: "inception_4a/pool" | |
type: "Pooling" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4a/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4a/pool" | |
top: "inception_4a/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4a/pool_proj" | |
top: "inception_4a/pool_proj" | |
} | |
layer { | |
name: "inception_4a/output" | |
type: "Concat" | |
bottom: "inception_4a/1x1" | |
bottom: "inception_4a/3x3" | |
bottom: "inception_4a/5x5" | |
bottom: "inception_4a/pool_proj" | |
top: "inception_4a/output" | |
} | |
layer { | |
name: "inception_4b/1x1" | |
type: "Convolution" | |
bottom: "inception_4a/output" | |
top: "inception_4b/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 160 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4b/1x1" | |
top: "inception_4b/1x1" | |
} | |
layer { | |
name: "inception_4b/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4a/output" | |
top: "inception_4b/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 112 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4b/3x3_reduce" | |
top: "inception_4b/3x3_reduce" | |
} | |
layer { | |
name: "inception_4b/3x3" | |
type: "Convolution" | |
bottom: "inception_4b/3x3_reduce" | |
top: "inception_4b/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 224 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4b/3x3" | |
top: "inception_4b/3x3" | |
} | |
layer { | |
name: "inception_4b/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4a/output" | |
top: "inception_4b/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4b/5x5_reduce" | |
top: "inception_4b/5x5_reduce" | |
} | |
layer { | |
name: "inception_4b/5x5" | |
type: "Convolution" | |
bottom: "inception_4b/5x5_reduce" | |
top: "inception_4b/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4b/5x5" | |
top: "inception_4b/5x5" | |
} | |
layer { | |
name: "inception_4b/pool" | |
type: "Pooling" | |
bottom: "inception_4a/output" | |
top: "inception_4b/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4b/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4b/pool" | |
top: "inception_4b/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4b/pool_proj" | |
top: "inception_4b/pool_proj" | |
} | |
layer { | |
name: "inception_4b/output" | |
type: "Concat" | |
bottom: "inception_4b/1x1" | |
bottom: "inception_4b/3x3" | |
bottom: "inception_4b/5x5" | |
bottom: "inception_4b/pool_proj" | |
top: "inception_4b/output" | |
} | |
layer { | |
name: "inception_4c/1x1" | |
type: "Convolution" | |
bottom: "inception_4b/output" | |
top: "inception_4c/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4c/1x1" | |
top: "inception_4c/1x1" | |
} | |
layer { | |
name: "inception_4c/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4b/output" | |
top: "inception_4c/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4c/3x3_reduce" | |
top: "inception_4c/3x3_reduce" | |
} | |
layer { | |
name: "inception_4c/3x3" | |
type: "Convolution" | |
bottom: "inception_4c/3x3_reduce" | |
top: "inception_4c/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4c/3x3" | |
top: "inception_4c/3x3" | |
} | |
layer { | |
name: "inception_4c/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4b/output" | |
top: "inception_4c/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4c/5x5_reduce" | |
top: "inception_4c/5x5_reduce" | |
} | |
layer { | |
name: "inception_4c/5x5" | |
type: "Convolution" | |
bottom: "inception_4c/5x5_reduce" | |
top: "inception_4c/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4c/5x5" | |
top: "inception_4c/5x5" | |
} | |
layer { | |
name: "inception_4c/pool" | |
type: "Pooling" | |
bottom: "inception_4b/output" | |
top: "inception_4c/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4c/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4c/pool" | |
top: "inception_4c/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4c/pool_proj" | |
top: "inception_4c/pool_proj" | |
} | |
layer { | |
name: "inception_4c/output" | |
type: "Concat" | |
bottom: "inception_4c/1x1" | |
bottom: "inception_4c/3x3" | |
bottom: "inception_4c/5x5" | |
bottom: "inception_4c/pool_proj" | |
top: "inception_4c/output" | |
} | |
layer { | |
name: "inception_4d/1x1" | |
type: "Convolution" | |
bottom: "inception_4c/output" | |
top: "inception_4d/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 112 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4d/1x1" | |
top: "inception_4d/1x1" | |
} | |
layer { | |
name: "inception_4d/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4c/output" | |
top: "inception_4d/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 144 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4d/3x3_reduce" | |
top: "inception_4d/3x3_reduce" | |
} | |
layer { | |
name: "inception_4d/3x3" | |
type: "Convolution" | |
bottom: "inception_4d/3x3_reduce" | |
top: "inception_4d/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 288 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4d/3x3" | |
top: "inception_4d/3x3" | |
} | |
layer { | |
name: "inception_4d/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4c/output" | |
top: "inception_4d/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4d/5x5_reduce" | |
top: "inception_4d/5x5_reduce" | |
} | |
layer { | |
name: "inception_4d/5x5" | |
type: "Convolution" | |
bottom: "inception_4d/5x5_reduce" | |
top: "inception_4d/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4d/5x5" | |
top: "inception_4d/5x5" | |
} | |
layer { | |
name: "inception_4d/pool" | |
type: "Pooling" | |
bottom: "inception_4c/output" | |
top: "inception_4d/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4d/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4d/pool" | |
top: "inception_4d/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4d/pool_proj" | |
top: "inception_4d/pool_proj" | |
} | |
layer { | |
name: "inception_4d/output" | |
type: "Concat" | |
bottom: "inception_4d/1x1" | |
bottom: "inception_4d/3x3" | |
bottom: "inception_4d/5x5" | |
bottom: "inception_4d/pool_proj" | |
top: "inception_4d/output" | |
} | |
layer { | |
name: "inception_4e/1x1" | |
type: "Convolution" | |
bottom: "inception_4d/output" | |
top: "inception_4e/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4e/1x1" | |
top: "inception_4e/1x1" | |
} | |
layer { | |
name: "inception_4e/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4d/output" | |
top: "inception_4e/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 160 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4e/3x3_reduce" | |
top: "inception_4e/3x3_reduce" | |
} | |
layer { | |
name: "inception_4e/3x3" | |
type: "Convolution" | |
bottom: "inception_4e/3x3_reduce" | |
top: "inception_4e/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 320 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4e/3x3" | |
top: "inception_4e/3x3" | |
} | |
layer { | |
name: "inception_4e/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4d/output" | |
top: "inception_4e/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4e/5x5_reduce" | |
top: "inception_4e/5x5_reduce" | |
} | |
layer { | |
name: "inception_4e/5x5" | |
type: "Convolution" | |
bottom: "inception_4e/5x5_reduce" | |
top: "inception_4e/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4e/5x5" | |
top: "inception_4e/5x5" | |
} | |
layer { | |
name: "inception_4e/pool" | |
type: "Pooling" | |
bottom: "inception_4d/output" | |
top: "inception_4e/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4e/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4e/pool" | |
top: "inception_4e/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4e/pool_proj" | |
top: "inception_4e/pool_proj" | |
} | |
layer { | |
name: "inception_4e/output" | |
type: "Concat" | |
bottom: "inception_4e/1x1" | |
bottom: "inception_4e/3x3" | |
bottom: "inception_4e/5x5" | |
bottom: "inception_4e/pool_proj" | |
top: "inception_4e/output" | |
} | |
layer { | |
name: "pool4/3x3_s2" | |
type: "Pooling" | |
bottom: "inception_4e/output" | |
top: "pool4/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "inception_5a/1x1" | |
type: "Convolution" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_5a/1x1" | |
top: "inception_5a/1x1" | |
} | |
layer { | |
name: "inception_5a/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 160 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_5a/3x3_reduce" | |
top: "inception_5a/3x3_reduce" | |
} | |
layer { | |
name: "inception_5a/3x3" | |
type: "Convolution" | |
bottom: "inception_5a/3x3_reduce" | |
top: "inception_5a/3x3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 320 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_5a/3x3" | |
top: "inception_5a/3x3" | |
} | |
layer { | |
name: "inception_5a/5x5_reduce" | |
type: "Convolution" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_5a/5x5_reduce" | |
top: "inception_5a/5x5_reduce" | |
} | |
layer { | |
name: "inception_5a/5x5" | |
type: "Convolution" | |
bottom: "inception_5a/5x5_reduce" | |
top: "inception_5a/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_5a/5x5" | |
top: "inception_5a/5x5" | |
} | |
layer { | |
name: "inception_5a/pool" | |
type: "Pooling" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_5a/pool_proj" | |
type: "Convolution" | |
bottom: "inception_5a/pool" | |
top: "inception_5a/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_5a/pool_proj" | |
top: "inception_5a/pool_proj" | |
} | |
layer { | |
name: "inception_5a/output" | |
type: "Concat" | |
bottom: "inception_5a/1x1" | |
bottom: "inception_5a/3x3" | |
bottom: "inception_5a/5x5" | |
bottom: "inception_5a/pool_proj" | |
top: "inception_5a/output" | |
} | |
layer { | |
name: "inception_5b/1x1" | |
type: "Convolution" | |
bottom: "inception_5a/output" | |
top: "inception_5b/1x1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 384 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_5b/1x1" | |
top: "inception_5b/1x1" | |
} | |
layer { | |
name: "inception_5b/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_5a/output" | |
top: "inception_5b/3x3_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.09 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_5b/3x3_reduce" | |
top: "inception_5b/3x3_reduce" | |
} | |
layer { | |
name: "inception_5b/3x3" | |
type: "Convolution" | |
bottom: "inception_5b/3x3_reduce" | |
top: "inception_5b/3x3" | |
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: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_5b/3x3" | |
top: "inception_5b/3x3" | |
} | |
layer { | |
name: "inception_5b/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_5a/output" | |
top: "inception_5b/5x5_reduce" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 48 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.2 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_5b/5x5_reduce" | |
top: "inception_5b/5x5_reduce" | |
} | |
layer { | |
name: "inception_5b/5x5" | |
type: "Convolution" | |
bottom: "inception_5b/5x5_reduce" | |
top: "inception_5b/5x5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
std: 0.03 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_5b/5x5" | |
top: "inception_5b/5x5" | |
} | |
layer { | |
name: "inception_5b/pool" | |
type: "Pooling" | |
bottom: "inception_5a/output" | |
top: "inception_5b/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_5b/pool_proj" | |
type: "Convolution" | |
bottom: "inception_5b/pool" | |
top: "inception_5b/pool_proj" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
std: 0.1 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_5b/pool_proj" | |
top: "inception_5b/pool_proj" | |
} | |
layer { | |
name: "inception_5b/output" | |
type: "Concat" | |
bottom: "inception_5b/1x1" | |
bottom: "inception_5b/3x3" | |
bottom: "inception_5b/5x5" | |
bottom: "inception_5b/pool_proj" | |
top: "inception_5b/output" | |
} | |
layer { | |
name: "pool5/7x7_s1" | |
type: "Pooling" | |
bottom: "inception_5b/output" | |
top: "pool5/7x7_s1" | |
pooling_param { | |
pool: AVE | |
kernel_size: 7 | |
stride: 1 | |
} | |
} | |
layer { | |
name: "pool5/drop_7x7_s1" | |
type: "Dropout" | |
bottom: "pool5/7x7_s1" | |
top: "pool5/7x7_s1" | |
dropout_param { | |
dropout_ratio: 0.4 | |
} | |
} | |
layer { | |
name: "fc_out" | |
type: "InnerProduct" | |
bottom: "pool5/7x7_s1" | |
top: "fc_out" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "prob" | |
type: "Softmax" | |
bottom: "fc_out" | |
top: "prob" | |
} |
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net: "/path/to/your/train_val.prototxt" | |
test_iter: 10 | |
test_interval: 300 | |
test_initialization: false | |
display: 40 | |
average_loss: 40 | |
base_lr: 0.001 | |
lr_policy: "step" | |
stepsize: 5000 | |
gamma: 0.96 | |
max_iter: 2000 | |
momentum: 0.9 | |
weight_decay: 0.0002 | |
snapshot: 1000 | |
snapshot_prefix: "/path/to/your/prefix" | |
solver_mode: GPU |
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name: "GoogleNet" | |
layer { | |
name: "data" | |
type: "Data" | |
top: "data" | |
top: "label" | |
include { | |
phase: TRAIN | |
} | |
transform_param { | |
mirror: true | |
crop_size: 224 | |
# mean_value: 104 | |
# mean_value: 117 | |
# mean_value: 123 | |
mean_file: "/path/to/your/mean.binaryproto" | |
} | |
data_param { | |
source: "/path/to/your/img_train_lmdb" | |
batch_size: 30 | |
backend: LMDB | |
} | |
} | |
layer { | |
name: "data" | |
type: "Data" | |
top: "data" | |
top: "label" | |
include { | |
phase: TEST | |
} | |
transform_param { | |
mirror: false | |
crop_size: 224 | |
# mean_value: 104 | |
# mean_value: 117 | |
# mean_value: 123 | |
mean_file: "/path/to/your/mean.binaryproto" | |
} | |
data_param { | |
source: "/path/to/your/img_test_lmdb" | |
batch_size: 30 | |
backend: LMDB | |
} | |
} | |
layer { | |
name: "conv1/7x7_s2" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1/7x7_s2" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 3 | |
kernel_size: 7 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "conv1/relu_7x7" | |
type: "ReLU" | |
bottom: "conv1/7x7_s2" | |
top: "conv1/7x7_s2" | |
} | |
layer { | |
name: "pool1/3x3_s2" | |
type: "Pooling" | |
bottom: "conv1/7x7_s2" | |
top: "pool1/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "pool1/norm1" | |
type: "LRN" | |
bottom: "pool1/3x3_s2" | |
top: "pool1/norm1" | |
lrn_param { | |
local_size: 5 | |
alpha: 0.0001 | |
beta: 0.75 | |
} | |
} | |
layer { | |
name: "conv2/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool1/norm1" | |
top: "conv2/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "conv2/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "conv2/3x3_reduce" | |
top: "conv2/3x3_reduce" | |
} | |
layer { | |
name: "conv2/3x3" | |
type: "Convolution" | |
bottom: "conv2/3x3_reduce" | |
top: "conv2/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "conv2/relu_3x3" | |
type: "ReLU" | |
bottom: "conv2/3x3" | |
top: "conv2/3x3" | |
} | |
layer { | |
name: "conv2/norm2" | |
type: "LRN" | |
bottom: "conv2/3x3" | |
top: "conv2/norm2" | |
lrn_param { | |
local_size: 5 | |
alpha: 0.0001 | |
beta: 0.75 | |
} | |
} | |
layer { | |
name: "pool2/3x3_s2" | |
type: "Pooling" | |
bottom: "conv2/norm2" | |
top: "pool2/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "inception_3a/1x1" | |
type: "Convolution" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_3a/1x1" | |
top: "inception_3a/1x1" | |
} | |
layer { | |
name: "inception_3a/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 96 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_3a/3x3_reduce" | |
top: "inception_3a/3x3_reduce" | |
} | |
layer { | |
name: "inception_3a/3x3" | |
type: "Convolution" | |
bottom: "inception_3a/3x3_reduce" | |
top: "inception_3a/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_3a/3x3" | |
top: "inception_3a/3x3" | |
} | |
layer { | |
name: "inception_3a/5x5_reduce" | |
type: "Convolution" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_3a/5x5_reduce" | |
top: "inception_3a/5x5_reduce" | |
} | |
layer { | |
name: "inception_3a/5x5" | |
type: "Convolution" | |
bottom: "inception_3a/5x5_reduce" | |
top: "inception_3a/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_3a/5x5" | |
top: "inception_3a/5x5" | |
} | |
layer { | |
name: "inception_3a/pool" | |
type: "Pooling" | |
bottom: "pool2/3x3_s2" | |
top: "inception_3a/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_3a/pool_proj" | |
type: "Convolution" | |
bottom: "inception_3a/pool" | |
top: "inception_3a/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3a/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_3a/pool_proj" | |
top: "inception_3a/pool_proj" | |
} | |
layer { | |
name: "inception_3a/output" | |
type: "Concat" | |
bottom: "inception_3a/1x1" | |
bottom: "inception_3a/3x3" | |
bottom: "inception_3a/5x5" | |
bottom: "inception_3a/pool_proj" | |
top: "inception_3a/output" | |
} | |
layer { | |
name: "inception_3b/1x1" | |
type: "Convolution" | |
bottom: "inception_3a/output" | |
top: "inception_3b/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_3b/1x1" | |
top: "inception_3b/1x1" | |
} | |
layer { | |
name: "inception_3b/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_3a/output" | |
top: "inception_3b/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_3b/3x3_reduce" | |
top: "inception_3b/3x3_reduce" | |
} | |
layer { | |
name: "inception_3b/3x3" | |
type: "Convolution" | |
bottom: "inception_3b/3x3_reduce" | |
top: "inception_3b/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_3b/3x3" | |
top: "inception_3b/3x3" | |
} | |
layer { | |
name: "inception_3b/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_3a/output" | |
top: "inception_3b/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_3b/5x5_reduce" | |
top: "inception_3b/5x5_reduce" | |
} | |
layer { | |
name: "inception_3b/5x5" | |
type: "Convolution" | |
bottom: "inception_3b/5x5_reduce" | |
top: "inception_3b/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 96 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_3b/5x5" | |
top: "inception_3b/5x5" | |
} | |
layer { | |
name: "inception_3b/pool" | |
type: "Pooling" | |
bottom: "inception_3a/output" | |
top: "inception_3b/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_3b/pool_proj" | |
type: "Convolution" | |
bottom: "inception_3b/pool" | |
top: "inception_3b/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_3b/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_3b/pool_proj" | |
top: "inception_3b/pool_proj" | |
} | |
layer { | |
name: "inception_3b/output" | |
type: "Concat" | |
bottom: "inception_3b/1x1" | |
bottom: "inception_3b/3x3" | |
bottom: "inception_3b/5x5" | |
bottom: "inception_3b/pool_proj" | |
top: "inception_3b/output" | |
} | |
layer { | |
name: "pool3/3x3_s2" | |
type: "Pooling" | |
bottom: "inception_3b/output" | |
top: "pool3/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "inception_4a/1x1" | |
type: "Convolution" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4a/1x1" | |
top: "inception_4a/1x1" | |
} | |
layer { | |
name: "inception_4a/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 96 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4a/3x3_reduce" | |
top: "inception_4a/3x3_reduce" | |
} | |
layer { | |
name: "inception_4a/3x3" | |
type: "Convolution" | |
bottom: "inception_4a/3x3_reduce" | |
top: "inception_4a/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 208 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4a/3x3" | |
top: "inception_4a/3x3" | |
} | |
layer { | |
name: "inception_4a/5x5_reduce" | |
type: "Convolution" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4a/5x5_reduce" | |
top: "inception_4a/5x5_reduce" | |
} | |
layer { | |
name: "inception_4a/5x5" | |
type: "Convolution" | |
bottom: "inception_4a/5x5_reduce" | |
top: "inception_4a/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 48 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4a/5x5" | |
top: "inception_4a/5x5" | |
} | |
layer { | |
name: "inception_4a/pool" | |
type: "Pooling" | |
bottom: "pool3/3x3_s2" | |
top: "inception_4a/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4a/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4a/pool" | |
top: "inception_4a/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4a/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4a/pool_proj" | |
top: "inception_4a/pool_proj" | |
} | |
layer { | |
name: "inception_4a/output" | |
type: "Concat" | |
bottom: "inception_4a/1x1" | |
bottom: "inception_4a/3x3" | |
bottom: "inception_4a/5x5" | |
bottom: "inception_4a/pool_proj" | |
top: "inception_4a/output" | |
} | |
layer { | |
name: "loss1/ave_pool" | |
type: "Pooling" | |
bottom: "inception_4a/output" | |
top: "loss1/ave_pool" | |
pooling_param { | |
pool: AVE | |
kernel_size: 5 | |
stride: 3 | |
} | |
} | |
layer { | |
name: "loss1/conv" | |
type: "Convolution" | |
bottom: "loss1/ave_pool" | |
top: "loss1/conv" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "loss1/relu_conv" | |
type: "ReLU" | |
bottom: "loss1/conv" | |
top: "loss1/conv" | |
} | |
layer { | |
name: "loss1/fc" | |
type: "InnerProduct" | |
bottom: "loss1/conv" | |
top: "loss1/fc" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 1024 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "loss1/relu_fc" | |
type: "ReLU" | |
bottom: "loss1/fc" | |
top: "loss1/fc" | |
} | |
layer { | |
name: "loss1/drop_fc" | |
type: "Dropout" | |
bottom: "loss1/fc" | |
top: "loss1/fc" | |
dropout_param { | |
dropout_ratio: 0.7 | |
} | |
} | |
layer { | |
name: "loss1/classifier" | |
type: "InnerProduct" | |
bottom: "loss1/fc" | |
top: "loss1/classifier" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 1000 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "loss1/loss" | |
type: "SoftmaxWithLoss" | |
bottom: "loss1/classifier" | |
bottom: "label" | |
top: "loss1/loss1" | |
loss_weight: 0.3 | |
} | |
layer { | |
name: "loss1/top-1" | |
type: "Accuracy" | |
bottom: "loss1/classifier" | |
bottom: "label" | |
top: "loss1/top-1" | |
include { | |
phase: TEST | |
} | |
} | |
layer { | |
name: "loss1/top-5" | |
type: "Accuracy" | |
bottom: "loss1/classifier" | |
bottom: "label" | |
top: "loss1/top-5" | |
include { | |
phase: TEST | |
} | |
accuracy_param { | |
top_k: 5 | |
} | |
} | |
layer { | |
name: "inception_4b/1x1" | |
type: "Convolution" | |
bottom: "inception_4a/output" | |
top: "inception_4b/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 160 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4b/1x1" | |
top: "inception_4b/1x1" | |
} | |
layer { | |
name: "inception_4b/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4a/output" | |
top: "inception_4b/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 112 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4b/3x3_reduce" | |
top: "inception_4b/3x3_reduce" | |
} | |
layer { | |
name: "inception_4b/3x3" | |
type: "Convolution" | |
bottom: "inception_4b/3x3_reduce" | |
top: "inception_4b/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 224 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4b/3x3" | |
top: "inception_4b/3x3" | |
} | |
layer { | |
name: "inception_4b/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4a/output" | |
top: "inception_4b/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4b/5x5_reduce" | |
top: "inception_4b/5x5_reduce" | |
} | |
layer { | |
name: "inception_4b/5x5" | |
type: "Convolution" | |
bottom: "inception_4b/5x5_reduce" | |
top: "inception_4b/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4b/5x5" | |
top: "inception_4b/5x5" | |
} | |
layer { | |
name: "inception_4b/pool" | |
type: "Pooling" | |
bottom: "inception_4a/output" | |
top: "inception_4b/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4b/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4b/pool" | |
top: "inception_4b/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4b/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4b/pool_proj" | |
top: "inception_4b/pool_proj" | |
} | |
layer { | |
name: "inception_4b/output" | |
type: "Concat" | |
bottom: "inception_4b/1x1" | |
bottom: "inception_4b/3x3" | |
bottom: "inception_4b/5x5" | |
bottom: "inception_4b/pool_proj" | |
top: "inception_4b/output" | |
} | |
layer { | |
name: "inception_4c/1x1" | |
type: "Convolution" | |
bottom: "inception_4b/output" | |
top: "inception_4c/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4c/1x1" | |
top: "inception_4c/1x1" | |
} | |
layer { | |
name: "inception_4c/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4b/output" | |
top: "inception_4c/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4c/3x3_reduce" | |
top: "inception_4c/3x3_reduce" | |
} | |
layer { | |
name: "inception_4c/3x3" | |
type: "Convolution" | |
bottom: "inception_4c/3x3_reduce" | |
top: "inception_4c/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4c/3x3" | |
top: "inception_4c/3x3" | |
} | |
layer { | |
name: "inception_4c/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4b/output" | |
top: "inception_4c/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4c/5x5_reduce" | |
top: "inception_4c/5x5_reduce" | |
} | |
layer { | |
name: "inception_4c/5x5" | |
type: "Convolution" | |
bottom: "inception_4c/5x5_reduce" | |
top: "inception_4c/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4c/5x5" | |
top: "inception_4c/5x5" | |
} | |
layer { | |
name: "inception_4c/pool" | |
type: "Pooling" | |
bottom: "inception_4b/output" | |
top: "inception_4c/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4c/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4c/pool" | |
top: "inception_4c/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4c/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4c/pool_proj" | |
top: "inception_4c/pool_proj" | |
} | |
layer { | |
name: "inception_4c/output" | |
type: "Concat" | |
bottom: "inception_4c/1x1" | |
bottom: "inception_4c/3x3" | |
bottom: "inception_4c/5x5" | |
bottom: "inception_4c/pool_proj" | |
top: "inception_4c/output" | |
} | |
layer { | |
name: "inception_4d/1x1" | |
type: "Convolution" | |
bottom: "inception_4c/output" | |
top: "inception_4d/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 112 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4d/1x1" | |
top: "inception_4d/1x1" | |
} | |
layer { | |
name: "inception_4d/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4c/output" | |
top: "inception_4d/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 144 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4d/3x3_reduce" | |
top: "inception_4d/3x3_reduce" | |
} | |
layer { | |
name: "inception_4d/3x3" | |
type: "Convolution" | |
bottom: "inception_4d/3x3_reduce" | |
top: "inception_4d/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 288 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4d/3x3" | |
top: "inception_4d/3x3" | |
} | |
layer { | |
name: "inception_4d/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4c/output" | |
top: "inception_4d/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4d/5x5_reduce" | |
top: "inception_4d/5x5_reduce" | |
} | |
layer { | |
name: "inception_4d/5x5" | |
type: "Convolution" | |
bottom: "inception_4d/5x5_reduce" | |
top: "inception_4d/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4d/5x5" | |
top: "inception_4d/5x5" | |
} | |
layer { | |
name: "inception_4d/pool" | |
type: "Pooling" | |
bottom: "inception_4c/output" | |
top: "inception_4d/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4d/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4d/pool" | |
top: "inception_4d/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4d/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4d/pool_proj" | |
top: "inception_4d/pool_proj" | |
} | |
layer { | |
name: "inception_4d/output" | |
type: "Concat" | |
bottom: "inception_4d/1x1" | |
bottom: "inception_4d/3x3" | |
bottom: "inception_4d/5x5" | |
bottom: "inception_4d/pool_proj" | |
top: "inception_4d/output" | |
} | |
layer { | |
name: "loss2/ave_pool" | |
type: "Pooling" | |
bottom: "inception_4d/output" | |
top: "loss2/ave_pool" | |
pooling_param { | |
pool: AVE | |
kernel_size: 5 | |
stride: 3 | |
} | |
} | |
layer { | |
name: "loss2/conv" | |
type: "Convolution" | |
bottom: "loss2/ave_pool" | |
top: "loss2/conv" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "loss2/relu_conv" | |
type: "ReLU" | |
bottom: "loss2/conv" | |
top: "loss2/conv" | |
} | |
layer { | |
name: "loss2/fc" | |
type: "InnerProduct" | |
bottom: "loss2/conv" | |
top: "loss2/fc" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 1024 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "loss2/relu_fc" | |
type: "ReLU" | |
bottom: "loss2/fc" | |
top: "loss2/fc" | |
} | |
layer { | |
name: "loss2/drop_fc" | |
type: "Dropout" | |
bottom: "loss2/fc" | |
top: "loss2/fc" | |
dropout_param { | |
dropout_ratio: 0.7 | |
} | |
} | |
layer { | |
name: "loss2/classifier" | |
type: "InnerProduct" | |
bottom: "loss2/fc" | |
top: "loss2/classifier" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 1000 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "loss2/loss" | |
type: "SoftmaxWithLoss" | |
bottom: "loss2/classifier" | |
bottom: "label" | |
top: "loss2/loss1" | |
loss_weight: 0.3 | |
} | |
layer { | |
name: "loss2/top-1" | |
type: "Accuracy" | |
bottom: "loss2/classifier" | |
bottom: "label" | |
top: "loss2/top-1" | |
include { | |
phase: TEST | |
} | |
} | |
layer { | |
name: "loss2/top-5" | |
type: "Accuracy" | |
bottom: "loss2/classifier" | |
bottom: "label" | |
top: "loss2/top-5" | |
include { | |
phase: TEST | |
} | |
accuracy_param { | |
top_k: 5 | |
} | |
} | |
layer { | |
name: "inception_4e/1x1" | |
type: "Convolution" | |
bottom: "inception_4d/output" | |
top: "inception_4e/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_4e/1x1" | |
top: "inception_4e/1x1" | |
} | |
layer { | |
name: "inception_4e/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_4d/output" | |
top: "inception_4e/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 160 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_4e/3x3_reduce" | |
top: "inception_4e/3x3_reduce" | |
} | |
layer { | |
name: "inception_4e/3x3" | |
type: "Convolution" | |
bottom: "inception_4e/3x3_reduce" | |
top: "inception_4e/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 320 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_4e/3x3" | |
top: "inception_4e/3x3" | |
} | |
layer { | |
name: "inception_4e/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_4d/output" | |
top: "inception_4e/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_4e/5x5_reduce" | |
top: "inception_4e/5x5_reduce" | |
} | |
layer { | |
name: "inception_4e/5x5" | |
type: "Convolution" | |
bottom: "inception_4e/5x5_reduce" | |
top: "inception_4e/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_4e/5x5" | |
top: "inception_4e/5x5" | |
} | |
layer { | |
name: "inception_4e/pool" | |
type: "Pooling" | |
bottom: "inception_4d/output" | |
top: "inception_4e/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_4e/pool_proj" | |
type: "Convolution" | |
bottom: "inception_4e/pool" | |
top: "inception_4e/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_4e/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_4e/pool_proj" | |
top: "inception_4e/pool_proj" | |
} | |
layer { | |
name: "inception_4e/output" | |
type: "Concat" | |
bottom: "inception_4e/1x1" | |
bottom: "inception_4e/3x3" | |
bottom: "inception_4e/5x5" | |
bottom: "inception_4e/pool_proj" | |
top: "inception_4e/output" | |
} | |
layer { | |
name: "pool4/3x3_s2" | |
type: "Pooling" | |
bottom: "inception_4e/output" | |
top: "pool4/3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "inception_5a/1x1" | |
type: "Convolution" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_5a/1x1" | |
top: "inception_5a/1x1" | |
} | |
layer { | |
name: "inception_5a/3x3_reduce" | |
type: "Convolution" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 160 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_5a/3x3_reduce" | |
top: "inception_5a/3x3_reduce" | |
} | |
layer { | |
name: "inception_5a/3x3" | |
type: "Convolution" | |
bottom: "inception_5a/3x3_reduce" | |
top: "inception_5a/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 320 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_5a/3x3" | |
top: "inception_5a/3x3" | |
} | |
layer { | |
name: "inception_5a/5x5_reduce" | |
type: "Convolution" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_5a/5x5_reduce" | |
top: "inception_5a/5x5_reduce" | |
} | |
layer { | |
name: "inception_5a/5x5" | |
type: "Convolution" | |
bottom: "inception_5a/5x5_reduce" | |
top: "inception_5a/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_5a/5x5" | |
top: "inception_5a/5x5" | |
} | |
layer { | |
name: "inception_5a/pool" | |
type: "Pooling" | |
bottom: "pool4/3x3_s2" | |
top: "inception_5a/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_5a/pool_proj" | |
type: "Convolution" | |
bottom: "inception_5a/pool" | |
top: "inception_5a/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5a/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_5a/pool_proj" | |
top: "inception_5a/pool_proj" | |
} | |
layer { | |
name: "inception_5a/output" | |
type: "Concat" | |
bottom: "inception_5a/1x1" | |
bottom: "inception_5a/3x3" | |
bottom: "inception_5a/5x5" | |
bottom: "inception_5a/pool_proj" | |
top: "inception_5a/output" | |
} | |
layer { | |
name: "inception_5b/1x1" | |
type: "Convolution" | |
bottom: "inception_5a/output" | |
top: "inception_5b/1x1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 384 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_1x1" | |
type: "ReLU" | |
bottom: "inception_5b/1x1" | |
top: "inception_5b/1x1" | |
} | |
layer { | |
name: "inception_5b/3x3_reduce" | |
type: "Convolution" | |
bottom: "inception_5a/output" | |
top: "inception_5b/3x3_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 192 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_3x3_reduce" | |
type: "ReLU" | |
bottom: "inception_5b/3x3_reduce" | |
top: "inception_5b/3x3_reduce" | |
} | |
layer { | |
name: "inception_5b/3x3" | |
type: "Convolution" | |
bottom: "inception_5b/3x3_reduce" | |
top: "inception_5b/3x3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 384 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_3x3" | |
type: "ReLU" | |
bottom: "inception_5b/3x3" | |
top: "inception_5b/3x3" | |
} | |
layer { | |
name: "inception_5b/5x5_reduce" | |
type: "Convolution" | |
bottom: "inception_5a/output" | |
top: "inception_5b/5x5_reduce" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 48 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_5x5_reduce" | |
type: "ReLU" | |
bottom: "inception_5b/5x5_reduce" | |
top: "inception_5b/5x5_reduce" | |
} | |
layer { | |
name: "inception_5b/5x5" | |
type: "Convolution" | |
bottom: "inception_5b/5x5_reduce" | |
top: "inception_5b/5x5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 2 | |
kernel_size: 5 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_5x5" | |
type: "ReLU" | |
bottom: "inception_5b/5x5" | |
top: "inception_5b/5x5" | |
} | |
layer { | |
name: "inception_5b/pool" | |
type: "Pooling" | |
bottom: "inception_5a/output" | |
top: "inception_5b/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
} | |
} | |
layer { | |
name: "inception_5b/pool_proj" | |
type: "Convolution" | |
bottom: "inception_5b/pool" | |
top: "inception_5b/pool_proj" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0.2 | |
} | |
} | |
} | |
layer { | |
name: "inception_5b/relu_pool_proj" | |
type: "ReLU" | |
bottom: "inception_5b/pool_proj" | |
top: "inception_5b/pool_proj" | |
} | |
layer { | |
name: "inception_5b/output" | |
type: "Concat" | |
bottom: "inception_5b/1x1" | |
bottom: "inception_5b/3x3" | |
bottom: "inception_5b/5x5" | |
bottom: "inception_5b/pool_proj" | |
top: "inception_5b/output" | |
} | |
layer { | |
name: "pool5/7x7_s1" | |
type: "Pooling" | |
bottom: "inception_5b/output" | |
top: "pool5/7x7_s1" | |
pooling_param { | |
pool: AVE | |
kernel_size: 7 | |
stride: 1 | |
} | |
} | |
layer { | |
name: "pool5/drop_7x7_s1" | |
type: "Dropout" | |
bottom: "pool5/7x7_s1" | |
top: "pool5/7x7_s1" | |
dropout_param { | |
dropout_ratio: 0.4 | |
} | |
} | |
layer { | |
name: "fc_out" | |
type: "InnerProduct" | |
bottom: "pool5/7x7_s1" | |
top: "fc_out" | |
param { | |
lr_mult: 10 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 20 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "loss3/loss3" | |
type: "SoftmaxWithLoss" | |
bottom: "fc_out" | |
bottom: "label" | |
top: "loss3/loss3" | |
} | |
layer { | |
name: "loss3/top-1" | |
type: "Accuracy" | |
bottom: "fc_out" | |
bottom: "label" | |
top: "loss3/top-1" | |
include { | |
phase: TEST | |
} | |
} | |
The test_iter
in solver.prototxt and batch_size
in data layer TEST
phrase of train_val.prototxt are important for training.
test_iter * batch_size
should equal to the sum number of your test image set.
The pretrained caffe model can be downloaded by run the following command in your caffe root folder.
sudo ./scripts/download_model_binary.py models/bvlc_googlenet
Fine-tuning the googlenet caffe model on your own images by run the following command in your caffe root folder.
sudo ./build/tools/caffe train -solver /path/to/your/solver.prototxt -weights /path/to/bvlc_googlenet.caffemodel
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I changed the last three layers in deploy.prototxt and train_val.prototxt on
fc_out
andnum_output
.