Hi,
I am trying the new SNPE 1.12.0 support for MobileNet-SSD. Using a caffe version of SSD with PriorBox, the SNPE converter fails to recognize PriorBox layer. Is PriorBox supported?
Thanks in advance for any replies.
Rex
$ snpe-caffe-to-dlc -c MobileNetSSD-deploy.prototxt -b MobileNetSSD-model.caffemodel -d MobileNetSSD-model.dlc --encoding bgr --input_size 300 300 --model_version 1_12_0 --in_layer data --in_type image --verbose
2018-02-15 09:29:23,303 - 1003 - DEBUG - no validation target specified.
WARNING: Logging before InitGoogleLogging() is written to STDERR
W0215 09:29:23.330819 31627 _caffe.cpp:122] DEPRECATION WARNING - deprecated use of Python interface
W0215 09:29:23.330850 31627 _caffe.cpp:123] Use this instead (with the named "weights" parameter):
W0215 09:29:23.330855 31627 _caffe.cpp:125] Net('MobileNetSSD-deploy.prototxt', 1, weights='MobileNetSSD-model.caffemodel')
I0215 09:29:23.334318 31627 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: MobileNetSSD-deploy.prototxt
I0215 09:29:23.334486 31627 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0215 09:29:23.334496 31627 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0215 09:29:23.335646 31627 net.cpp:58] Initializing net from parameters:
name: "MobileNet-SSD"
state {
phase: TEST
level: 0
}
layer {
name: "input"
type: "Input"
top: "data"
input_param {
shape {
dim: 1
dim: 3
dim: 300
dim: 300
}
}
}
layer {
name: "conv0"
type: "Convolution"
bottom: "data"
top: "conv0"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv0/relu"
type: "ReLU"
bottom: "conv0"
top: "conv0"
}
layer {
name: "conv1/dw"
type: "Convolution"
bottom: "conv0"
top: "conv1/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
group: 32
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv1/relu"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv2/dw"
type: "Convolution"
bottom: "conv1"
top: "conv2/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
group: 64
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv2/relu"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "conv3/dw"
type: "Convolution"
bottom: "conv2"
top: "conv3/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv3/relu"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4/dw"
type: "Convolution"
bottom: "conv3"
top: "conv4/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv4/relu"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5/dw"
type: "Convolution"
bottom: "conv4"
top: "conv5/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 256
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv5/relu"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "conv6/dw"
type: "Convolution"
bottom: "conv5"
top: "conv6/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 256
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv6/relu"
type: "ReLU"
bottom: "conv6"
top: "conv6"
}
layer {
name: "conv7/dw"
type: "Convolution"
bottom: "conv6"
top: "conv7/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv7/relu"
type: "ReLU"
bottom: "conv7"
top: "conv7"
}
layer {
name: "conv8/dw"
type: "Convolution"
bottom: "conv7"
top: "conv8/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv8/relu"
type: "ReLU"
bottom: "conv8"
top: "conv8"
}
layer {
name: "conv9/dw"
type: "Convolution"
bottom: "conv8"
top: "conv9/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv9/relu"
type: "ReLU"
bottom: "conv9"
top: "conv9"
}
layer {
name: "conv10/dw"
type: "Convolution"
bottom: "conv9"
top: "conv10/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv10/relu"
type: "ReLU"
bottom: "conv10"
top: "conv10"
}
layer {
name: "conv11/dw"
type: "Convolution"
bottom: "conv10"
top: "conv11/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
group: 512
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv11/relu"
type: "ReLU"
bottom: "conv11"
top: "conv11"
}
layer {
name: "conv12/dw"
type: "Convolution"
bottom: "conv11"
top: "conv12/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
group: 512
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv12/relu"
type: "ReLU"
bottom: "conv12"
top: "conv12"
}
layer {
name: "conv13/dw"
type: "Convolution"
bottom: "conv12"
top: "conv13/dw"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
pad: 1
kernel_size: 3
group: 1024
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
engine: CAFFE
}
}
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: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1024
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv13/relu"
type: "ReLU"
bottom: "conv13"
top: "conv13"
}
layer {
name: "conv14_1"
type: "Convolution"
bottom: "conv13"
top: "conv14_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv14_1/relu"
type: "ReLU"
bottom: "conv14_1"
top: "conv14_1"
}
layer {
name: "conv14_2"
type: "Convolution"
bottom: "conv14_1"
top: "conv14_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv14_2/relu"
type: "ReLU"
bottom: "conv14_2"
top: "conv14_2"
}
layer {
name: "conv15_1"
type: "Convolution"
bottom: "conv14_2"
top: "conv15_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv15_1/relu"
type: "ReLU"
bottom: "conv15_1"
top: "conv15_1"
}
layer {
name: "conv15_2"
type: "Convolution"
bottom: "conv15_1"
top: "conv15_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv15_2/relu"
type: "ReLU"
bottom: "conv15_2"
top: "conv15_2"
}
layer {
name: "conv16_1"
type: "Convolution"
bottom: "conv15_2"
top: "conv16_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv16_1/relu"
type: "ReLU"
bottom: "conv16_1"
top: "conv16_1"
}
layer {
name: "conv16_2"
type: "Convolution"
bottom: "conv16_1"
top: "conv16_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv16_2/relu"
type: "ReLU"
bottom: "conv16_2"
top: "conv16_2"
}
layer {
name: "conv17_1"
type: "Convolution"
bottom: "conv16_2"
top: "conv17_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv17_1/relu"
type: "ReLU"
bottom: "conv17_1"
top: "conv17_1"
}
layer {
name: "conv17_2"
type: "Convolution"
bottom: "conv17_1"
top: "conv17_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv17_2/relu"
type: "ReLU"
bottom: "conv17_2"
top: "conv17_2"
}
layer {
name: "conv11_mbox_loc"
type: "Convolution"
bottom: "conv11"
top: "conv11_mbox_loc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 12
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv11_mbox_loc_perm"
type: "Permute"
bottom: "conv11_mbox_loc"
top: "conv11_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv11_mbox_loc_flat"
type: "Flatten"
bottom: "conv11_mbox_loc_perm"
top: "conv11_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv11_mbox_conf"
type: "Convolution"
bottom: "conv11"
top: "conv11_mbox_conf"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 63
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv11_mbox_conf_perm"
type: "Permute"
bottom: "conv11_mbox_conf"
top: "conv11_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv11_mbox_conf_flat"
type: "Flatten"
bottom: "conv11_mbox_conf_perm"
top: "conv11_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv11_mbox_priorbox"
type: "PriorBox"
bottom: "conv11"
bottom: "data"
top: "conv11_mbox_priorbox"
prior_box_param {
min_size: 60
aspect_ratio: 2
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "conv13_mbox_loc"
type: "Convolution"
bottom: "conv13"
top: "conv13_mbox_loc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv13_mbox_loc_perm"
type: "Permute"
bottom: "conv13_mbox_loc"
top: "conv13_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv13_mbox_loc_flat"
type: "Flatten"
bottom: "conv13_mbox_loc_perm"
top: "conv13_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv13_mbox_conf"
type: "Convolution"
bottom: "conv13"
top: "conv13_mbox_conf"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 126
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv13_mbox_conf_perm"
type: "Permute"
bottom: "conv13_mbox_conf"
top: "conv13_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv13_mbox_conf_flat"
type: "Flatten"
bottom: "conv13_mbox_conf_perm"
top: "conv13_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv13_mbox_priorbox"
type: "PriorBox"
bottom: "conv13"
bottom: "data"
top: "conv13_mbox_priorbox"
prior_box_param {
min_size: 105
max_size: 150
aspect_ratio: 2
aspect_ratio: 3
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "conv14_2_mbox_loc"
type: "Convolution"
bottom: "conv14_2"
top: "conv14_2_mbox_loc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv14_2_mbox_loc_perm"
type: "Permute"
bottom: "conv14_2_mbox_loc"
top: "conv14_2_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv14_2_mbox_loc_flat"
type: "Flatten"
bottom: "conv14_2_mbox_loc_perm"
top: "conv14_2_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv14_2_mbox_conf"
type: "Convolution"
bottom: "conv14_2"
top: "conv14_2_mbox_conf"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 126
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv14_2_mbox_conf_perm"
type: "Permute"
bottom: "conv14_2_mbox_conf"
top: "conv14_2_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv14_2_mbox_conf_flat"
type: "Flatten"
bottom: "conv14_2_mbox_conf_perm"
top: "conv14_2_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv14_2_mbox_priorbox"
type: "PriorBox"
bottom: "conv14_2"
bottom: "data"
top: "conv14_2_mbox_priorbox"
prior_box_param {
min_size: 150
max_size: 195
aspect_ratio: 2
aspect_ratio: 3
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "conv15_2_mbox_loc"
type: "Convolution"
bottom: "conv15_2"
top: "conv15_2_mbox_loc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv15_2_mbox_loc_perm"
type: "Permute"
bottom: "conv15_2_mbox_loc"
top: "conv15_2_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv15_2_mbox_loc_flat"
type: "Flatten"
bottom: "conv15_2_mbox_loc_perm"
top: "conv15_2_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv15_2_mbox_conf"
type: "Convolution"
bottom: "conv15_2"
top: "conv15_2_mbox_conf"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 126
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv15_2_mbox_conf_perm"
type: "Permute"
bottom: "conv15_2_mbox_conf"
top: "conv15_2_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv15_2_mbox_conf_flat"
type: "Flatten"
bottom: "conv15_2_mbox_conf_perm"
top: "conv15_2_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv15_2_mbox_priorbox"
type: "PriorBox"
bottom: "conv15_2"
bottom: "data"
top: "conv15_2_mbox_priorbox"
prior_box_param {
min_size: 195
max_size: 240
aspect_ratio: 2
aspect_ratio: 3
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "conv16_2_mbox_loc"
type: "Convolution"
bottom: "conv16_2"
top: "conv16_2_mbox_loc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv16_2_mbox_loc_perm"
type: "Permute"
bottom: "conv16_2_mbox_loc"
top: "conv16_2_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv16_2_mbox_loc_flat"
type: "Flatten"
bottom: "conv16_2_mbox_loc_perm"
top: "conv16_2_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv16_2_mbox_conf"
type: "Convolution"
bottom: "conv16_2"
top: "conv16_2_mbox_conf"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 126
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv16_2_mbox_conf_perm"
type: "Permute"
bottom: "conv16_2_mbox_conf"
top: "conv16_2_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv16_2_mbox_conf_flat"
type: "Flatten"
bottom: "conv16_2_mbox_conf_perm"
top: "conv16_2_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv16_2_mbox_priorbox"
type: "PriorBox"
bottom: "conv16_2"
bottom: "data"
top: "conv16_2_mbox_priorbox"
prior_box_param {
min_size: 240
max_size: 285
aspect_ratio: 2
aspect_ratio: 3
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "conv17_2_mbox_loc"
type: "Convolution"
bottom: "conv17_2"
top: "conv17_2_mbox_loc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv17_2_mbox_loc_perm"
type: "Permute"
bottom: "conv17_2_mbox_loc"
top: "conv17_2_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv17_2_mbox_loc_flat"
type: "Flatten"
bottom: "conv17_2_mbox_loc_perm"
top: "conv17_2_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv17_2_mbox_conf"
type: "Convolution"
bottom: "conv17_2"
top: "conv17_2_mbox_conf"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 126
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv17_2_mbox_conf_perm"
type: "Permute"
bottom: "conv17_2_mbox_conf"
top: "conv17_2_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv17_2_mbox_conf_flat"
type: "Flatten"
bottom: "conv17_2_mbox_conf_perm"
top: "conv17_2_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv17_2_mbox_priorbox"
type: "PriorBox"
bottom: "conv17_2"
bottom: "data"
top: "conv17_2_mbox_priorbox"
prior_box_param {
min_size: 285
max_size: 300
aspect_ratio: 2
aspect_ratio: 3
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "mbox_loc"
type: "Concat"
bottom: "conv11_mbox_loc_flat"
bottom: "conv13_mbox_loc_flat"
bottom: "conv14_2_mbox_loc_flat"
bottom: "conv15_2_mbox_loc_flat"
bottom: "conv16_2_mbox_loc_flat"
bottom: "conv17_2_mbox_loc_flat"
top: "mbox_loc"
concat_param {
axis: 1
}
}
layer {
name: "mbox_conf"
type: "Concat"
bottom: "conv11_mbox_conf_flat"
bottom: "conv13_mbox_conf_flat"
bottom: "conv14_2_mbox_conf_flat"
bottom: "conv15_2_mbox_conf_flat"
bottom: "conv16_2_mbox_conf_flat"
bottom: "conv17_2_mbox_conf_flat"
top: "mbox_conf"
concat_param {
axis: 1
}
}
layer {
name: "mbox_priorbox"
type: "Concat"
bottom: "conv11_mbox_priorbox"
bottom: "conv13_mbox_priorbox"
bottom: "conv14_2_mbox_priorbox"
bottom: "conv15_2_mbox_priorbox"
bottom: "conv16_2_mbox_priorbox"
bottom: "conv17_2_mbox_priorbox"
top: "mbox_priorbox"
concat_param {
axis: 2
}
}
layer {
name: "mbox_conf_reshape"
type: "Reshape"
bottom: "mbox_conf"
top: "mbox_conf_reshape"
reshape_param {
shape {
dim: 0
dim: -1
dim: 21
}
}
}
layer {
name: "mbox_conf_softmax"
type: "Softmax"
bottom: "mbox_conf_reshape"
top: "mbox_conf_softmax"
softmax_param {
axis: 2
}
}
layer {
name: "mbox_conf_flatten"
type: "Flatten"
bottom: "mbox_conf_softmax"
top: "mbox_conf_flatten"
flatten_param {
axis: 1
}
}
layer {
name: "detection_out"
type: "DetectionOutput"
bottom: "mbox_loc"
bottom: "mbox_conf_flatten"
bottom: "mbox_priorbox"
top: "detection_out"
include {
phase: TEST
}
detection_output_param {
num_classes: 21
share_location: true
background_label_id: 0
nms_param {
nms_threshold: 0.45
top_k: 100
}
code_type: CENTER_SIZE
keep_top_k: 100
confidence_threshold: 0.25
}
}
I0215 09:29:23.336915 31627 layer_factory.hpp:77] Creating layer input
I0215 09:29:23.336925 31627 net.cpp:100] Creating Layer input
I0215 09:29:23.336930 31627 net.cpp:408] input -> data
I0215 09:29:23.336953 31627 net.cpp:150] Setting up input
I0215 09:29:23.336959 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.336963 31627 net.cpp:165] Memory required for data: 1080000
I0215 09:29:23.336967 31627 layer_factory.hpp:77] Creating layer data_input_0_split
I0215 09:29:23.336973 31627 net.cpp:100] Creating Layer data_input_0_split
I0215 09:29:23.336977 31627 net.cpp:434] data_input_0_split <- data
I0215 09:29:23.336983 31627 net.cpp:408] data_input_0_split -> data_input_0_split_0
I0215 09:29:23.336990 31627 net.cpp:408] data_input_0_split -> data_input_0_split_1
I0215 09:29:23.336997 31627 net.cpp:408] data_input_0_split -> data_input_0_split_2
I0215 09:29:23.337003 31627 net.cpp:408] data_input_0_split -> data_input_0_split_3
I0215 09:29:23.337009 31627 net.cpp:408] data_input_0_split -> data_input_0_split_4
I0215 09:29:23.337015 31627 net.cpp:408] data_input_0_split -> data_input_0_split_5
I0215 09:29:23.337021 31627 net.cpp:408] data_input_0_split -> data_input_0_split_6
I0215 09:29:23.337029 31627 net.cpp:150] Setting up data_input_0_split
I0215 09:29:23.337034 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.337038 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.337043 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.337046 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.337050 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.337054 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.337059 31627 net.cpp:157] Top shape: 1 3 300 300 (270000)
I0215 09:29:23.337062 31627 net.cpp:165] Memory required for data: 8640000
I0215 09:29:23.337065 31627 layer_factory.hpp:77] Creating layer conv0
I0215 09:29:23.337074 31627 net.cpp:100] Creating Layer conv0
I0215 09:29:23.337079 31627 net.cpp:434] conv0 <- data_input_0_split_0
I0215 09:29:23.337085 31627 net.cpp:408] conv0 -> conv0
I0215 09:29:23.337486 31627 net.cpp:150] Setting up conv0
<....CUT....>
2018-02-15 09:29:24,737 - 205 - DEBUG - DEBUG_CAFFE_KEY_VALUE_PRINT: + conv5/dw : conv5/dw/relu.conv5/dw
2018-02-15 09:29:24,737 - 205 - DEBUG - DEBUG_CAFFE_KEY_VALUE_PRINT: + conv8/dw : conv8/dw/relu.conv8/dw
2018-02-15 09:29:24,737 - 205 - DEBUG - DEBUG_CAFFE_KEY_VALUE_PRINT: + conv12/dw : conv12/dw/relu.conv12/dw
2018-02-15 09:29:24,737 - 205 - DEBUG - DEBUG_CAFFE_KEY_VALUE_PRINT: + conv6/dw : conv6/dw/relu.conv6/dw
2018-02-15 09:29:24,737 - 205 - DEBUG - DEBUG_CAFFE_KEY_VALUE_PRINT: + conv15_2 : conv15_2/relu.conv15_2
2018-02-15 09:29:24,738 - 205 - DEBUG - DEBUG_CAFFE_KEY_VALUE_PRINT: + conv14_1 : conv14_1/relu.conv14_1
2018-02-15 09:29:24,738 - 205 - DEBUG - DEBUG_CAFFE_KEY_VALUE_PRINT: + conv14_2 : conv14_2/relu.conv14_2
ERROR_CAFFE_LAYER_TYPE_NOT_SUPPORTED: Cannot resolve conv11_mbox_priorbox layer of type PRIORBOX which is not yet supported by this conversion script.