TensorRT-Demo/mtcnn/det3_relu.prototxt

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name: "ONet"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 48
input_dim: 48
##################################
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 32
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1_1"
type: "ReLU"
bottom: "conv1"
top: "conv1_1"
}
layer {
name: "scale1_1"
bottom: "conv1"
top: "conv1_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "ReLU1_2"
type: "ReLU"
bottom: "conv1_2"
top: "conv1_2"
}
layer {
name: "scale1_2"
bottom: "conv1_2"
top: "conv1_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "eltwise-sum1"
type: "Eltwise"
bottom: "conv1_1"
bottom: "conv1_2"
top: "conv1_3"
eltwise_param { operation: SUM }
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1_3"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu2_1"
type: "ReLU"
bottom: "conv2"
top: "conv2_1"
}
layer {
name: "scale2_1"
bottom: "conv2"
top: "conv2_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "ReLU2_2"
type: "ReLU"
bottom: "conv2_2"
top: "conv2_2"
}
layer {
name: "scale2_2"
bottom: "conv2_2"
top: "conv2_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "eltwise-sum2"
type: "Eltwise"
bottom: "conv2_1"
bottom: "conv2_2"
top: "conv2_3"
eltwise_param { operation: SUM }
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2_3"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 64
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3_1"
type: "ReLU"
bottom: "conv3"
top: "conv3_1"
}
layer {
name: "scale3_1"
bottom: "conv3"
top: "conv3_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "ReLU3_2"
type: "ReLU"
bottom: "conv3_2"
top: "conv3_2"
}
layer {
name: "scale3_2"
bottom: "conv3_2"
top: "conv3_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "eltwise-sum3"
type: "Eltwise"
bottom: "conv3_1"
bottom: "conv3_2"
top: "conv3_3"
eltwise_param { operation: SUM }
}
layer {
name: "pool3"
type: "Pooling"
bottom: "conv3_3"
top: "pool3"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv4"
type: "Convolution"
bottom: "pool3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
convolution_param {
num_output: 128
kernel_size: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4_1"
}
layer {
name: "scale4_1"
bottom: "conv4"
top: "conv4_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "ReLU4_2"
type: "ReLU"
bottom: "conv4_2"
top: "conv4_2"
}
layer {
name: "scale4_2"
bottom: "conv4_2"
top: "conv4_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "eltwise-sum4"
type: "Eltwise"
bottom: "conv4_1"
bottom: "conv4_2"
top: "conv4_3"
eltwise_param { operation: SUM }
}
layer {
name: "conv5"
type: "InnerProduct"
bottom: "conv4_3"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
inner_product_param {
#kernel_size: 3
num_output: 256
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu5_1"
type: "ReLU"
bottom: "conv5"
top: "conv5_1"
}
layer {
name: "scale5_1"
bottom: "conv5"
top: "conv5_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "ReLU5_2"
type: "ReLU"
bottom: "conv5_2"
top: "conv5_2"
}
layer {
name: "scale5_2"
bottom: "conv5_2"
top: "conv5_2"
type: "Scale"
scale_param {
axis: 1
bias_term:false
}
}
layer {
name: "eltwise-sum5"
type: "Eltwise"
bottom: "conv5_1"
bottom: "conv5_2"
top: "conv5_3"
eltwise_param { operation: SUM }
}
layer {
name: "conv6-1"
type: "InnerProduct"
bottom: "conv5_3"
top: "conv6-1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
inner_product_param {
#kernel_size: 1
num_output: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv6-2"
type: "InnerProduct"
bottom: "conv5_3"
top: "conv6-2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
inner_product_param {
#kernel_size: 1
num_output: 4
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv6-3"
type: "InnerProduct"
bottom: "conv5_3"
top: "conv6-3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
inner_product_param {
#kernel_size: 1
num_output: 10
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prob1"
type: "Softmax"
bottom: "conv6-1"
top: "prob1"
}