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@eric612
Created August 7, 2018 05:15
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name: "YOLONET"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 416
dim: 416
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn1"
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: "scale1"
type: "Scale"
bottom: "conv1"
top: "conv1"
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: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer{
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn2"
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: "scale2"
type: "Scale"
bottom: "conv2"
top: "conv2"
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: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer{
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn3"
type: "BatchNorm"
bottom: "conv3"
top: "conv3"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale3"
type: "Scale"
bottom: "conv3"
top: "conv3"
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: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
kernel_size: 1
pad: 0 #??
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn4"
type: "BatchNorm"
bottom: "conv4"
top: "conv4"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale4"
type: "Scale"
bottom: "conv4"
top: "conv4"
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: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn5"
type: "BatchNorm"
bottom: "conv5"
top: "conv5"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale5"
type: "Scale"
bottom: "conv5"
top: "conv5"
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: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer{
name: "conv6"
type: "Convolution"
bottom: "pool5"
top: "conv6"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn6"
type: "BatchNorm"
bottom: "conv6"
top: "conv6"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale6"
type: "Scale"
bottom: "conv6"
top: "conv6"
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: "relu6"
type: "ReLU"
bottom: "conv6"
top: "conv6"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv7"
type: "Convolution"
bottom: "conv6"
top: "conv7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn7"
type: "BatchNorm"
bottom: "conv7"
top: "conv7"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale7"
type: "Scale"
bottom: "conv7"
top: "conv7"
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: "relu7"
type: "ReLU"
bottom: "conv7"
top: "conv7"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv8"
type: "Convolution"
bottom: "conv7"
top: "conv8"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn8"
type: "BatchNorm"
bottom: "conv8"
top: "conv8"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale8"
type: "Scale"
bottom: "conv8"
top: "conv8"
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: "relu8"
type: "ReLU"
bottom: "conv8"
top: "conv8"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool8"
type: "Pooling"
bottom: "conv8"
top: "pool8"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer{
name: "conv9"
type: "Convolution"
bottom: "pool8"
top: "conv9"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn9"
type: "BatchNorm"
bottom: "conv9"
top: "conv9"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale9"
type: "Scale"
bottom: "conv9"
top: "conv9"
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: "relu9"
type: "ReLU"
bottom: "conv9"
top: "conv9"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv10"
type: "Convolution"
bottom: "conv9"
top: "conv10"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn10"
type: "BatchNorm"
bottom: "conv10"
top: "conv10"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale10"
type: "Scale"
bottom: "conv10"
top: "conv10"
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: "relu10"
type: "ReLU"
bottom: "conv10"
top: "conv10"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv11"
type: "Convolution"
bottom: "conv10"
top: "conv11"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn11"
type: "BatchNorm"
bottom: "conv11"
top: "conv11"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale11"
type: "Scale"
bottom: "conv11"
top: "conv11"
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: "relu11"
type: "ReLU"
bottom: "conv11"
top: "conv11"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv12"
type: "Convolution"
bottom: "conv11"
top: "conv12"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn12"
type: "BatchNorm"
bottom: "conv12"
top: "conv12"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale12"
type: "Scale"
bottom: "conv12"
top: "conv12"
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: "relu12"
type: "ReLU"
bottom: "conv12"
top: "conv12"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv13"
type: "Convolution"
bottom: "conv12"
top: "conv13"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn13"
type: "BatchNorm"
bottom: "conv13"
top: "conv13"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale13"
type: "Scale"
bottom: "conv13"
top: "conv13"
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: "relu13"
type: "ReLU"
bottom: "conv13"
top: "conv13"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool13"
type: "Pooling"
bottom: "conv13"
top: "pool13"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer{
name: "conv14"
type: "Convolution"
bottom: "pool13"
top: "conv14"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn14"
type: "BatchNorm"
bottom: "conv14"
top: "conv14"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale14"
type: "Scale"
bottom: "conv14"
top: "conv14"
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: "relu14"
type: "ReLU"
bottom: "conv14"
top: "conv14"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv15"
type: "Convolution"
bottom: "conv14"
top: "conv15"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn15"
type: "BatchNorm"
bottom: "conv15"
top: "conv15"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale15"
type: "Scale"
bottom: "conv15"
top: "conv15"
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: "relu15"
type: "ReLU"
bottom: "conv15"
top: "conv15"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv16"
type: "Convolution"
bottom: "conv15"
top: "conv16"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn16"
type: "BatchNorm"
bottom: "conv16"
top: "conv16"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale16"
type: "Scale"
bottom: "conv16"
top: "conv16"
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: "relu16"
type: "ReLU"
bottom: "conv16"
top: "conv16"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv17"
type: "Convolution"
bottom: "conv16"
top: "conv17"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn17"
type: "BatchNorm"
bottom: "conv17"
top: "conv17"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale17"
type: "Scale"
bottom: "conv17"
top: "conv17"
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: "relu17"
type: "ReLU"
bottom: "conv17"
top: "conv17"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv18"
type: "Convolution"
bottom: "conv17"
top: "conv18"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn18"
type: "BatchNorm"
bottom: "conv18"
top: "conv18"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale18"
type: "Scale"
bottom: "conv18"
top: "conv18"
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: "relu18"
type: "ReLU"
bottom: "conv18"
top: "conv18"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv19"
type: "Convolution"
bottom: "conv18"
top: "conv19"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn19"
type: "BatchNorm"
bottom: "conv19"
top: "conv19"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale19"
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: "relu19"
type: "ReLU"
bottom: "conv19"
top: "conv19"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv20"
type: "Convolution"
bottom: "conv19"
top: "conv20"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn20"
type: "BatchNorm"
bottom: "conv20"
top: "conv20"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale20"
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: "relu20"
type: "ReLU"
bottom: "conv20"
top: "conv20"
relu_param {
negative_slope: 0.1
}
}
layer{
name: "conv21"
type: "Convolution"
bottom: "conv13"
top: "conv21"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn21"
type: "BatchNorm"
bottom: "conv21"
top: "conv21"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale21"
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: "relu21"
type: "ReLU"
bottom: "conv21"
top: "conv21"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool21"
type: "Pooling"
bottom: "conv21"
top: "pool21"
pooling_param {
pool: AVE
kernel_size: 2
stride: 2
}
}
layer {
name: "concat2"
type: "Concat"
bottom: "pool21"
bottom: "conv20"
top: "concat2"
}
layer{
name: "conv22"
type: "Convolution"
bottom: "concat2"
top: "conv22"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
bias_term: false
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn22"
type: "BatchNorm"
bottom: "conv22"
top: "conv22"
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
param {
lr_mult: 0
decay_mult: 0.0
}
}
layer {
name: "scale22"
type: "Scale"
bottom: "conv22"
top: "conv22"
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: "relu22"
type: "ReLU"
bottom: "conv22"
top: "conv22"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "conv23_indoor"
type: "Convolution"
bottom: "conv22"
top: "conv23_indoor"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 125
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
#0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828
layer {
name: "detection_out"
type: "YoloDetectionOutput"
bottom: "conv23_indoor"
top: "detection_out"
include {
phase: TEST
}
yolo_detection_output_param {
num_classes: 20
coords: 4
confidence_threshold: 0.01
nms_threshold: 0.45
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: "detection_eval"
type: "DetectionEvaluate"
bottom: "detection_out"
bottom: "label"
top: "detection_eval"
include {
phase: TEST
}
detection_evaluate_param {
num_classes: 21
background_label_id: 0
overlap_threshold: 0.5
evaluate_difficult_gt: false
}
}
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