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eric612/mobilenetv2_yolov3_train.prototxt

Last active December 28, 2018 10:44
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mobilenetv2_yolov3_train.prototxt
name: "MobileNetv2-YOLO"
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
force_color: true
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 608
width: 608
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 416
width: 416
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 320
width: 320
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 352
width: 352
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 384
width: 384
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 448
width: 448
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 480
width: 480
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 512
width: 512
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
height: 544
width: 544
interp_mode: LINEAR
interp_mode: AREA
interp_mode: LANCZOS4
}
resize_param {
prob: 0.1
resize_mode: FIT_LARGE_SIZE_AND_PAD
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
}
}
data_param {
source: "examples/coco/coco_train_lmdb"
batch_size: 3
backend: LMDB
}
annotated_data_param {
yolo_data_type : 1
yolo_data_jitter : 0.3
label_map_file: "data/coco/labelmap_coco.prototxt"
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv1/bn"
type: "BatchNorm"
bottom: "conv1"
top: "conv1"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv1/scale"
type: "Scale"
bottom: "conv1"
top: "conv1"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv2_1/expand"
type: "Convolution"
bottom: "conv1"
top: "conv2_1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/expand/bn"
type: "BatchNorm"
bottom: "conv2_1/expand"
top: "conv2_1/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv2_1/expand/scale"
type: "Scale"
bottom: "conv2_1/expand"
top: "conv2_1/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu2_1/expand"
type: "ReLU"
bottom: "conv2_1/expand"
top: "conv2_1/expand"
}
layer {
name: "conv2_1/dwise"
type: "DepthwiseConvolution"
bottom: "conv2_1/expand"
top: "conv2_1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
group: 32
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv2_1/dwise/bn"
type: "BatchNorm"
bottom: "conv2_1/dwise"
top: "conv2_1/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv2_1/dwise/scale"
type: "Scale"
bottom: "conv2_1/dwise"
top: "conv2_1/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu2_1/dwise"
type: "ReLU"
bottom: "conv2_1/dwise"
top: "conv2_1/dwise"
}
layer {
name: "conv2_1/linear"
type: "Convolution"
bottom: "conv2_1/dwise"
top: "conv2_1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 16
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_1/linear/bn"
type: "BatchNorm"
bottom: "conv2_1/linear"
top: "conv2_1/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv2_1/linear/scale"
type: "Scale"
bottom: "conv2_1/linear"
top: "conv2_1/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv2_2/expand"
type: "Convolution"
bottom: "conv2_1/linear"
top: "conv2_2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_2/expand/bn"
type: "BatchNorm"
bottom: "conv2_2/expand"
top: "conv2_2/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv2_2/expand/scale"
type: "Scale"
bottom: "conv2_2/expand"
top: "conv2_2/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu2_2/expand"
type: "ReLU"
bottom: "conv2_2/expand"
top: "conv2_2/expand"
}
layer {
name: "conv2_2/dwise"
type: "DepthwiseConvolution"
bottom: "conv2_2/expand"
top: "conv2_2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
pad: 1
kernel_size: 3
group: 96
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv2_2/dwise/bn"
type: "BatchNorm"
bottom: "conv2_2/dwise"
top: "conv2_2/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv2_2/dwise/scale"
type: "Scale"
bottom: "conv2_2/dwise"
top: "conv2_2/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu2_2/dwise"
type: "ReLU"
bottom: "conv2_2/dwise"
top: "conv2_2/dwise"
}
layer {
name: "conv2_2/linear"
type: "Convolution"
bottom: "conv2_2/dwise"
top: "conv2_2/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 24
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2_2/linear/bn"
type: "BatchNorm"
bottom: "conv2_2/linear"
top: "conv2_2/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv2_2/linear/scale"
type: "Scale"
bottom: "conv2_2/linear"
top: "conv2_2/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv3_1/expand"
type: "Convolution"
bottom: "conv2_2/linear"
top: "conv3_1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 144
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_1/expand/bn"
type: "BatchNorm"
bottom: "conv3_1/expand"
top: "conv3_1/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv3_1/expand/scale"
type: "Scale"
bottom: "conv3_1/expand"
top: "conv3_1/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu3_1/expand"
type: "ReLU"
bottom: "conv3_1/expand"
top: "conv3_1/expand"
}
layer {
name: "conv3_1/dwise"
type: "DepthwiseConvolution"
bottom: "conv3_1/expand"
top: "conv3_1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 144
bias_term: false
pad: 1
kernel_size: 3
group: 144
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv3_1/dwise/bn"
type: "BatchNorm"
bottom: "conv3_1/dwise"
top: "conv3_1/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv3_1/dwise/scale"
type: "Scale"
bottom: "conv3_1/dwise"
top: "conv3_1/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu3_1/dwise"
type: "ReLU"
bottom: "conv3_1/dwise"
top: "conv3_1/dwise"
}
layer {
name: "conv3_1/linear"
type: "Convolution"
bottom: "conv3_1/dwise"
top: "conv3_1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 24
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_1/linear/bn"
type: "BatchNorm"
bottom: "conv3_1/linear"
top: "conv3_1/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv3_1/linear/scale"
type: "Scale"
bottom: "conv3_1/linear"
top: "conv3_1/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_3_1"
type: "Eltwise"
bottom: "conv2_2/linear"
bottom: "conv3_1/linear"
top: "block_3_1"
}
layer {
name: "conv3_2/expand"
type: "Convolution"
bottom: "block_3_1"
top: "conv3_2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 144
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_2/expand/bn"
type: "BatchNorm"
bottom: "conv3_2/expand"
top: "conv3_2/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv3_2/expand/scale"
type: "Scale"
bottom: "conv3_2/expand"
top: "conv3_2/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu3_2/expand"
type: "ReLU"
bottom: "conv3_2/expand"
top: "conv3_2/expand"
}
layer {
name: "conv3_2/dwise"
type: "DepthwiseConvolution"
bottom: "conv3_2/expand"
top: "conv3_2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 144
bias_term: false
pad: 1
kernel_size: 3
group: 144
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv3_2/dwise/bn"
type: "BatchNorm"
bottom: "conv3_2/dwise"
top: "conv3_2/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv3_2/dwise/scale"
type: "Scale"
bottom: "conv3_2/dwise"
top: "conv3_2/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu3_2/dwise"
type: "ReLU"
bottom: "conv3_2/dwise"
top: "conv3_2/dwise"
}
layer {
name: "conv3_2/linear"
type: "Convolution"
bottom: "conv3_2/dwise"
top: "conv3_2/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3_2/linear/bn"
type: "BatchNorm"
bottom: "conv3_2/linear"
top: "conv3_2/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv3_2/linear/scale"
type: "Scale"
bottom: "conv3_2/linear"
top: "conv3_2/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv4_1/expand"
type: "Convolution"
bottom: "conv3_2/linear"
top: "conv4_1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_1/expand/bn"
type: "BatchNorm"
bottom: "conv4_1/expand"
top: "conv4_1/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_1/expand/scale"
type: "Scale"
bottom: "conv4_1/expand"
top: "conv4_1/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_1/expand"
type: "ReLU"
bottom: "conv4_1/expand"
top: "conv4_1/expand"
}
layer {
name: "conv4_1/dwise"
type: "DepthwiseConvolution"
bottom: "conv4_1/expand"
top: "conv4_1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 1
kernel_size: 3
group: 192
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4_1/dwise/bn"
type: "BatchNorm"
bottom: "conv4_1/dwise"
top: "conv4_1/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_1/dwise/scale"
type: "Scale"
bottom: "conv4_1/dwise"
top: "conv4_1/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_1/dwise"
type: "ReLU"
bottom: "conv4_1/dwise"
top: "conv4_1/dwise"
}
layer {
name: "conv4_1/linear"
type: "Convolution"
bottom: "conv4_1/dwise"
top: "conv4_1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_1/linear/bn"
type: "BatchNorm"
bottom: "conv4_1/linear"
top: "conv4_1/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_1/linear/scale"
type: "Scale"
bottom: "conv4_1/linear"
top: "conv4_1/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_4_1"
type: "Eltwise"
bottom: "conv3_2/linear"
bottom: "conv4_1/linear"
top: "block_4_1"
}
layer {
name: "conv4_2/expand"
type: "Convolution"
bottom: "block_4_1"
top: "conv4_2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_2/expand/bn"
type: "BatchNorm"
bottom: "conv4_2/expand"
top: "conv4_2/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_2/expand/scale"
type: "Scale"
bottom: "conv4_2/expand"
top: "conv4_2/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_2/expand"
type: "ReLU"
bottom: "conv4_2/expand"
top: "conv4_2/expand"
}
layer {
name: "conv4_2/dwise"
type: "DepthwiseConvolution"
bottom: "conv4_2/expand"
top: "conv4_2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 1
kernel_size: 3
group: 192
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4_2/dwise/bn"
type: "BatchNorm"
bottom: "conv4_2/dwise"
top: "conv4_2/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_2/dwise/scale"
type: "Scale"
bottom: "conv4_2/dwise"
top: "conv4_2/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_2/dwise"
type: "ReLU"
bottom: "conv4_2/dwise"
top: "conv4_2/dwise"
}
layer {
name: "conv4_2/linear"
type: "Convolution"
bottom: "conv4_2/dwise"
top: "conv4_2/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_2/linear/bn"
type: "BatchNorm"
bottom: "conv4_2/linear"
top: "conv4_2/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_2/linear/scale"
type: "Scale"
bottom: "conv4_2/linear"
top: "conv4_2/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_4_2"
type: "Eltwise"
bottom: "block_4_1"
bottom: "conv4_2/linear"
top: "block_4_2"
}
layer {
name: "conv4_3/expand"
type: "Convolution"
bottom: "block_4_2"
top: "conv4_3/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_3/expand/bn"
type: "BatchNorm"
bottom: "conv4_3/expand"
top: "conv4_3/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_3/expand/scale"
type: "Scale"
bottom: "conv4_3/expand"
top: "conv4_3/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_3/expand"
type: "ReLU"
bottom: "conv4_3/expand"
top: "conv4_3/expand"
}
layer {
name: "conv4_3/dwise"
type: "DepthwiseConvolution"
bottom: "conv4_3/expand"
top: "conv4_3/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 1
kernel_size: 3
group: 192
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4_3/dwise/bn"
type: "BatchNorm"
bottom: "conv4_3/dwise"
top: "conv4_3/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_3/dwise/scale"
type: "Scale"
bottom: "conv4_3/dwise"
top: "conv4_3/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_3/dwise"
type: "ReLU"
bottom: "conv4_3/dwise"
top: "conv4_3/dwise"
}
layer {
name: "conv4_3/linear"
type: "Convolution"
bottom: "conv4_3/dwise"
top: "conv4_3/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_3/linear/bn"
type: "BatchNorm"
bottom: "conv4_3/linear"
top: "conv4_3/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_3/linear/scale"
type: "Scale"
bottom: "conv4_3/linear"
top: "conv4_3/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv4_4/expand"
type: "Convolution"
bottom: "conv4_3/linear"
top: "conv4_4/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_4/expand/bn"
type: "BatchNorm"
bottom: "conv4_4/expand"
top: "conv4_4/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_4/expand/scale"
type: "Scale"
bottom: "conv4_4/expand"
top: "conv4_4/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_4/expand"
type: "ReLU"
bottom: "conv4_4/expand"
top: "conv4_4/expand"
}
layer {
name: "conv4_4/dwise"
type: "DepthwiseConvolution"
bottom: "conv4_4/expand"
top: "conv4_4/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 384
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4_4/dwise/bn"
type: "BatchNorm"
bottom: "conv4_4/dwise"
top: "conv4_4/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_4/dwise/scale"
type: "Scale"
bottom: "conv4_4/dwise"
top: "conv4_4/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_4/dwise"
type: "ReLU"
bottom: "conv4_4/dwise"
top: "conv4_4/dwise"
}
layer {
name: "conv4_4/linear"
type: "Convolution"
bottom: "conv4_4/dwise"
top: "conv4_4/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_4/linear/bn"
type: "BatchNorm"
bottom: "conv4_4/linear"
top: "conv4_4/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_4/linear/scale"
type: "Scale"
bottom: "conv4_4/linear"
top: "conv4_4/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_4_4"
type: "Eltwise"
bottom: "conv4_3/linear"
bottom: "conv4_4/linear"
top: "block_4_4"
}
layer {
name: "conv4_5/expand"
type: "Convolution"
bottom: "block_4_4"
top: "conv4_5/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_5/expand/bn"
type: "BatchNorm"
bottom: "conv4_5/expand"
top: "conv4_5/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_5/expand/scale"
type: "Scale"
bottom: "conv4_5/expand"
top: "conv4_5/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_5/expand"
type: "ReLU"
bottom: "conv4_5/expand"
top: "conv4_5/expand"
}
layer {
name: "conv4_5/dwise"
type: "DepthwiseConvolution"
bottom: "conv4_5/expand"
top: "conv4_5/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 384
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4_5/dwise/bn"
type: "BatchNorm"
bottom: "conv4_5/dwise"
top: "conv4_5/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_5/dwise/scale"
type: "Scale"
bottom: "conv4_5/dwise"
top: "conv4_5/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_5/dwise"
type: "ReLU"
bottom: "conv4_5/dwise"
top: "conv4_5/dwise"
}
layer {
name: "conv4_5/linear"
type: "Convolution"
bottom: "conv4_5/dwise"
top: "conv4_5/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_5/linear/bn"
type: "BatchNorm"
bottom: "conv4_5/linear"
top: "conv4_5/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_5/linear/scale"
type: "Scale"
bottom: "conv4_5/linear"
top: "conv4_5/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_4_5"
type: "Eltwise"
bottom: "block_4_4"
bottom: "conv4_5/linear"
top: "block_4_5"
}
layer {
name: "conv4_6/expand"
type: "Convolution"
bottom: "block_4_5"
top: "conv4_6/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_6/expand/bn"
type: "BatchNorm"
bottom: "conv4_6/expand"
top: "conv4_6/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_6/expand/scale"
type: "Scale"
bottom: "conv4_6/expand"
top: "conv4_6/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_6/expand"
type: "ReLU"
bottom: "conv4_6/expand"
top: "conv4_6/expand"
}
layer {
name: "conv4_6/dwise"
type: "DepthwiseConvolution"
bottom: "conv4_6/expand"
top: "conv4_6/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 384
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4_6/dwise/bn"
type: "BatchNorm"
bottom: "conv4_6/dwise"
top: "conv4_6/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_6/dwise/scale"
type: "Scale"
bottom: "conv4_6/dwise"
top: "conv4_6/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_6/dwise"
type: "ReLU"
bottom: "conv4_6/dwise"
top: "conv4_6/dwise"
}
layer {
name: "conv4_6/linear"
type: "Convolution"
bottom: "conv4_6/dwise"
top: "conv4_6/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_6/linear/bn"
type: "BatchNorm"
bottom: "conv4_6/linear"
top: "conv4_6/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_6/linear/scale"
type: "Scale"
bottom: "conv4_6/linear"
top: "conv4_6/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_4_6"
type: "Eltwise"
bottom: "block_4_5"
bottom: "conv4_6/linear"
top: "block_4_6"
}
layer {
name: "conv4_7/expand"
type: "Convolution"
bottom: "block_4_6"
top: "conv4_7/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_7/expand/bn"
type: "BatchNorm"
bottom: "conv4_7/expand"
top: "conv4_7/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_7/expand/scale"
type: "Scale"
bottom: "conv4_7/expand"
top: "conv4_7/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_7/expand"
type: "ReLU"
bottom: "conv4_7/expand"
top: "conv4_7/expand"
}
layer {
name: "conv4_7/dwise"
type: "DepthwiseConvolution"
bottom: "conv4_7/expand"
top: "conv4_7/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
pad: 1
kernel_size: 3
group: 384
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv4_7/dwise/bn"
type: "BatchNorm"
bottom: "conv4_7/dwise"
top: "conv4_7/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_7/dwise/scale"
type: "Scale"
bottom: "conv4_7/dwise"
top: "conv4_7/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu4_7/dwise"
type: "ReLU"
bottom: "conv4_7/dwise"
top: "conv4_7/dwise"
}
layer {
name: "conv4_7/linear"
type: "Convolution"
bottom: "conv4_7/dwise"
top: "conv4_7/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4_7/linear/bn"
type: "BatchNorm"
bottom: "conv4_7/linear"
top: "conv4_7/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv4_7/linear/scale"
type: "Scale"
bottom: "conv4_7/linear"
top: "conv4_7/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv5_1/expand"
type: "Convolution"
bottom: "conv4_7/linear"
top: "conv5_1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 576
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_1/expand/bn"
type: "BatchNorm"
bottom: "conv5_1/expand"
top: "conv5_1/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_1/expand/scale"
type: "Scale"
bottom: "conv5_1/expand"
top: "conv5_1/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu5_1/expand"
type: "ReLU"
bottom: "conv5_1/expand"
top: "conv5_1/expand"
}
layer {
name: "conv5_1/dwise"
type: "DepthwiseConvolution"
bottom: "conv5_1/expand"
top: "conv5_1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 576
bias_term: false
pad: 1
kernel_size: 3
group: 576
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv5_1/dwise/bn"
type: "BatchNorm"
bottom: "conv5_1/dwise"
top: "conv5_1/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_1/dwise/scale"
type: "Scale"
bottom: "conv5_1/dwise"
top: "conv5_1/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu5_1/dwise"
type: "ReLU"
bottom: "conv5_1/dwise"
top: "conv5_1/dwise"
}
layer {
name: "conv5_1/linear"
type: "Convolution"
bottom: "conv5_1/dwise"
top: "conv5_1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_1/linear/bn"
type: "BatchNorm"
bottom: "conv5_1/linear"
top: "conv5_1/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_1/linear/scale"
type: "Scale"
bottom: "conv5_1/linear"
top: "conv5_1/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_5_1"
type: "Eltwise"
bottom: "conv4_7/linear"
bottom: "conv5_1/linear"
top: "block_5_1"
}
layer {
name: "conv5_2/expand"
type: "Convolution"
bottom: "block_5_1"
top: "conv5_2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 576
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_2/expand/bn"
type: "BatchNorm"
bottom: "conv5_2/expand"
top: "conv5_2/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_2/expand/scale"
type: "Scale"
bottom: "conv5_2/expand"
top: "conv5_2/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu5_2/expand"
type: "ReLU"
bottom: "conv5_2/expand"
top: "conv5_2/expand"
}
layer {
name: "conv5_2/dwise"
type: "DepthwiseConvolution"
bottom: "conv5_2/expand"
top: "conv5_2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 576
bias_term: false
pad: 1
kernel_size: 3
group: 576
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv5_2/dwise/bn"
type: "BatchNorm"
bottom: "conv5_2/dwise"
top: "conv5_2/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_2/dwise/scale"
type: "Scale"
bottom: "conv5_2/dwise"
top: "conv5_2/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu5_2/dwise"
type: "ReLU"
bottom: "conv5_2/dwise"
top: "conv5_2/dwise"
}
layer {
name: "conv5_2/linear"
type: "Convolution"
bottom: "conv5_2/dwise"
top: "conv5_2/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_2/linear/bn"
type: "BatchNorm"
bottom: "conv5_2/linear"
top: "conv5_2/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_2/linear/scale"
type: "Scale"
bottom: "conv5_2/linear"
top: "conv5_2/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_5_2"
type: "Eltwise"
bottom: "block_5_1"
bottom: "conv5_2/linear"
top: "block_5_2"
}
layer {
name: "conv5_3/expand"
type: "Convolution"
bottom: "block_5_2"
top: "conv5_3/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 576
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_3/expand/bn"
type: "BatchNorm"
bottom: "conv5_3/expand"
top: "conv5_3/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_3/expand/scale"
type: "Scale"
bottom: "conv5_3/expand"
top: "conv5_3/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu5_3/expand"
type: "ReLU"
bottom: "conv5_3/expand"
top: "conv5_3/expand"
}
layer {
name: "conv5_3/dwise"
type: "DepthwiseConvolution"
bottom: "conv5_3/expand"
top: "conv5_3/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 576
bias_term: false
pad: 1
kernel_size: 3
group: 576
stride: 2
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv5_3/dwise/bn"
type: "BatchNorm"
bottom: "conv5_3/dwise"
top: "conv5_3/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_3/dwise/scale"
type: "Scale"
bottom: "conv5_3/dwise"
top: "conv5_3/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu5_3/dwise"
type: "ReLU"
bottom: "conv5_3/dwise"
top: "conv5_3/dwise"
}
layer {
name: "conv5_3/linear"
type: "Convolution"
bottom: "conv5_3/dwise"
top: "conv5_3/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5_3/linear/bn"
type: "BatchNorm"
bottom: "conv5_3/linear"
top: "conv5_3/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv5_3/linear/scale"
type: "Scale"
bottom: "conv5_3/linear"
top: "conv5_3/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv6_1/expand"
type: "Convolution"
bottom: "conv5_3/linear"
top: "conv6_1/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 960
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_1/expand/bn"
type: "BatchNorm"
bottom: "conv6_1/expand"
top: "conv6_1/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_1/expand/scale"
type: "Scale"
bottom: "conv6_1/expand"
top: "conv6_1/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu6_1/expand"
type: "ReLU"
bottom: "conv6_1/expand"
top: "conv6_1/expand"
}
layer {
name: "conv6_1/dwise"
type: "DepthwiseConvolution"
bottom: "conv6_1/expand"
top: "conv6_1/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 960
bias_term: false
pad: 1
kernel_size: 3
group: 960
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv6_1/dwise/bn"
type: "BatchNorm"
bottom: "conv6_1/dwise"
top: "conv6_1/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_1/dwise/scale"
type: "Scale"
bottom: "conv6_1/dwise"
top: "conv6_1/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu6_1/dwise"
type: "ReLU"
bottom: "conv6_1/dwise"
top: "conv6_1/dwise"
}
layer {
name: "conv6_1/linear"
type: "Convolution"
bottom: "conv6_1/dwise"
top: "conv6_1/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_1/linear/bn"
type: "BatchNorm"
bottom: "conv6_1/linear"
top: "conv6_1/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_1/linear/scale"
type: "Scale"
bottom: "conv6_1/linear"
top: "conv6_1/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_6_1"
type: "Eltwise"
bottom: "conv5_3/linear"
bottom: "conv6_1/linear"
top: "block_6_1"
}
layer {
name: "conv6_2/expand"
type: "Convolution"
bottom: "block_6_1"
top: "conv6_2/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 960
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_2/expand/bn"
type: "BatchNorm"
bottom: "conv6_2/expand"
top: "conv6_2/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_2/expand/scale"
type: "Scale"
bottom: "conv6_2/expand"
top: "conv6_2/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu6_2/expand"
type: "ReLU"
bottom: "conv6_2/expand"
top: "conv6_2/expand"
}
layer {
name: "conv6_2/dwise"
type: "DepthwiseConvolution"
bottom: "conv6_2/expand"
top: "conv6_2/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 960
bias_term: false
pad: 1
kernel_size: 3
group: 960
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv6_2/dwise/bn"
type: "BatchNorm"
bottom: "conv6_2/dwise"
top: "conv6_2/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_2/dwise/scale"
type: "Scale"
bottom: "conv6_2/dwise"
top: "conv6_2/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu6_2/dwise"
type: "ReLU"
bottom: "conv6_2/dwise"
top: "conv6_2/dwise"
}
layer {
name: "conv6_2/linear"
type: "Convolution"
bottom: "conv6_2/dwise"
top: "conv6_2/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_2/linear/bn"
type: "BatchNorm"
bottom: "conv6_2/linear"
top: "conv6_2/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_2/linear/scale"
type: "Scale"
bottom: "conv6_2/linear"
top: "conv6_2/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "block_6_2"
type: "Eltwise"
bottom: "block_6_1"
bottom: "conv6_2/linear"
top: "block_6_2"
}
layer {
name: "conv6_3/expand"
type: "Convolution"
bottom: "block_6_2"
top: "conv6_3/expand"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 960
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_3/expand/bn"
type: "BatchNorm"
bottom: "conv6_3/expand"
top: "conv6_3/expand"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_3/expand/scale"
type: "Scale"
bottom: "conv6_3/expand"
top: "conv6_3/expand"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu6_3/expand"
type: "ReLU"
bottom: "conv6_3/expand"
top: "conv6_3/expand"
}
layer {
name: "conv6_3/dwise"
type: "DepthwiseConvolution"
bottom: "conv6_3/expand"
top: "conv6_3/dwise"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 960
bias_term: false
pad: 1
kernel_size: 3
group: 960
weight_filler {
type: "msra"
}
engine: CAFFE
}
}
layer {
name: "conv6_3/dwise/bn"
type: "BatchNorm"
bottom: "conv6_3/dwise"
top: "conv6_3/dwise"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_3/dwise/scale"
type: "Scale"
bottom: "conv6_3/dwise"
top: "conv6_3/dwise"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu6_3/dwise"
type: "ReLU"
bottom: "conv6_3/dwise"
top: "conv6_3/dwise"
}
layer {
name: "conv6_3/linear"
type: "Convolution"
bottom: "conv6_3/dwise"
top: "conv6_3/linear"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 320
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_3/linear/bn"
type: "BatchNorm"
bottom: "conv6_3/linear"
top: "conv6_3/linear"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_3/linear/scale"
type: "Scale"
bottom: "conv6_3/linear"
top: "conv6_3/linear"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv6_4"
type: "Convolution"
bottom: "conv6_3/linear"
top: "conv6_4"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1280
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6_4/bn"
type: "BatchNorm"
bottom: "conv6_4"
top: "conv6_4"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
batch_norm_param {
eps: 1e-5
}
}
layer {
name: "conv6_4/scale"
type: "Scale"
bottom: "conv6_4"
top: "conv6_4"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "relu6_4"
type: "ReLU"
bottom: "conv6_4"
top: "conv6_4"
}
layer {
name: "conv15/dw"
type: "DepthwiseConvolution"
bottom: "conv6_4"
top: "conv15/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1280
bias_term: false
pad: 1
kernel_size: 3
group: 1280
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv15/dw/bn"
type: "BatchNorm"
bottom: "conv15/dw"
top: "conv15/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv15/dw/scale"
type: "Scale"
bottom: "conv15/dw"
top: "conv15/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv15/dw/relu"
type: "ReLU"
bottom: "conv15/dw"
top: "conv15/dw"
}
layer {
name: "conv15"
type: "Convolution"
bottom: "conv15/dw"
top: "conv15"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1280
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv15/bn"
type: "BatchNorm"
bottom: "conv15"
top: "conv15"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv15/scale"
type: "Scale"
bottom: "conv15"
top: "conv15"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv15/relu"
type: "ReLU"
bottom: "conv15"
top: "conv15"
}
layer {
name: "upsample"
type: "Deconvolution"
bottom: "conv15"
top: "upsample"
param { lr_mult: 0 decay_mult: 0 }
convolution_param {
num_output: 640
group: 640
kernel_size: 1 stride: 2 pad: 0
weight_filler: {
type: "constant"
value : 1
}
bias_term: false
}
}
layer {
name: "maxpool"
top: "maxpool"
bottom: "upsample"
type: "Pooling"
pooling_param {
kernel_size: 2
stride: 1
pool: MAX
pad: 1
}
}
layer {
name: "conv16/dw"
type: "DepthwiseConvolution"
bottom: "maxpool"
top: "conv16/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 640
bias_term: false
pad: 1
kernel_size: 3
group: 640
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv16/dw/bn"
type: "BatchNorm"
bottom: "conv16/dw"
top: "conv16/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv16/dw/scale"
type: "Scale"
bottom: "conv16/dw"
top: "conv16/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv16/dw/relu"
type: "ReLU"
bottom: "conv16/dw"
top: "conv16/dw"
}
layer {
name: "conv16"
type: "Convolution"
bottom: "conv16/dw"
top: "conv16"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 640
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv16/bn"
type: "BatchNorm"
bottom: "conv16"
top: "conv16"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv16/scale"
type: "Scale"
bottom: "conv16"
top: "conv16"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv16/relu"
type: "ReLU"
bottom: "conv16"
top: "conv16"
}
layer {
name: "conv17/dw"
type: "DepthwiseConvolution"
bottom: "block_5_2"
top: "conv17/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
pad: 1
kernel_size: 3
group: 96
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv17/dw/bn"
type: "BatchNorm"
bottom: "conv17/dw"
top: "conv17/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv17/dw/scale"
type: "Scale"
bottom: "conv17/dw"
top: "conv17/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv17/dw/relu"
type: "ReLU"
bottom: "conv17/dw"
top: "conv17/dw"
}
layer {
name: "conv17"
type: "Convolution"
bottom: "conv17/dw"
top: "conv17"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 640
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv17/bn"
type: "BatchNorm"
bottom: "conv17"
top: "conv17"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv17/scale"
type: "Scale"
bottom: "conv17"
top: "conv17"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv17/relu"
type: "ReLU"
bottom: "conv17"
top: "conv17"
}
layer {
name: "conv17/sum"
type: "Eltwise"
bottom: "conv16"
bottom: "conv17"
top: "conv17/sum"
}
layer {
name: "conv18/dw"
type: "DepthwiseConvolution"
bottom: "conv17/sum"
top: "conv18/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 640
bias_term: false
pad: 1
kernel_size: 3
group: 640
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv18/dw/bn"
type: "BatchNorm"
bottom: "conv18/dw"
top: "conv18/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv18/dw/scale"
type: "Scale"
bottom: "conv18/dw"
top: "conv18/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv18/dw/relu"
type: "ReLU"
bottom: "conv18/dw"
top: "conv18/dw"
}
layer {
name: "conv18"
type: "Convolution"
bottom: "conv18/dw"
top: "conv18"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 640
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv18/bn"
type: "BatchNorm"
bottom: "conv18"
top: "conv18"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv18/scale"
type: "Scale"
bottom: "conv18"
top: "conv18"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv18/relu"
type: "ReLU"
bottom: "conv18"
top: "conv18"
}
layer {
name: "upsample2"
type: "Deconvolution"
bottom: "conv18"
top: "upsample2"
param { lr_mult: 0 decay_mult: 0 }
convolution_param {
num_output: 320
group: 320
kernel_size: 1 stride: 2 pad: 0
weight_filler: {
type: "constant"
value : 1
}
bias_term: false
}
}
layer {
name: "maxpool2"
top: "maxpool2"
bottom: "upsample2"
type: "Pooling"
pooling_param {
kernel_size: 2
stride: 1
pool: MAX
pad: 1
}
}
layer {
name: "conv19/dw"
type: "DepthwiseConvolution"
bottom: "maxpool2"
top: "conv19/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 320
bias_term: false
pad: 1
kernel_size: 3
group: 320
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv19/dw/bn"
type: "BatchNorm"
bottom: "conv19/dw"
top: "conv19/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv19/dw/scale"
type: "Scale"
bottom: "conv19/dw"
top: "conv19/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv19/dw/relu"
type: "ReLU"
bottom: "conv19/dw"
top: "conv19/dw"
}
layer {
name: "conv19"
type: "Convolution"
bottom: "conv19/dw"
top: "conv19"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 320
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv19/bn"
type: "BatchNorm"
bottom: "conv19"
top: "conv19"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv19/scale"
type: "Scale"
bottom: "conv19"
top: "conv19"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv19/relu"
type: "ReLU"
bottom: "conv19"
top: "conv19"
}
layer {
name: "conv20/dw"
type: "DepthwiseConvolution"
bottom: "block_4_6"
top: "conv20/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
group: 64
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv20/dw/bn"
type: "BatchNorm"
bottom: "conv20/dw"
top: "conv20/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv20/dw/scale"
type: "Scale"
bottom: "conv20/dw"
top: "conv20/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv20/dw/relu"
type: "ReLU"
bottom: "conv20/dw"
top: "conv20/dw"
}
layer {
name: "conv20"
type: "Convolution"
bottom: "conv20/dw"
top: "conv20"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 320
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv20/bn"
type: "BatchNorm"
bottom: "conv20"
top: "conv20"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv20/scale"
type: "Scale"
bottom: "conv20"
top: "conv20"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv20/relu"
type: "ReLU"
bottom: "conv20"
top: "conv20"
}
layer {
name: "conv20/sum"
type: "Eltwise"
bottom: "conv19"
bottom: "conv20"
top: "conv20/sum"
}
layer {
name: "conv21/dw"
type: "DepthwiseConvolution"
bottom: "conv20/sum"
top: "conv21/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 320
bias_term: false
pad: 1
kernel_size: 3
group: 320
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv21/dw/bn"
type: "BatchNorm"
bottom: "conv21/dw"
top: "conv21/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv21/dw/scale"
type: "Scale"
bottom: "conv21/dw"
top: "conv21/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv21/dw/relu"
type: "ReLU"
bottom: "conv21/dw"
top: "conv21/dw"
}
layer {
name: "conv21"
type: "Convolution"
bottom: "conv21/dw"
top: "conv21"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv21/bn"
type: "BatchNorm"
bottom: "conv21"
top: "conv21"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv21/scale"
type: "Scale"
bottom: "conv21"
top: "conv21"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv21/relu"
type: "ReLU"
bottom: "conv21"
top: "conv21"
}
layer {
name: "conv22"
type: "Convolution"
bottom: "conv15"
top: "conv22"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 255
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "conv23"
type: "Convolution"
bottom: "conv18"
top: "conv23"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 255
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "conv24"
type: "Convolution"
bottom: "conv21"
top: "conv24"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 255
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "Yolov3Loss1"
type: "Yolov3"
bottom: "conv22"
bottom: "label"
top: "det_loss1"
loss_weight: 1
yolov3_param {
side: 13
num_class: 80
num: 3
object_scale: 5.0
noobject_scale: 1.0
class_scale: 1.0
coord_scale: 1.0
thresh: 0.7
anchors_scale : 32
#10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
biases: 10
biases: 13
biases: 16
biases: 30
biases: 33
biases: 23
biases: 30
biases: 61
biases: 62
biases: 45
biases: 59
biases: 119
biases: 116
biases: 90
biases: 156
biases: 198
biases: 373
biases: 326
mask:6
mask:7
mask:8
}
}
layer {
name: "Yolov3Loss2"
type: "Yolov3"
bottom: "conv23"
bottom: "label"
top: "det_loss2"
loss_weight: 1
yolov3_param {
side: 26
num_class: 80
num: 3
object_scale: 5.0
noobject_scale: 1.0
class_scale: 1.0
coord_scale: 1.0
thresh: 0.7
anchors_scale : 16
#10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
biases: 10
biases: 13
biases: 16
biases: 30
biases: 33
biases: 23
biases: 30
biases: 61
biases: 62
biases: 45
biases: 59
biases: 119
biases: 116
biases: 90
biases: 156
biases: 198
biases: 373
biases: 326
mask:3
mask:4
mask:5
}
}
layer {
name: "Yolov3Loss3"
type: "Yolov3"
bottom: "conv24"
bottom: "label"
top: "det_loss3"
loss_weight: 1
yolov3_param {
side: 26
num_class: 80
num: 3
object_scale: 5.0
noobject_scale: 1.0
class_scale: 1.0
coord_scale: 1.0
thresh: 0.6
anchors_scale : 8
#10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
biases: 10
biases: 13
biases: 16
biases: 30
biases: 33
biases: 23
biases: 30
biases: 61
biases: 62
biases: 45
biases: 59
biases: 119
biases: 116
biases: 90
biases: 156
biases: 198
biases: 373
biases: 326
mask:0
mask:1
mask:2
}
}
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