text YOLOv1
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name: "YOLONet"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 448
dim: 448
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
convolution_param {
num_output: 64
kernel_size: 7
pad: 3
stride: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 192
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv6"
type: "Convolution"
bottom: "conv5"
top: "conv6"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "conv6"
top: "conv6"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool6"
type: "Pooling"
bottom: "conv6"
top: "pool6"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer{
name: "conv7"
type: "Convolution"
bottom: "pool6"
top: "conv7"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu8"
type: "ReLU"
bottom: "conv8"
top: "conv8"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv9"
type: "Convolution"
bottom: "conv8"
top: "conv9"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu13"
type: "ReLU"
bottom: "conv13"
top: "conv13"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv14"
type: "Convolution"
bottom: "conv13"
top: "conv14"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu16"
type: "ReLU"
bottom: "conv16"
top: "conv16"
relu_param{
negative_slope: 0.1
}
}
layer {
name: "pool16"
type: "Pooling"
bottom: "conv16"
top: "pool16"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer{
name: "conv17"
type: "Convolution"
bottom: "pool16"
top: "conv17"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
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"
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu20"
type: "ReLU"
bottom: "conv20"
top: "conv20"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv21"
type: "Convolution"
bottom: "conv20"
top: "conv21"
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu21"
type: "ReLU"
bottom: "conv21"
top: "conv21"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv22"
type: "Convolution"
bottom: "conv21"
top: "conv22"
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu22"
type: "ReLU"
bottom: "conv22"
top: "conv22"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv23"
type: "Convolution"
bottom: "conv22"
top: "conv23"
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu23"
type: "ReLU"
bottom: "conv23"
top: "conv23"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "conv24"
type: "Convolution"
bottom: "conv23"
top: "conv24"
convolution_param {
num_output: 1024
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu24"
type: "ReLU"
bottom: "conv24"
top: "conv24"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "fc25"
type: "InnerProduct"
bottom: "conv24"
top: "fc25"
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu25"
type: "ReLU"
bottom: "fc25"
top: "fc25"
relu_param{
negative_slope: 0.1
}
}
layer{
name: "fc26"
type: "InnerProduct"
bottom: "fc25"
top: "result"
inner_product_param {
num_output: 1470
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
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