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name: "MobileNet-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 | |
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: 6 | |
backend: LMDB | |
} | |
annotated_data_param { | |
yolo_data_type : 1 | |
yolo_data_jitter : 0.3 | |
label_map_file: "data/VOC0712/labelmap_voc.prototxt" | |
} | |
} | |
layer { | |
name: "conv0" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv0" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv0/bn" | |
type: "BatchNorm" | |
bottom: "conv0" | |
top: "conv0" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv0/scale" | |
type: "Scale" | |
bottom: "conv0" | |
top: "conv0" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv0/relu" | |
type: "ReLU" | |
bottom: "conv0" | |
top: "conv0" | |
} | |
layer { | |
name: "conv1/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv0" | |
top: "conv1/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 32 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv1/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv1/dw" | |
top: "conv1/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv1/dw/scale" | |
type: "Scale" | |
bottom: "conv1/dw" | |
top: "conv1/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv1/dw/relu" | |
type: "ReLU" | |
bottom: "conv1/dw" | |
top: "conv1/dw" | |
} | |
layer { | |
name: "conv1" | |
type: "Convolution" | |
bottom: "conv1/dw" | |
top: "conv1" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
kernel_size: 1 | |
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 | |
} | |
} | |
layer { | |
name: "conv1/scale" | |
type: "Scale" | |
bottom: "conv1" | |
top: "conv1" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv1/relu" | |
type: "ReLU" | |
bottom: "conv1" | |
top: "conv1" | |
} | |
layer { | |
name: "conv2/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv1" | |
top: "conv2/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
group: 64 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv2/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv2/dw" | |
top: "conv2/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv2/dw/scale" | |
type: "Scale" | |
bottom: "conv2/dw" | |
top: "conv2/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv2/dw/relu" | |
type: "ReLU" | |
bottom: "conv2/dw" | |
top: "conv2/dw" | |
} | |
layer { | |
name: "conv2" | |
type: "Convolution" | |
bottom: "conv2/dw" | |
top: "conv2" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv2/bn" | |
type: "BatchNorm" | |
bottom: "conv2" | |
top: "conv2" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv2/scale" | |
type: "Scale" | |
bottom: "conv2" | |
top: "conv2" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv2/relu" | |
type: "ReLU" | |
bottom: "conv2" | |
top: "conv2" | |
} | |
layer { | |
name: "conv3/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv2" | |
top: "conv3/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 128 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv3/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv3/dw" | |
top: "conv3/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv3/dw/scale" | |
type: "Scale" | |
bottom: "conv3/dw" | |
top: "conv3/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv3/dw/relu" | |
type: "ReLU" | |
bottom: "conv3/dw" | |
top: "conv3/dw" | |
} | |
layer { | |
name: "conv3" | |
type: "Convolution" | |
bottom: "conv3/dw" | |
top: "conv3" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv3/bn" | |
type: "BatchNorm" | |
bottom: "conv3" | |
top: "conv3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv3/scale" | |
type: "Scale" | |
bottom: "conv3" | |
top: "conv3" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv3/relu" | |
type: "ReLU" | |
bottom: "conv3" | |
top: "conv3" | |
} | |
layer { | |
name: "conv4/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv3" | |
top: "conv4/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
group: 128 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv4/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv4/dw" | |
top: "conv4/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv4/dw/scale" | |
type: "Scale" | |
bottom: "conv4/dw" | |
top: "conv4/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv4/dw/relu" | |
type: "ReLU" | |
bottom: "conv4/dw" | |
top: "conv4/dw" | |
} | |
layer { | |
name: "conv4" | |
type: "Convolution" | |
bottom: "conv4/dw" | |
top: "conv4" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv4/bn" | |
type: "BatchNorm" | |
bottom: "conv4" | |
top: "conv4" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv4/scale" | |
type: "Scale" | |
bottom: "conv4" | |
top: "conv4" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv4/relu" | |
type: "ReLU" | |
bottom: "conv4" | |
top: "conv4" | |
} | |
layer { | |
name: "conv5/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv4" | |
top: "conv5/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 256 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv5/dw" | |
top: "conv5/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5/dw/scale" | |
type: "Scale" | |
bottom: "conv5/dw" | |
top: "conv5/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv5/dw/relu" | |
type: "ReLU" | |
bottom: "conv5/dw" | |
top: "conv5/dw" | |
} | |
layer { | |
name: "conv5" | |
type: "Convolution" | |
bottom: "conv5/dw" | |
top: "conv5" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5/bn" | |
type: "BatchNorm" | |
bottom: "conv5" | |
top: "conv5" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5/scale" | |
type: "Scale" | |
bottom: "conv5" | |
top: "conv5" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv5/relu" | |
type: "ReLU" | |
bottom: "conv5" | |
top: "conv5" | |
} | |
layer { | |
name: "conv6/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv5" | |
top: "conv6/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
group: 256 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv6/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv6/dw" | |
top: "conv6/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv6/dw/scale" | |
type: "Scale" | |
bottom: "conv6/dw" | |
top: "conv6/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv6/dw/relu" | |
type: "ReLU" | |
bottom: "conv6/dw" | |
top: "conv6/dw" | |
} | |
layer { | |
name: "conv6" | |
type: "Convolution" | |
bottom: "conv6/dw" | |
top: "conv6" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv6/bn" | |
type: "BatchNorm" | |
bottom: "conv6" | |
top: "conv6" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv6/scale" | |
type: "Scale" | |
bottom: "conv6" | |
top: "conv6" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv6/relu" | |
type: "ReLU" | |
bottom: "conv6" | |
top: "conv6" | |
} | |
layer { | |
name: "conv7/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv6" | |
top: "conv7/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 512 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv7/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv7/dw" | |
top: "conv7/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv7/dw/scale" | |
type: "Scale" | |
bottom: "conv7/dw" | |
top: "conv7/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv7/dw/relu" | |
type: "ReLU" | |
bottom: "conv7/dw" | |
top: "conv7/dw" | |
} | |
layer { | |
name: "conv7" | |
type: "Convolution" | |
bottom: "conv7/dw" | |
top: "conv7" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv7/bn" | |
type: "BatchNorm" | |
bottom: "conv7" | |
top: "conv7" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv7/scale" | |
type: "Scale" | |
bottom: "conv7" | |
top: "conv7" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv7/relu" | |
type: "ReLU" | |
bottom: "conv7" | |
top: "conv7" | |
} | |
layer { | |
name: "conv8/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv7" | |
top: "conv8/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 512 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv8/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv8/dw" | |
top: "conv8/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv8/dw/scale" | |
type: "Scale" | |
bottom: "conv8/dw" | |
top: "conv8/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv8/dw/relu" | |
type: "ReLU" | |
bottom: "conv8/dw" | |
top: "conv8/dw" | |
} | |
layer { | |
name: "conv8" | |
type: "Convolution" | |
bottom: "conv8/dw" | |
top: "conv8" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv8/bn" | |
type: "BatchNorm" | |
bottom: "conv8" | |
top: "conv8" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv8/scale" | |
type: "Scale" | |
bottom: "conv8" | |
top: "conv8" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv8/relu" | |
type: "ReLU" | |
bottom: "conv8" | |
top: "conv8" | |
} | |
layer { | |
name: "conv9/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv8" | |
top: "conv9/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 512 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv9/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv9/dw" | |
top: "conv9/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv9/dw/scale" | |
type: "Scale" | |
bottom: "conv9/dw" | |
top: "conv9/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv9/dw/relu" | |
type: "ReLU" | |
bottom: "conv9/dw" | |
top: "conv9/dw" | |
} | |
layer { | |
name: "conv9" | |
type: "Convolution" | |
bottom: "conv9/dw" | |
top: "conv9" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv9/bn" | |
type: "BatchNorm" | |
bottom: "conv9" | |
top: "conv9" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv9/scale" | |
type: "Scale" | |
bottom: "conv9" | |
top: "conv9" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv9/relu" | |
type: "ReLU" | |
bottom: "conv9" | |
top: "conv9" | |
} | |
layer { | |
name: "conv10/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv9" | |
top: "conv10/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 512 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv10/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv10/dw" | |
top: "conv10/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv10/dw/scale" | |
type: "Scale" | |
bottom: "conv10/dw" | |
top: "conv10/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv10/dw/relu" | |
type: "ReLU" | |
bottom: "conv10/dw" | |
top: "conv10/dw" | |
} | |
layer { | |
name: "conv10" | |
type: "Convolution" | |
bottom: "conv10/dw" | |
top: "conv10" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv10/bn" | |
type: "BatchNorm" | |
bottom: "conv10" | |
top: "conv10" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv10/scale" | |
type: "Scale" | |
bottom: "conv10" | |
top: "conv10" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv10/relu" | |
type: "ReLU" | |
bottom: "conv10" | |
top: "conv10" | |
} | |
layer { | |
name: "conv11/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv10" | |
top: "conv11/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 512 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv11/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv11/dw" | |
top: "conv11/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv11/dw/scale" | |
type: "Scale" | |
bottom: "conv11/dw" | |
top: "conv11/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv11/dw/relu" | |
type: "ReLU" | |
bottom: "conv11/dw" | |
top: "conv11/dw" | |
} | |
layer { | |
name: "conv11" | |
type: "Convolution" | |
bottom: "conv11/dw" | |
top: "conv11" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv11/bn" | |
type: "BatchNorm" | |
bottom: "conv11" | |
top: "conv11" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv11/scale" | |
type: "Scale" | |
bottom: "conv11" | |
top: "conv11" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv11/relu" | |
type: "ReLU" | |
bottom: "conv11" | |
top: "conv11" | |
} | |
layer { | |
name: "conv12/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv11" | |
top: "conv12/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
group: 512 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv12/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv12/dw" | |
top: "conv12/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv12/dw/scale" | |
type: "Scale" | |
bottom: "conv12/dw" | |
top: "conv12/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv12/dw/relu" | |
type: "ReLU" | |
bottom: "conv12/dw" | |
top: "conv12/dw" | |
} | |
layer { | |
name: "conv12" | |
type: "Convolution" | |
bottom: "conv12/dw" | |
top: "conv12" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 1024 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv12/bn" | |
type: "BatchNorm" | |
bottom: "conv12" | |
top: "conv12" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv12/scale" | |
type: "Scale" | |
bottom: "conv12" | |
top: "conv12" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv12/relu" | |
type: "ReLU" | |
bottom: "conv12" | |
top: "conv12" | |
} | |
layer { | |
name: "conv13/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv12" | |
top: "conv13/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 1024 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 1024 | |
engine: CAFFE | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv13/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv13/dw" | |
top: "conv13/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv13/dw/scale" | |
type: "Scale" | |
bottom: "conv13/dw" | |
top: "conv13/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv13/dw/relu" | |
type: "ReLU" | |
bottom: "conv13/dw" | |
top: "conv13/dw" | |
} | |
layer { | |
name: "conv13" | |
type: "Convolution" | |
bottom: "conv13/dw" | |
top: "conv13" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 1024 | |
bias_term: false | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv13/bn" | |
type: "BatchNorm" | |
bottom: "conv13" | |
top: "conv13" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv13/scale" | |
type: "Scale" | |
bottom: "conv13" | |
top: "conv13" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
decay_mult: 0.0 | |
} | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv13/relu" | |
type: "ReLU" | |
bottom: "conv13" | |
top: "conv13" | |
} | |
#layer { | |
# name: "concat1" | |
# type: "Concat" | |
# bottom: "conv11" | |
# top: "concat1" | |
#} | |
#layer { | |
# name: "reorg1" | |
# type: "Reorg" | |
# bottom: "concat1" | |
# top: "reorg1" | |
# reorg_param { | |
# stride: 2 | |
# } | |
#} | |
#layer { | |
# name: "concat2" | |
# type: "Concat" | |
# bottom: "reorg1" | |
# bottom: "conv13" | |
# top: "concat2" | |
#} | |
layer { | |
name: "conv16/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv13" | |
top: "conv16/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 1024 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 1024 | |
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: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
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: "conv17" | |
type: "Convolution" | |
bottom: "conv16/dw" | |
top: "conv17" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 1024 | |
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: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
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: "upsample" | |
type: "Deconvolution" | |
bottom: "conv17" | |
top: "upsample" | |
param { lr_mult: 0 decay_mult: 0 } | |
convolution_param { | |
num_output: 512 | |
kernel_size: 4 stride: 2 pad: 1 | |
group: 512 | |
weight_filler: { type: "bilinear" } | |
bias_term: false | |
} | |
} | |
layer { | |
name: "conv_18/sum" | |
type: "Eltwise" | |
bottom: "conv11" | |
bottom: "upsample" | |
top: "conv_18/sum" | |
} | |
layer { | |
name: "conv19/dw" | |
type: "DepthwiseConvolution" | |
bottom: "conv_18/sum" | |
top: "conv19/dw" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 512 | |
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: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
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: "conv20" | |
type: "Convolution" | |
bottom: "conv19/dw" | |
top: "conv20" | |
param { | |
lr_mult: 0.1 | |
decay_mult: 0.1 | |
} | |
convolution_param { | |
num_output: 1024 | |
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: 0.1 | |
decay_mult: 0.0 | |
} | |
param { | |
lr_mult: 0.2 | |
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: "conv22_indoor" | |
type: "Convolution" | |
bottom: "conv17" | |
top: "conv22" | |
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: "conv23_indoor" | |
type: "Convolution" | |
bottom: "conv20" | |
top: "conv23" | |
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_Loss1" | |
type: "RegionLoss" | |
bottom: "conv22" | |
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 | |
} | |
} | |
layer { | |
name: "Region_Loss2" | |
type: "RegionLoss" | |
bottom: "conv23" | |
bottom: "label" | |
top: "det_loss2" | |
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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