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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
name: "MobileNet-YOLO"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 320
dim: 320
}
+
+
+
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: true
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
+
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: true
pad: 1
kernel_size: 3
group: 32
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
+
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
+
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: true
pad: 1
kernel_size: 3
stride: 2
group: 64
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
+
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
+
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: true
pad: 1
kernel_size: 3
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
+
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
+
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: true
pad: 1
kernel_size: 3
stride: 2
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
+
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
+
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: true
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
+
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
stride: 2
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
stride: 2
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
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: true
pad: 1
kernel_size: 3
group: 1024
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
+
layer {
name: "conv13/relu"
type: "ReLU"
bottom: "conv13"
top: "conv13"
}
+
layer {
name: "conv16/dw"
type: "DepthwiseConvolution"
bottom: "conv13"
top: "conv16/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: true
pad: 1
kernel_size: 3
group: 1024
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: 1024
bias_term: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
+
layer {
name: "conv16/relu"
type: "ReLU"
bottom: "conv16"
top: "conv16"
}
layer {
name: "upsample"
type: "Deconvolution"
bottom: "conv16"
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: true
}
}
layer {
name: "conv17/dw"
type: "DepthwiseConvolution"
bottom: "conv11"
top: "conv17/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: true
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
+
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: 512
bias_term: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv17/relu"
type: "ReLU"
bottom: "conv17"
top: "conv17"
}
layer {
name: "conv17/sum"
type: "Eltwise"
bottom: "conv17"
bottom: "upsample"
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: 512
bias_term: true
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
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: 1024
bias_term: true
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv18/relu"
type: "ReLU"
bottom: "conv18"
top: "conv18"
}
+
+
layer {
name: "conv20"
type: "Convolution"
bottom: "conv16"
top: "conv20"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 75
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
+
layer {
name: "conv21"
type: "Convolution"
bottom: "conv18"
top: "conv21"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 75
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
+
+
layer {
name: "detection_out"
type: "Yolov3DetectionOutput"
bottom: "conv20"
bottom: "conv21"
top: "detection_out"
+
yolov3_detection_output_param {
confidence_threshold: 0.01
nms_threshold: 0.45
num_classes: 20
#10,14, 23,27, 37,58, 81,82, 135,169, 344,319
biases: 10
biases: 14
biases: 23
biases: 27
biases: 37
biases: 58
biases: 81
biases: 82
biases: 135
biases: 169
biases: 344
biases: 319
mask:3
mask:4
mask:5
mask:0
mask:1
mask:2
anchors_scale:32
anchors_scale:16
mask_group_num:2
}
}
+
+ + + +
+ +
+ + + +
+ + +
+ + +
 +
+ + +
+
+
+ +
+
+ +