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name: "PeleeNet" | |
layer { | |
name: "data" | |
type: "AnnotatedData" | |
top: "data" | |
top: "label" | |
include { | |
phase: TRAIN | |
} | |
transform_param { | |
scale: 0.007843 | |
mirror: true | |
mean_value: 127.5 | |
mean_value: 127.5 | |
mean_value: 127.5 | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 608 | |
width: 608 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 416 | |
width: 416 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 320 | |
width: 320 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 352 | |
width: 352 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 384 | |
width: 384 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 448 | |
width: 448 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 480 | |
width: 480 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 512 | |
width: 512 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 544 | |
width: 544 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
resize_param { | |
prob: 0.1 | |
resize_mode: WARP | |
height: 576 | |
width: 576 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: LANCZOS4 | |
} | |
emit_constraint { | |
emit_type: CENTER | |
} | |
distort_param { | |
brightness_prob: 0.5 | |
brightness_delta: 32.0 | |
contrast_prob: 0.5 | |
contrast_lower: 0.5 | |
contrast_upper: 1.5 | |
hue_prob: 0.5 | |
hue_delta: 18.0 | |
saturation_prob: 0.5 | |
saturation_lower: 0.5 | |
saturation_upper: 1.5 | |
random_order_prob: 0.0 | |
} | |
expand_param { | |
prob: 0.5 | |
max_expand_ratio: 2.0 | |
} | |
} | |
data_param { | |
source: "examples/VOC0712/VOC0712_trainval_lmdb" | |
batch_size: 4 | |
backend: LMDB | |
} | |
annotated_data_param { | |
yolo_data_type : 1 | |
yolo_data_jitter : 0.3 | |
label_map_file: "data/VOC0712/labelmap_voc.prototxt" | |
} | |
} | |
layer { | |
name: "stem1" | |
type: "Convolution" | |
bottom: "data" | |
top: "stem1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stem1/bn" | |
type: "BatchNorm" | |
bottom: "stem1" | |
top: "stem1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stem1/scale" | |
type: "Scale" | |
bottom: "stem1" | |
top: "stem1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stem1/relu" | |
type: "ReLU" | |
bottom: "stem1" | |
top: "stem1" | |
} | |
layer { | |
name: "stem2a" | |
type: "Convolution" | |
bottom: "stem1" | |
top: "stem2a" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stem2a/bn" | |
type: "BatchNorm" | |
bottom: "stem2a" | |
top: "stem2a" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stem2a/scale" | |
type: "Scale" | |
bottom: "stem2a" | |
top: "stem2a" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stem2a/relu" | |
type: "ReLU" | |
bottom: "stem2a" | |
top: "stem2a" | |
} | |
layer { | |
name: "stem2b" | |
type: "Convolution" | |
bottom: "stem2a" | |
top: "stem2b" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stem2b/bn" | |
type: "BatchNorm" | |
bottom: "stem2b" | |
top: "stem2b" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stem2b/scale" | |
type: "Scale" | |
bottom: "stem2b" | |
top: "stem2b" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stem2b/relu" | |
type: "ReLU" | |
bottom: "stem2b" | |
top: "stem2b" | |
} | |
layer { | |
name: "stem1/pool" | |
type: "Pooling" | |
bottom: "stem1" | |
top: "stem1/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "stem/concat" | |
type: "Concat" | |
bottom: "stem2b" | |
bottom: "stem1/pool" | |
top: "stem/concat" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stem" | |
type: "Convolution" | |
bottom: "stem/concat" | |
top: "stem" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stem/bn" | |
type: "BatchNorm" | |
bottom: "stem" | |
top: "stem" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stem/scale" | |
type: "Scale" | |
bottom: "stem" | |
top: "stem" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stem/relu" | |
type: "ReLU" | |
bottom: "stem" | |
top: "stem" | |
} | |
layer { | |
name: "stage1_1/a1" | |
type: "Convolution" | |
bottom: "stem" | |
top: "stage1_1/a1" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage1_1/a1" | |
top: "stage1_1/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_1/a1/scale" | |
type: "Scale" | |
bottom: "stage1_1/a1" | |
top: "stage1_1/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/a1/relu" | |
type: "ReLU" | |
bottom: "stage1_1/a1" | |
top: "stage1_1/a1" | |
} | |
layer { | |
name: "stage1_1/a2" | |
type: "Convolution" | |
bottom: "stage1_1/a1" | |
top: "stage1_1/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage1_1/a2" | |
top: "stage1_1/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_1/a2/scale" | |
type: "Scale" | |
bottom: "stage1_1/a2" | |
top: "stage1_1/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/a2/relu" | |
type: "ReLU" | |
bottom: "stage1_1/a2" | |
top: "stage1_1/a2" | |
} | |
layer { | |
name: "stage1_1/b1" | |
type: "Convolution" | |
bottom: "stem" | |
top: "stage1_1/b1" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage1_1/b1" | |
top: "stage1_1/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_1/b1/scale" | |
type: "Scale" | |
bottom: "stage1_1/b1" | |
top: "stage1_1/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/b1/relu" | |
type: "ReLU" | |
bottom: "stage1_1/b1" | |
top: "stage1_1/b1" | |
} | |
layer { | |
name: "stage1_1/b2" | |
type: "Convolution" | |
bottom: "stage1_1/b1" | |
top: "stage1_1/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage1_1/b2" | |
top: "stage1_1/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_1/b2/scale" | |
type: "Scale" | |
bottom: "stage1_1/b2" | |
top: "stage1_1/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/b2/relu" | |
type: "ReLU" | |
bottom: "stage1_1/b2" | |
top: "stage1_1/b2" | |
} | |
layer { | |
name: "stage1_1/b3" | |
type: "Convolution" | |
bottom: "stage1_1/b2" | |
top: "stage1_1/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage1_1/b3" | |
top: "stage1_1/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_1/b3/scale" | |
type: "Scale" | |
bottom: "stage1_1/b3" | |
top: "stage1_1/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_1/b3/relu" | |
type: "ReLU" | |
bottom: "stage1_1/b3" | |
top: "stage1_1/b3" | |
} | |
layer { | |
name: "stage1_1" | |
type: "Concat" | |
bottom: "stem" | |
bottom: "stage1_1/a2" | |
bottom: "stage1_1/b3" | |
top: "stage1_1" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage1_2/a1" | |
type: "Convolution" | |
bottom: "stage1_1" | |
top: "stage1_2/a1" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage1_2/a1" | |
top: "stage1_2/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_2/a1/scale" | |
type: "Scale" | |
bottom: "stage1_2/a1" | |
top: "stage1_2/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/a1/relu" | |
type: "ReLU" | |
bottom: "stage1_2/a1" | |
top: "stage1_2/a1" | |
} | |
layer { | |
name: "stage1_2/a2" | |
type: "Convolution" | |
bottom: "stage1_2/a1" | |
top: "stage1_2/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage1_2/a2" | |
top: "stage1_2/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_2/a2/scale" | |
type: "Scale" | |
bottom: "stage1_2/a2" | |
top: "stage1_2/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/a2/relu" | |
type: "ReLU" | |
bottom: "stage1_2/a2" | |
top: "stage1_2/a2" | |
} | |
layer { | |
name: "stage1_2/b1" | |
type: "Convolution" | |
bottom: "stage1_1" | |
top: "stage1_2/b1" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage1_2/b1" | |
top: "stage1_2/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_2/b1/scale" | |
type: "Scale" | |
bottom: "stage1_2/b1" | |
top: "stage1_2/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/b1/relu" | |
type: "ReLU" | |
bottom: "stage1_2/b1" | |
top: "stage1_2/b1" | |
} | |
layer { | |
name: "stage1_2/b2" | |
type: "Convolution" | |
bottom: "stage1_2/b1" | |
top: "stage1_2/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage1_2/b2" | |
top: "stage1_2/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_2/b2/scale" | |
type: "Scale" | |
bottom: "stage1_2/b2" | |
top: "stage1_2/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/b2/relu" | |
type: "ReLU" | |
bottom: "stage1_2/b2" | |
top: "stage1_2/b2" | |
} | |
layer { | |
name: "stage1_2/b3" | |
type: "Convolution" | |
bottom: "stage1_2/b2" | |
top: "stage1_2/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage1_2/b3" | |
top: "stage1_2/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_2/b3/scale" | |
type: "Scale" | |
bottom: "stage1_2/b3" | |
top: "stage1_2/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_2/b3/relu" | |
type: "ReLU" | |
bottom: "stage1_2/b3" | |
top: "stage1_2/b3" | |
} | |
layer { | |
name: "stage1_2" | |
type: "Concat" | |
bottom: "stage1_1" | |
bottom: "stage1_2/a2" | |
bottom: "stage1_2/b3" | |
top: "stage1_2" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage1_3/a1" | |
type: "Convolution" | |
bottom: "stage1_2" | |
top: "stage1_3/a1" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage1_3/a1" | |
top: "stage1_3/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_3/a1/scale" | |
type: "Scale" | |
bottom: "stage1_3/a1" | |
top: "stage1_3/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/a1/relu" | |
type: "ReLU" | |
bottom: "stage1_3/a1" | |
top: "stage1_3/a1" | |
} | |
layer { | |
name: "stage1_3/a2" | |
type: "Convolution" | |
bottom: "stage1_3/a1" | |
top: "stage1_3/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage1_3/a2" | |
top: "stage1_3/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_3/a2/scale" | |
type: "Scale" | |
bottom: "stage1_3/a2" | |
top: "stage1_3/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/a2/relu" | |
type: "ReLU" | |
bottom: "stage1_3/a2" | |
top: "stage1_3/a2" | |
} | |
layer { | |
name: "stage1_3/b1" | |
type: "Convolution" | |
bottom: "stage1_2" | |
top: "stage1_3/b1" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage1_3/b1" | |
top: "stage1_3/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_3/b1/scale" | |
type: "Scale" | |
bottom: "stage1_3/b1" | |
top: "stage1_3/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/b1/relu" | |
type: "ReLU" | |
bottom: "stage1_3/b1" | |
top: "stage1_3/b1" | |
} | |
layer { | |
name: "stage1_3/b2" | |
type: "Convolution" | |
bottom: "stage1_3/b1" | |
top: "stage1_3/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage1_3/b2" | |
top: "stage1_3/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_3/b2/scale" | |
type: "Scale" | |
bottom: "stage1_3/b2" | |
top: "stage1_3/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/b2/relu" | |
type: "ReLU" | |
bottom: "stage1_3/b2" | |
top: "stage1_3/b2" | |
} | |
layer { | |
name: "stage1_3/b3" | |
type: "Convolution" | |
bottom: "stage1_3/b2" | |
top: "stage1_3/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage1_3/b3" | |
top: "stage1_3/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1_3/b3/scale" | |
type: "Scale" | |
bottom: "stage1_3/b3" | |
top: "stage1_3/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1_3/b3/relu" | |
type: "ReLU" | |
bottom: "stage1_3/b3" | |
top: "stage1_3/b3" | |
} | |
layer { | |
name: "stage1_3" | |
type: "Concat" | |
bottom: "stage1_2" | |
bottom: "stage1_3/a2" | |
bottom: "stage1_3/b3" | |
top: "stage1_3" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage1" | |
type: "Convolution" | |
bottom: "stage1_3" | |
top: "stage1" | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage1/bn" | |
type: "BatchNorm" | |
bottom: "stage1" | |
top: "stage1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage1/scale" | |
type: "Scale" | |
bottom: "stage1" | |
top: "stage1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage1/relu" | |
type: "ReLU" | |
bottom: "stage1" | |
top: "stage1" | |
} | |
layer { | |
name: "stage1/pool" | |
type: "Pooling" | |
bottom: "stage1" | |
top: "stage1/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "stage2_1/a1" | |
type: "Convolution" | |
bottom: "stage1/pool" | |
top: "stage2_1/a1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_1/a1" | |
top: "stage2_1/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_1/a1/scale" | |
type: "Scale" | |
bottom: "stage2_1/a1" | |
top: "stage2_1/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/a1/relu" | |
type: "ReLU" | |
bottom: "stage2_1/a1" | |
top: "stage2_1/a1" | |
} | |
layer { | |
name: "stage2_1/a2" | |
type: "Convolution" | |
bottom: "stage2_1/a1" | |
top: "stage2_1/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_1/a2" | |
top: "stage2_1/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_1/a2/scale" | |
type: "Scale" | |
bottom: "stage2_1/a2" | |
top: "stage2_1/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/a2/relu" | |
type: "ReLU" | |
bottom: "stage2_1/a2" | |
top: "stage2_1/a2" | |
} | |
layer { | |
name: "stage2_1/b1" | |
type: "Convolution" | |
bottom: "stage1/pool" | |
top: "stage2_1/b1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_1/b1" | |
top: "stage2_1/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_1/b1/scale" | |
type: "Scale" | |
bottom: "stage2_1/b1" | |
top: "stage2_1/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/b1/relu" | |
type: "ReLU" | |
bottom: "stage2_1/b1" | |
top: "stage2_1/b1" | |
} | |
layer { | |
name: "stage2_1/b2" | |
type: "Convolution" | |
bottom: "stage2_1/b1" | |
top: "stage2_1/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_1/b2" | |
top: "stage2_1/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_1/b2/scale" | |
type: "Scale" | |
bottom: "stage2_1/b2" | |
top: "stage2_1/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/b2/relu" | |
type: "ReLU" | |
bottom: "stage2_1/b2" | |
top: "stage2_1/b2" | |
} | |
layer { | |
name: "stage2_1/b3" | |
type: "Convolution" | |
bottom: "stage2_1/b2" | |
top: "stage2_1/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage2_1/b3" | |
top: "stage2_1/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_1/b3/scale" | |
type: "Scale" | |
bottom: "stage2_1/b3" | |
top: "stage2_1/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_1/b3/relu" | |
type: "ReLU" | |
bottom: "stage2_1/b3" | |
top: "stage2_1/b3" | |
} | |
layer { | |
name: "stage2_1" | |
type: "Concat" | |
bottom: "stage1/pool" | |
bottom: "stage2_1/a2" | |
bottom: "stage2_1/b3" | |
top: "stage2_1" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage2_2/a1" | |
type: "Convolution" | |
bottom: "stage2_1" | |
top: "stage2_2/a1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_2/a1" | |
top: "stage2_2/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_2/a1/scale" | |
type: "Scale" | |
bottom: "stage2_2/a1" | |
top: "stage2_2/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/a1/relu" | |
type: "ReLU" | |
bottom: "stage2_2/a1" | |
top: "stage2_2/a1" | |
} | |
layer { | |
name: "stage2_2/a2" | |
type: "Convolution" | |
bottom: "stage2_2/a1" | |
top: "stage2_2/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_2/a2" | |
top: "stage2_2/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_2/a2/scale" | |
type: "Scale" | |
bottom: "stage2_2/a2" | |
top: "stage2_2/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/a2/relu" | |
type: "ReLU" | |
bottom: "stage2_2/a2" | |
top: "stage2_2/a2" | |
} | |
layer { | |
name: "stage2_2/b1" | |
type: "Convolution" | |
bottom: "stage2_1" | |
top: "stage2_2/b1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_2/b1" | |
top: "stage2_2/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_2/b1/scale" | |
type: "Scale" | |
bottom: "stage2_2/b1" | |
top: "stage2_2/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/b1/relu" | |
type: "ReLU" | |
bottom: "stage2_2/b1" | |
top: "stage2_2/b1" | |
} | |
layer { | |
name: "stage2_2/b2" | |
type: "Convolution" | |
bottom: "stage2_2/b1" | |
top: "stage2_2/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_2/b2" | |
top: "stage2_2/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_2/b2/scale" | |
type: "Scale" | |
bottom: "stage2_2/b2" | |
top: "stage2_2/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/b2/relu" | |
type: "ReLU" | |
bottom: "stage2_2/b2" | |
top: "stage2_2/b2" | |
} | |
layer { | |
name: "stage2_2/b3" | |
type: "Convolution" | |
bottom: "stage2_2/b2" | |
top: "stage2_2/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage2_2/b3" | |
top: "stage2_2/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_2/b3/scale" | |
type: "Scale" | |
bottom: "stage2_2/b3" | |
top: "stage2_2/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_2/b3/relu" | |
type: "ReLU" | |
bottom: "stage2_2/b3" | |
top: "stage2_2/b3" | |
} | |
layer { | |
name: "stage2_2" | |
type: "Concat" | |
bottom: "stage2_1" | |
bottom: "stage2_2/a2" | |
bottom: "stage2_2/b3" | |
top: "stage2_2" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage2_3/a1" | |
type: "Convolution" | |
bottom: "stage2_2" | |
top: "stage2_3/a1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_3/a1" | |
top: "stage2_3/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_3/a1/scale" | |
type: "Scale" | |
bottom: "stage2_3/a1" | |
top: "stage2_3/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/a1/relu" | |
type: "ReLU" | |
bottom: "stage2_3/a1" | |
top: "stage2_3/a1" | |
} | |
layer { | |
name: "stage2_3/a2" | |
type: "Convolution" | |
bottom: "stage2_3/a1" | |
top: "stage2_3/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_3/a2" | |
top: "stage2_3/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_3/a2/scale" | |
type: "Scale" | |
bottom: "stage2_3/a2" | |
top: "stage2_3/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/a2/relu" | |
type: "ReLU" | |
bottom: "stage2_3/a2" | |
top: "stage2_3/a2" | |
} | |
layer { | |
name: "stage2_3/b1" | |
type: "Convolution" | |
bottom: "stage2_2" | |
top: "stage2_3/b1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_3/b1" | |
top: "stage2_3/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_3/b1/scale" | |
type: "Scale" | |
bottom: "stage2_3/b1" | |
top: "stage2_3/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/b1/relu" | |
type: "ReLU" | |
bottom: "stage2_3/b1" | |
top: "stage2_3/b1" | |
} | |
layer { | |
name: "stage2_3/b2" | |
type: "Convolution" | |
bottom: "stage2_3/b1" | |
top: "stage2_3/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_3/b2" | |
top: "stage2_3/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_3/b2/scale" | |
type: "Scale" | |
bottom: "stage2_3/b2" | |
top: "stage2_3/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/b2/relu" | |
type: "ReLU" | |
bottom: "stage2_3/b2" | |
top: "stage2_3/b2" | |
} | |
layer { | |
name: "stage2_3/b3" | |
type: "Convolution" | |
bottom: "stage2_3/b2" | |
top: "stage2_3/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage2_3/b3" | |
top: "stage2_3/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_3/b3/scale" | |
type: "Scale" | |
bottom: "stage2_3/b3" | |
top: "stage2_3/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_3/b3/relu" | |
type: "ReLU" | |
bottom: "stage2_3/b3" | |
top: "stage2_3/b3" | |
} | |
layer { | |
name: "stage2_3" | |
type: "Concat" | |
bottom: "stage2_2" | |
bottom: "stage2_3/a2" | |
bottom: "stage2_3/b3" | |
top: "stage2_3" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage2_4/a1" | |
type: "Convolution" | |
bottom: "stage2_3" | |
top: "stage2_4/a1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_4/a1" | |
top: "stage2_4/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_4/a1/scale" | |
type: "Scale" | |
bottom: "stage2_4/a1" | |
top: "stage2_4/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/a1/relu" | |
type: "ReLU" | |
bottom: "stage2_4/a1" | |
top: "stage2_4/a1" | |
} | |
layer { | |
name: "stage2_4/a2" | |
type: "Convolution" | |
bottom: "stage2_4/a1" | |
top: "stage2_4/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_4/a2" | |
top: "stage2_4/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_4/a2/scale" | |
type: "Scale" | |
bottom: "stage2_4/a2" | |
top: "stage2_4/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/a2/relu" | |
type: "ReLU" | |
bottom: "stage2_4/a2" | |
top: "stage2_4/a2" | |
} | |
layer { | |
name: "stage2_4/b1" | |
type: "Convolution" | |
bottom: "stage2_3" | |
top: "stage2_4/b1" | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage2_4/b1" | |
top: "stage2_4/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_4/b1/scale" | |
type: "Scale" | |
bottom: "stage2_4/b1" | |
top: "stage2_4/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/b1/relu" | |
type: "ReLU" | |
bottom: "stage2_4/b1" | |
top: "stage2_4/b1" | |
} | |
layer { | |
name: "stage2_4/b2" | |
type: "Convolution" | |
bottom: "stage2_4/b1" | |
top: "stage2_4/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage2_4/b2" | |
top: "stage2_4/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_4/b2/scale" | |
type: "Scale" | |
bottom: "stage2_4/b2" | |
top: "stage2_4/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/b2/relu" | |
type: "ReLU" | |
bottom: "stage2_4/b2" | |
top: "stage2_4/b2" | |
} | |
layer { | |
name: "stage2_4/b3" | |
type: "Convolution" | |
bottom: "stage2_4/b2" | |
top: "stage2_4/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage2_4/b3" | |
top: "stage2_4/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2_4/b3/scale" | |
type: "Scale" | |
bottom: "stage2_4/b3" | |
top: "stage2_4/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2_4/b3/relu" | |
type: "ReLU" | |
bottom: "stage2_4/b3" | |
top: "stage2_4/b3" | |
} | |
layer { | |
name: "stage2_4" | |
type: "Concat" | |
bottom: "stage2_3" | |
bottom: "stage2_4/a2" | |
bottom: "stage2_4/b3" | |
top: "stage2_4" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage2" | |
type: "Convolution" | |
bottom: "stage2_4" | |
top: "stage2" | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage2/bn" | |
type: "BatchNorm" | |
bottom: "stage2" | |
top: "stage2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage2/scale" | |
type: "Scale" | |
bottom: "stage2" | |
top: "stage2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage2/relu" | |
type: "ReLU" | |
bottom: "stage2" | |
top: "stage2" | |
} | |
layer { | |
name: "stage2/pool" | |
type: "Pooling" | |
bottom: "stage2" | |
top: "stage2/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "stage3_1/a1" | |
type: "Convolution" | |
bottom: "stage2/pool" | |
top: "stage3_1/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_1/a1" | |
top: "stage3_1/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_1/a1/scale" | |
type: "Scale" | |
bottom: "stage3_1/a1" | |
top: "stage3_1/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_1/a1" | |
top: "stage3_1/a1" | |
} | |
layer { | |
name: "stage3_1/a2" | |
type: "Convolution" | |
bottom: "stage3_1/a1" | |
top: "stage3_1/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_1/a2" | |
top: "stage3_1/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_1/a2/scale" | |
type: "Scale" | |
bottom: "stage3_1/a2" | |
top: "stage3_1/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_1/a2" | |
top: "stage3_1/a2" | |
} | |
layer { | |
name: "stage3_1/b1" | |
type: "Convolution" | |
bottom: "stage2/pool" | |
top: "stage3_1/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_1/b1" | |
top: "stage3_1/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_1/b1/scale" | |
type: "Scale" | |
bottom: "stage3_1/b1" | |
top: "stage3_1/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_1/b1" | |
top: "stage3_1/b1" | |
} | |
layer { | |
name: "stage3_1/b2" | |
type: "Convolution" | |
bottom: "stage3_1/b1" | |
top: "stage3_1/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_1/b2" | |
top: "stage3_1/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_1/b2/scale" | |
type: "Scale" | |
bottom: "stage3_1/b2" | |
top: "stage3_1/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_1/b2" | |
top: "stage3_1/b2" | |
} | |
layer { | |
name: "stage3_1/b3" | |
type: "Convolution" | |
bottom: "stage3_1/b2" | |
top: "stage3_1/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_1/b3" | |
top: "stage3_1/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_1/b3/scale" | |
type: "Scale" | |
bottom: "stage3_1/b3" | |
top: "stage3_1/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_1/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_1/b3" | |
top: "stage3_1/b3" | |
} | |
layer { | |
name: "stage3_1" | |
type: "Concat" | |
bottom: "stage2/pool" | |
bottom: "stage3_1/a2" | |
bottom: "stage3_1/b3" | |
top: "stage3_1" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3_2/a1" | |
type: "Convolution" | |
bottom: "stage3_1" | |
top: "stage3_2/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_2/a1" | |
top: "stage3_2/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_2/a1/scale" | |
type: "Scale" | |
bottom: "stage3_2/a1" | |
top: "stage3_2/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_2/a1" | |
top: "stage3_2/a1" | |
} | |
layer { | |
name: "stage3_2/a2" | |
type: "Convolution" | |
bottom: "stage3_2/a1" | |
top: "stage3_2/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_2/a2" | |
top: "stage3_2/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_2/a2/scale" | |
type: "Scale" | |
bottom: "stage3_2/a2" | |
top: "stage3_2/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_2/a2" | |
top: "stage3_2/a2" | |
} | |
layer { | |
name: "stage3_2/b1" | |
type: "Convolution" | |
bottom: "stage3_1" | |
top: "stage3_2/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_2/b1" | |
top: "stage3_2/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_2/b1/scale" | |
type: "Scale" | |
bottom: "stage3_2/b1" | |
top: "stage3_2/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_2/b1" | |
top: "stage3_2/b1" | |
} | |
layer { | |
name: "stage3_2/b2" | |
type: "Convolution" | |
bottom: "stage3_2/b1" | |
top: "stage3_2/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_2/b2" | |
top: "stage3_2/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_2/b2/scale" | |
type: "Scale" | |
bottom: "stage3_2/b2" | |
top: "stage3_2/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_2/b2" | |
top: "stage3_2/b2" | |
} | |
layer { | |
name: "stage3_2/b3" | |
type: "Convolution" | |
bottom: "stage3_2/b2" | |
top: "stage3_2/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_2/b3" | |
top: "stage3_2/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_2/b3/scale" | |
type: "Scale" | |
bottom: "stage3_2/b3" | |
top: "stage3_2/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_2/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_2/b3" | |
top: "stage3_2/b3" | |
} | |
layer { | |
name: "stage3_2" | |
type: "Concat" | |
bottom: "stage3_1" | |
bottom: "stage3_2/a2" | |
bottom: "stage3_2/b3" | |
top: "stage3_2" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3_3/a1" | |
type: "Convolution" | |
bottom: "stage3_2" | |
top: "stage3_3/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_3/a1" | |
top: "stage3_3/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_3/a1/scale" | |
type: "Scale" | |
bottom: "stage3_3/a1" | |
top: "stage3_3/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_3/a1" | |
top: "stage3_3/a1" | |
} | |
layer { | |
name: "stage3_3/a2" | |
type: "Convolution" | |
bottom: "stage3_3/a1" | |
top: "stage3_3/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_3/a2" | |
top: "stage3_3/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_3/a2/scale" | |
type: "Scale" | |
bottom: "stage3_3/a2" | |
top: "stage3_3/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_3/a2" | |
top: "stage3_3/a2" | |
} | |
layer { | |
name: "stage3_3/b1" | |
type: "Convolution" | |
bottom: "stage3_2" | |
top: "stage3_3/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_3/b1" | |
top: "stage3_3/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_3/b1/scale" | |
type: "Scale" | |
bottom: "stage3_3/b1" | |
top: "stage3_3/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_3/b1" | |
top: "stage3_3/b1" | |
} | |
layer { | |
name: "stage3_3/b2" | |
type: "Convolution" | |
bottom: "stage3_3/b1" | |
top: "stage3_3/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_3/b2" | |
top: "stage3_3/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_3/b2/scale" | |
type: "Scale" | |
bottom: "stage3_3/b2" | |
top: "stage3_3/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_3/b2" | |
top: "stage3_3/b2" | |
} | |
layer { | |
name: "stage3_3/b3" | |
type: "Convolution" | |
bottom: "stage3_3/b2" | |
top: "stage3_3/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_3/b3" | |
top: "stage3_3/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_3/b3/scale" | |
type: "Scale" | |
bottom: "stage3_3/b3" | |
top: "stage3_3/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_3/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_3/b3" | |
top: "stage3_3/b3" | |
} | |
layer { | |
name: "stage3_3" | |
type: "Concat" | |
bottom: "stage3_2" | |
bottom: "stage3_3/a2" | |
bottom: "stage3_3/b3" | |
top: "stage3_3" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3_4/a1" | |
type: "Convolution" | |
bottom: "stage3_3" | |
top: "stage3_4/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_4/a1" | |
top: "stage3_4/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_4/a1/scale" | |
type: "Scale" | |
bottom: "stage3_4/a1" | |
top: "stage3_4/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_4/a1" | |
top: "stage3_4/a1" | |
} | |
layer { | |
name: "stage3_4/a2" | |
type: "Convolution" | |
bottom: "stage3_4/a1" | |
top: "stage3_4/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_4/a2" | |
top: "stage3_4/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_4/a2/scale" | |
type: "Scale" | |
bottom: "stage3_4/a2" | |
top: "stage3_4/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_4/a2" | |
top: "stage3_4/a2" | |
} | |
layer { | |
name: "stage3_4/b1" | |
type: "Convolution" | |
bottom: "stage3_3" | |
top: "stage3_4/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_4/b1" | |
top: "stage3_4/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_4/b1/scale" | |
type: "Scale" | |
bottom: "stage3_4/b1" | |
top: "stage3_4/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_4/b1" | |
top: "stage3_4/b1" | |
} | |
layer { | |
name: "stage3_4/b2" | |
type: "Convolution" | |
bottom: "stage3_4/b1" | |
top: "stage3_4/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_4/b2" | |
top: "stage3_4/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_4/b2/scale" | |
type: "Scale" | |
bottom: "stage3_4/b2" | |
top: "stage3_4/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_4/b2" | |
top: "stage3_4/b2" | |
} | |
layer { | |
name: "stage3_4/b3" | |
type: "Convolution" | |
bottom: "stage3_4/b2" | |
top: "stage3_4/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_4/b3" | |
top: "stage3_4/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_4/b3/scale" | |
type: "Scale" | |
bottom: "stage3_4/b3" | |
top: "stage3_4/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_4/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_4/b3" | |
top: "stage3_4/b3" | |
} | |
layer { | |
name: "stage3_4" | |
type: "Concat" | |
bottom: "stage3_3" | |
bottom: "stage3_4/a2" | |
bottom: "stage3_4/b3" | |
top: "stage3_4" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3_5/a1" | |
type: "Convolution" | |
bottom: "stage3_4" | |
top: "stage3_5/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_5/a1" | |
top: "stage3_5/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_5/a1/scale" | |
type: "Scale" | |
bottom: "stage3_5/a1" | |
top: "stage3_5/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_5/a1" | |
top: "stage3_5/a1" | |
} | |
layer { | |
name: "stage3_5/a2" | |
type: "Convolution" | |
bottom: "stage3_5/a1" | |
top: "stage3_5/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_5/a2" | |
top: "stage3_5/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_5/a2/scale" | |
type: "Scale" | |
bottom: "stage3_5/a2" | |
top: "stage3_5/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_5/a2" | |
top: "stage3_5/a2" | |
} | |
layer { | |
name: "stage3_5/b1" | |
type: "Convolution" | |
bottom: "stage3_4" | |
top: "stage3_5/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_5/b1" | |
top: "stage3_5/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_5/b1/scale" | |
type: "Scale" | |
bottom: "stage3_5/b1" | |
top: "stage3_5/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_5/b1" | |
top: "stage3_5/b1" | |
} | |
layer { | |
name: "stage3_5/b2" | |
type: "Convolution" | |
bottom: "stage3_5/b1" | |
top: "stage3_5/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_5/b2" | |
top: "stage3_5/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_5/b2/scale" | |
type: "Scale" | |
bottom: "stage3_5/b2" | |
top: "stage3_5/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_5/b2" | |
top: "stage3_5/b2" | |
} | |
layer { | |
name: "stage3_5/b3" | |
type: "Convolution" | |
bottom: "stage3_5/b2" | |
top: "stage3_5/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_5/b3" | |
top: "stage3_5/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_5/b3/scale" | |
type: "Scale" | |
bottom: "stage3_5/b3" | |
top: "stage3_5/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_5/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_5/b3" | |
top: "stage3_5/b3" | |
} | |
layer { | |
name: "stage3_5" | |
type: "Concat" | |
bottom: "stage3_4" | |
bottom: "stage3_5/a2" | |
bottom: "stage3_5/b3" | |
top: "stage3_5" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3_6/a1" | |
type: "Convolution" | |
bottom: "stage3_5" | |
top: "stage3_6/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_6/a1" | |
top: "stage3_6/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_6/a1/scale" | |
type: "Scale" | |
bottom: "stage3_6/a1" | |
top: "stage3_6/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_6/a1" | |
top: "stage3_6/a1" | |
} | |
layer { | |
name: "stage3_6/a2" | |
type: "Convolution" | |
bottom: "stage3_6/a1" | |
top: "stage3_6/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_6/a2" | |
top: "stage3_6/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_6/a2/scale" | |
type: "Scale" | |
bottom: "stage3_6/a2" | |
top: "stage3_6/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_6/a2" | |
top: "stage3_6/a2" | |
} | |
layer { | |
name: "stage3_6/b1" | |
type: "Convolution" | |
bottom: "stage3_5" | |
top: "stage3_6/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_6/b1" | |
top: "stage3_6/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_6/b1/scale" | |
type: "Scale" | |
bottom: "stage3_6/b1" | |
top: "stage3_6/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_6/b1" | |
top: "stage3_6/b1" | |
} | |
layer { | |
name: "stage3_6/b2" | |
type: "Convolution" | |
bottom: "stage3_6/b1" | |
top: "stage3_6/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_6/b2" | |
top: "stage3_6/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_6/b2/scale" | |
type: "Scale" | |
bottom: "stage3_6/b2" | |
top: "stage3_6/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_6/b2" | |
top: "stage3_6/b2" | |
} | |
layer { | |
name: "stage3_6/b3" | |
type: "Convolution" | |
bottom: "stage3_6/b2" | |
top: "stage3_6/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_6/b3" | |
top: "stage3_6/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_6/b3/scale" | |
type: "Scale" | |
bottom: "stage3_6/b3" | |
top: "stage3_6/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_6/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_6/b3" | |
top: "stage3_6/b3" | |
} | |
layer { | |
name: "stage3_6" | |
type: "Concat" | |
bottom: "stage3_5" | |
bottom: "stage3_6/a2" | |
bottom: "stage3_6/b3" | |
top: "stage3_6" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3_7/a1" | |
type: "Convolution" | |
bottom: "stage3_6" | |
top: "stage3_7/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_7/a1" | |
top: "stage3_7/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_7/a1/scale" | |
type: "Scale" | |
bottom: "stage3_7/a1" | |
top: "stage3_7/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_7/a1" | |
top: "stage3_7/a1" | |
} | |
layer { | |
name: "stage3_7/a2" | |
type: "Convolution" | |
bottom: "stage3_7/a1" | |
top: "stage3_7/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_7/a2" | |
top: "stage3_7/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_7/a2/scale" | |
type: "Scale" | |
bottom: "stage3_7/a2" | |
top: "stage3_7/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_7/a2" | |
top: "stage3_7/a2" | |
} | |
layer { | |
name: "stage3_7/b1" | |
type: "Convolution" | |
bottom: "stage3_6" | |
top: "stage3_7/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_7/b1" | |
top: "stage3_7/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_7/b1/scale" | |
type: "Scale" | |
bottom: "stage3_7/b1" | |
top: "stage3_7/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_7/b1" | |
top: "stage3_7/b1" | |
} | |
layer { | |
name: "stage3_7/b2" | |
type: "Convolution" | |
bottom: "stage3_7/b1" | |
top: "stage3_7/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_7/b2" | |
top: "stage3_7/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_7/b2/scale" | |
type: "Scale" | |
bottom: "stage3_7/b2" | |
top: "stage3_7/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_7/b2" | |
top: "stage3_7/b2" | |
} | |
layer { | |
name: "stage3_7/b3" | |
type: "Convolution" | |
bottom: "stage3_7/b2" | |
top: "stage3_7/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_7/b3" | |
top: "stage3_7/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_7/b3/scale" | |
type: "Scale" | |
bottom: "stage3_7/b3" | |
top: "stage3_7/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_7/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_7/b3" | |
top: "stage3_7/b3" | |
} | |
layer { | |
name: "stage3_7" | |
type: "Concat" | |
bottom: "stage3_6" | |
bottom: "stage3_7/a2" | |
bottom: "stage3_7/b3" | |
top: "stage3_7" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3_8/a1" | |
type: "Convolution" | |
bottom: "stage3_7" | |
top: "stage3_8/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_8/a1" | |
top: "stage3_8/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_8/a1/scale" | |
type: "Scale" | |
bottom: "stage3_8/a1" | |
top: "stage3_8/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/a1/relu" | |
type: "ReLU" | |
bottom: "stage3_8/a1" | |
top: "stage3_8/a1" | |
} | |
layer { | |
name: "stage3_8/a2" | |
type: "Convolution" | |
bottom: "stage3_8/a1" | |
top: "stage3_8/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_8/a2" | |
top: "stage3_8/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_8/a2/scale" | |
type: "Scale" | |
bottom: "stage3_8/a2" | |
top: "stage3_8/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/a2/relu" | |
type: "ReLU" | |
bottom: "stage3_8/a2" | |
top: "stage3_8/a2" | |
} | |
layer { | |
name: "stage3_8/b1" | |
type: "Convolution" | |
bottom: "stage3_7" | |
top: "stage3_8/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage3_8/b1" | |
top: "stage3_8/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_8/b1/scale" | |
type: "Scale" | |
bottom: "stage3_8/b1" | |
top: "stage3_8/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/b1/relu" | |
type: "ReLU" | |
bottom: "stage3_8/b1" | |
top: "stage3_8/b1" | |
} | |
layer { | |
name: "stage3_8/b2" | |
type: "Convolution" | |
bottom: "stage3_8/b1" | |
top: "stage3_8/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage3_8/b2" | |
top: "stage3_8/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_8/b2/scale" | |
type: "Scale" | |
bottom: "stage3_8/b2" | |
top: "stage3_8/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/b2/relu" | |
type: "ReLU" | |
bottom: "stage3_8/b2" | |
top: "stage3_8/b2" | |
} | |
layer { | |
name: "stage3_8/b3" | |
type: "Convolution" | |
bottom: "stage3_8/b2" | |
top: "stage3_8/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage3_8/b3" | |
top: "stage3_8/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3_8/b3/scale" | |
type: "Scale" | |
bottom: "stage3_8/b3" | |
top: "stage3_8/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3_8/b3/relu" | |
type: "ReLU" | |
bottom: "stage3_8/b3" | |
top: "stage3_8/b3" | |
} | |
layer { | |
name: "stage3_8" | |
type: "Concat" | |
bottom: "stage3_7" | |
bottom: "stage3_8/a2" | |
bottom: "stage3_8/b3" | |
top: "stage3_8" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage3" | |
type: "Convolution" | |
bottom: "stage3_8" | |
top: "stage3" | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage3/bn" | |
type: "BatchNorm" | |
bottom: "stage3" | |
top: "stage3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage3/scale" | |
type: "Scale" | |
bottom: "stage3" | |
top: "stage3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage3/relu" | |
type: "ReLU" | |
bottom: "stage3" | |
top: "stage3" | |
} | |
layer { | |
name: "stage3/pool" | |
type: "Pooling" | |
bottom: "stage3" | |
top: "stage3/pool" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "stage4_1/a1" | |
type: "Convolution" | |
bottom: "stage3/pool" | |
top: "stage4_1/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_1/a1" | |
top: "stage4_1/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_1/a1/scale" | |
type: "Scale" | |
bottom: "stage4_1/a1" | |
top: "stage4_1/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/a1/relu" | |
type: "ReLU" | |
bottom: "stage4_1/a1" | |
top: "stage4_1/a1" | |
} | |
layer { | |
name: "stage4_1/a2" | |
type: "Convolution" | |
bottom: "stage4_1/a1" | |
top: "stage4_1/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_1/a2" | |
top: "stage4_1/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_1/a2/scale" | |
type: "Scale" | |
bottom: "stage4_1/a2" | |
top: "stage4_1/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/a2/relu" | |
type: "ReLU" | |
bottom: "stage4_1/a2" | |
top: "stage4_1/a2" | |
} | |
layer { | |
name: "stage4_1/b1" | |
type: "Convolution" | |
bottom: "stage3/pool" | |
top: "stage4_1/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_1/b1" | |
top: "stage4_1/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_1/b1/scale" | |
type: "Scale" | |
bottom: "stage4_1/b1" | |
top: "stage4_1/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/b1/relu" | |
type: "ReLU" | |
bottom: "stage4_1/b1" | |
top: "stage4_1/b1" | |
} | |
layer { | |
name: "stage4_1/b2" | |
type: "Convolution" | |
bottom: "stage4_1/b1" | |
top: "stage4_1/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_1/b2" | |
top: "stage4_1/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_1/b2/scale" | |
type: "Scale" | |
bottom: "stage4_1/b2" | |
top: "stage4_1/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/b2/relu" | |
type: "ReLU" | |
bottom: "stage4_1/b2" | |
top: "stage4_1/b2" | |
} | |
layer { | |
name: "stage4_1/b3" | |
type: "Convolution" | |
bottom: "stage4_1/b2" | |
top: "stage4_1/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage4_1/b3" | |
top: "stage4_1/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_1/b3/scale" | |
type: "Scale" | |
bottom: "stage4_1/b3" | |
top: "stage4_1/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_1/b3/relu" | |
type: "ReLU" | |
bottom: "stage4_1/b3" | |
top: "stage4_1/b3" | |
} | |
layer { | |
name: "stage4_1" | |
type: "Concat" | |
bottom: "stage3/pool" | |
bottom: "stage4_1/a2" | |
bottom: "stage4_1/b3" | |
top: "stage4_1" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage4_2/a1" | |
type: "Convolution" | |
bottom: "stage4_1" | |
top: "stage4_2/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_2/a1" | |
top: "stage4_2/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_2/a1/scale" | |
type: "Scale" | |
bottom: "stage4_2/a1" | |
top: "stage4_2/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/a1/relu" | |
type: "ReLU" | |
bottom: "stage4_2/a1" | |
top: "stage4_2/a1" | |
} | |
layer { | |
name: "stage4_2/a2" | |
type: "Convolution" | |
bottom: "stage4_2/a1" | |
top: "stage4_2/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_2/a2" | |
top: "stage4_2/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_2/a2/scale" | |
type: "Scale" | |
bottom: "stage4_2/a2" | |
top: "stage4_2/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/a2/relu" | |
type: "ReLU" | |
bottom: "stage4_2/a2" | |
top: "stage4_2/a2" | |
} | |
layer { | |
name: "stage4_2/b1" | |
type: "Convolution" | |
bottom: "stage4_1" | |
top: "stage4_2/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_2/b1" | |
top: "stage4_2/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_2/b1/scale" | |
type: "Scale" | |
bottom: "stage4_2/b1" | |
top: "stage4_2/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/b1/relu" | |
type: "ReLU" | |
bottom: "stage4_2/b1" | |
top: "stage4_2/b1" | |
} | |
layer { | |
name: "stage4_2/b2" | |
type: "Convolution" | |
bottom: "stage4_2/b1" | |
top: "stage4_2/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_2/b2" | |
top: "stage4_2/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_2/b2/scale" | |
type: "Scale" | |
bottom: "stage4_2/b2" | |
top: "stage4_2/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/b2/relu" | |
type: "ReLU" | |
bottom: "stage4_2/b2" | |
top: "stage4_2/b2" | |
} | |
layer { | |
name: "stage4_2/b3" | |
type: "Convolution" | |
bottom: "stage4_2/b2" | |
top: "stage4_2/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage4_2/b3" | |
top: "stage4_2/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_2/b3/scale" | |
type: "Scale" | |
bottom: "stage4_2/b3" | |
top: "stage4_2/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_2/b3/relu" | |
type: "ReLU" | |
bottom: "stage4_2/b3" | |
top: "stage4_2/b3" | |
} | |
layer { | |
name: "stage4_2" | |
type: "Concat" | |
bottom: "stage4_1" | |
bottom: "stage4_2/a2" | |
bottom: "stage4_2/b3" | |
top: "stage4_2" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage4_3/a1" | |
type: "Convolution" | |
bottom: "stage4_2" | |
top: "stage4_3/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_3/a1" | |
top: "stage4_3/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_3/a1/scale" | |
type: "Scale" | |
bottom: "stage4_3/a1" | |
top: "stage4_3/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/a1/relu" | |
type: "ReLU" | |
bottom: "stage4_3/a1" | |
top: "stage4_3/a1" | |
} | |
layer { | |
name: "stage4_3/a2" | |
type: "Convolution" | |
bottom: "stage4_3/a1" | |
top: "stage4_3/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_3/a2" | |
top: "stage4_3/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_3/a2/scale" | |
type: "Scale" | |
bottom: "stage4_3/a2" | |
top: "stage4_3/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/a2/relu" | |
type: "ReLU" | |
bottom: "stage4_3/a2" | |
top: "stage4_3/a2" | |
} | |
layer { | |
name: "stage4_3/b1" | |
type: "Convolution" | |
bottom: "stage4_2" | |
top: "stage4_3/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_3/b1" | |
top: "stage4_3/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_3/b1/scale" | |
type: "Scale" | |
bottom: "stage4_3/b1" | |
top: "stage4_3/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/b1/relu" | |
type: "ReLU" | |
bottom: "stage4_3/b1" | |
top: "stage4_3/b1" | |
} | |
layer { | |
name: "stage4_3/b2" | |
type: "Convolution" | |
bottom: "stage4_3/b1" | |
top: "stage4_3/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_3/b2" | |
top: "stage4_3/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_3/b2/scale" | |
type: "Scale" | |
bottom: "stage4_3/b2" | |
top: "stage4_3/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/b2/relu" | |
type: "ReLU" | |
bottom: "stage4_3/b2" | |
top: "stage4_3/b2" | |
} | |
layer { | |
name: "stage4_3/b3" | |
type: "Convolution" | |
bottom: "stage4_3/b2" | |
top: "stage4_3/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage4_3/b3" | |
top: "stage4_3/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_3/b3/scale" | |
type: "Scale" | |
bottom: "stage4_3/b3" | |
top: "stage4_3/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_3/b3/relu" | |
type: "ReLU" | |
bottom: "stage4_3/b3" | |
top: "stage4_3/b3" | |
} | |
layer { | |
name: "stage4_3" | |
type: "Concat" | |
bottom: "stage4_2" | |
bottom: "stage4_3/a2" | |
bottom: "stage4_3/b3" | |
top: "stage4_3" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage4_4/a1" | |
type: "Convolution" | |
bottom: "stage4_3" | |
top: "stage4_4/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_4/a1" | |
top: "stage4_4/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_4/a1/scale" | |
type: "Scale" | |
bottom: "stage4_4/a1" | |
top: "stage4_4/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/a1/relu" | |
type: "ReLU" | |
bottom: "stage4_4/a1" | |
top: "stage4_4/a1" | |
} | |
layer { | |
name: "stage4_4/a2" | |
type: "Convolution" | |
bottom: "stage4_4/a1" | |
top: "stage4_4/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_4/a2" | |
top: "stage4_4/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_4/a2/scale" | |
type: "Scale" | |
bottom: "stage4_4/a2" | |
top: "stage4_4/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/a2/relu" | |
type: "ReLU" | |
bottom: "stage4_4/a2" | |
top: "stage4_4/a2" | |
} | |
layer { | |
name: "stage4_4/b1" | |
type: "Convolution" | |
bottom: "stage4_3" | |
top: "stage4_4/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_4/b1" | |
top: "stage4_4/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_4/b1/scale" | |
type: "Scale" | |
bottom: "stage4_4/b1" | |
top: "stage4_4/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/b1/relu" | |
type: "ReLU" | |
bottom: "stage4_4/b1" | |
top: "stage4_4/b1" | |
} | |
layer { | |
name: "stage4_4/b2" | |
type: "Convolution" | |
bottom: "stage4_4/b1" | |
top: "stage4_4/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_4/b2" | |
top: "stage4_4/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_4/b2/scale" | |
type: "Scale" | |
bottom: "stage4_4/b2" | |
top: "stage4_4/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/b2/relu" | |
type: "ReLU" | |
bottom: "stage4_4/b2" | |
top: "stage4_4/b2" | |
} | |
layer { | |
name: "stage4_4/b3" | |
type: "Convolution" | |
bottom: "stage4_4/b2" | |
top: "stage4_4/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage4_4/b3" | |
top: "stage4_4/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_4/b3/scale" | |
type: "Scale" | |
bottom: "stage4_4/b3" | |
top: "stage4_4/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_4/b3/relu" | |
type: "ReLU" | |
bottom: "stage4_4/b3" | |
top: "stage4_4/b3" | |
} | |
layer { | |
name: "stage4_4" | |
type: "Concat" | |
bottom: "stage4_3" | |
bottom: "stage4_4/a2" | |
bottom: "stage4_4/b3" | |
top: "stage4_4" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage4_5/a1" | |
type: "Convolution" | |
bottom: "stage4_4" | |
top: "stage4_5/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_5/a1" | |
top: "stage4_5/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_5/a1/scale" | |
type: "Scale" | |
bottom: "stage4_5/a1" | |
top: "stage4_5/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/a1/relu" | |
type: "ReLU" | |
bottom: "stage4_5/a1" | |
top: "stage4_5/a1" | |
} | |
layer { | |
name: "stage4_5/a2" | |
type: "Convolution" | |
bottom: "stage4_5/a1" | |
top: "stage4_5/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_5/a2" | |
top: "stage4_5/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_5/a2/scale" | |
type: "Scale" | |
bottom: "stage4_5/a2" | |
top: "stage4_5/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/a2/relu" | |
type: "ReLU" | |
bottom: "stage4_5/a2" | |
top: "stage4_5/a2" | |
} | |
layer { | |
name: "stage4_5/b1" | |
type: "Convolution" | |
bottom: "stage4_4" | |
top: "stage4_5/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_5/b1" | |
top: "stage4_5/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_5/b1/scale" | |
type: "Scale" | |
bottom: "stage4_5/b1" | |
top: "stage4_5/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/b1/relu" | |
type: "ReLU" | |
bottom: "stage4_5/b1" | |
top: "stage4_5/b1" | |
} | |
layer { | |
name: "stage4_5/b2" | |
type: "Convolution" | |
bottom: "stage4_5/b1" | |
top: "stage4_5/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_5/b2" | |
top: "stage4_5/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_5/b2/scale" | |
type: "Scale" | |
bottom: "stage4_5/b2" | |
top: "stage4_5/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/b2/relu" | |
type: "ReLU" | |
bottom: "stage4_5/b2" | |
top: "stage4_5/b2" | |
} | |
layer { | |
name: "stage4_5/b3" | |
type: "Convolution" | |
bottom: "stage4_5/b2" | |
top: "stage4_5/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage4_5/b3" | |
top: "stage4_5/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_5/b3/scale" | |
type: "Scale" | |
bottom: "stage4_5/b3" | |
top: "stage4_5/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_5/b3/relu" | |
type: "ReLU" | |
bottom: "stage4_5/b3" | |
top: "stage4_5/b3" | |
} | |
layer { | |
name: "stage4_5" | |
type: "Concat" | |
bottom: "stage4_4" | |
bottom: "stage4_5/a2" | |
bottom: "stage4_5/b3" | |
top: "stage4_5" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage4_6/a1" | |
type: "Convolution" | |
bottom: "stage4_5" | |
top: "stage4_6/a1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_6/a1" | |
top: "stage4_6/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_6/a1/scale" | |
type: "Scale" | |
bottom: "stage4_6/a1" | |
top: "stage4_6/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/a1/relu" | |
type: "ReLU" | |
bottom: "stage4_6/a1" | |
top: "stage4_6/a1" | |
} | |
layer { | |
name: "stage4_6/a2" | |
type: "Convolution" | |
bottom: "stage4_6/a1" | |
top: "stage4_6/a2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_6/a2" | |
top: "stage4_6/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_6/a2/scale" | |
type: "Scale" | |
bottom: "stage4_6/a2" | |
top: "stage4_6/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/a2/relu" | |
type: "ReLU" | |
bottom: "stage4_6/a2" | |
top: "stage4_6/a2" | |
} | |
layer { | |
name: "stage4_6/b1" | |
type: "Convolution" | |
bottom: "stage4_5" | |
top: "stage4_6/b1" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage4_6/b1" | |
top: "stage4_6/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_6/b1/scale" | |
type: "Scale" | |
bottom: "stage4_6/b1" | |
top: "stage4_6/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/b1/relu" | |
type: "ReLU" | |
bottom: "stage4_6/b1" | |
top: "stage4_6/b1" | |
} | |
layer { | |
name: "stage4_6/b2" | |
type: "Convolution" | |
bottom: "stage4_6/b1" | |
top: "stage4_6/b2" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage4_6/b2" | |
top: "stage4_6/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_6/b2/scale" | |
type: "Scale" | |
bottom: "stage4_6/b2" | |
top: "stage4_6/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/b2/relu" | |
type: "ReLU" | |
bottom: "stage4_6/b2" | |
top: "stage4_6/b2" | |
} | |
layer { | |
name: "stage4_6/b3" | |
type: "Convolution" | |
bottom: "stage4_6/b2" | |
top: "stage4_6/b3" | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage4_6/b3" | |
top: "stage4_6/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage4_6/b3/scale" | |
type: "Scale" | |
bottom: "stage4_6/b3" | |
top: "stage4_6/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage4_6/b3/relu" | |
type: "ReLU" | |
bottom: "stage4_6/b3" | |
top: "stage4_6/b3" | |
} | |
layer { | |
name: "stage4_6" | |
type: "Concat" | |
bottom: "stage4_5" | |
bottom: "stage4_6/a2" | |
bottom: "stage4_6/b3" | |
top: "stage4_6" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage5/a1" | |
type: "Convolution" | |
bottom: "stage4_6" | |
top: "stage5/a1" | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage5/a1/bn" | |
type: "BatchNorm" | |
bottom: "stage5/a1" | |
top: "stage5/a1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage5/a1/scale" | |
type: "Scale" | |
bottom: "stage5/a1" | |
top: "stage5/a1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage5/a1/relu" | |
type: "ReLU" | |
bottom: "stage5/a1" | |
top: "stage5/a1" | |
} | |
layer { | |
name: "stage5/a2" | |
type: "Convolution" | |
bottom: "stage5/a1" | |
top: "stage5/a2" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage5/a2/bn" | |
type: "BatchNorm" | |
bottom: "stage5/a2" | |
top: "stage5/a2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage5/a2/scale" | |
type: "Scale" | |
bottom: "stage5/a2" | |
top: "stage5/a2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage5/a2/relu" | |
type: "ReLU" | |
bottom: "stage5/a2" | |
top: "stage5/a2" | |
} | |
layer { | |
name: "stage5/b1" | |
type: "Convolution" | |
bottom: "stage4_6" | |
top: "stage5/b1" | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage5/b1/bn" | |
type: "BatchNorm" | |
bottom: "stage5/b1" | |
top: "stage5/b1" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage5/b1/scale" | |
type: "Scale" | |
bottom: "stage5/b1" | |
top: "stage5/b1" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage5/b1/relu" | |
type: "ReLU" | |
bottom: "stage5/b1" | |
top: "stage5/b1" | |
} | |
layer { | |
name: "stage5/b2" | |
type: "Convolution" | |
bottom: "stage5/b1" | |
top: "stage5/b2" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage5/b2/bn" | |
type: "BatchNorm" | |
bottom: "stage5/b2" | |
top: "stage5/b2" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage5/b2/scale" | |
type: "Scale" | |
bottom: "stage5/b2" | |
top: "stage5/b2" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage5/b2/relu" | |
type: "ReLU" | |
bottom: "stage5/b2" | |
top: "stage5/b2" | |
} | |
layer { | |
name: "stage5/b3" | |
type: "Convolution" | |
bottom: "stage5/b2" | |
top: "stage5/b3" | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage5/b3/bn" | |
type: "BatchNorm" | |
bottom: "stage5/b3" | |
top: "stage5/b3" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage5/b3/scale" | |
type: "Scale" | |
bottom: "stage5/b3" | |
top: "stage5/b3" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage5/b3/relu" | |
type: "ReLU" | |
bottom: "stage5/b3" | |
top: "stage5/b3" | |
} | |
layer { | |
name: "stage5" | |
type: "Concat" | |
bottom: "stage4_6" | |
bottom: "stage5/a2" | |
bottom: "stage5/b3" | |
top: "stage5" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "stage5a" | |
type: "Convolution" | |
bottom: "stage5" | |
top: "stage5a" | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
} | |
} | |
layer { | |
name: "stage5a/bn" | |
type: "BatchNorm" | |
bottom: "stage5a" | |
top: "stage5a" | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.0 | |
decay_mult: 0.0 | |
} | |
batch_norm_param { | |
moving_average_fraction: 0.999000012875 | |
eps: 0.0010000000475 | |
} | |
} | |
layer { | |
name: "stage5a/scale" | |
type: "Scale" | |
bottom: "stage5a" | |
top: "stage5a" | |
scale_param { | |
filler { | |
value: 1.0 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0.0 | |
} | |
} | |
} | |
layer { | |
name: "stage5a/relu" | |
type: "ReLU" | |
bottom: "stage5a" | |
top: "stage5a" | |
} | |
layer { | |
name: "conv_indoor" | |
type: "Convolution" | |
bottom: "stage5a" | |
top: "conv_indoor" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 125 | |
kernel_size: 1 | |
pad: 0 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "Region_Loss" | |
type: "RegionLoss" | |
bottom: "conv_indoor" | |
bottom: "label" | |
top: "det_loss1" | |
loss_weight: 1 | |
region_loss_param { | |
side: 13 | |
num_class: 20 | |
coords: 4 | |
num: 5 | |
softmax: 1 | |
jitter: 0.2 | |
rescore: 1 | |
object_scale: 5.0 | |
noobject_scale: 1.0 | |
class_scale: 1.0 | |
coord_scale: 1.0 | |
absolute: 1 | |
thresh: 0.6 | |
random: 0 | |
biases: 1.08 | |
biases: 1.19 | |
biases: 3.42 | |
biases: 4.41 | |
biases: 6.63 | |
biases: 11.38 | |
biases: 9.42 | |
biases: 5.11 | |
biases: 16.62 | |
biases: 10.52 | |
} | |
} |
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