IOError: [Errno 2] No such file or directory: 'output/Conv_bn_moving_mean.dat'
corleonechensiyu opened this issue · comments
I1228 21:56:35.993526 22146 net.cpp:228] data_input_0_split does not need backward computation.
I1228 21:56:35.993530 22146 net.cpp:228] input does not need backward computation.
I1228 21:56:35.993532 22146 net.cpp:270] This network produces output detection_out
I1228 21:56:35.993688 22146 net.cpp:283] Network initialization done.
Conv
conv
Conv/bn
conv
Traceback (most recent call last):
File "load_caffe_weights.py", line 82, in
load_data(net_deploy)
File "load_caffe_weights.py", line 29, in load_data
net.params[key][0].data[...] = load_weights(prefix + '_moving_mean.dat')
File "load_caffe_weights.py", line 15, in load_weights
weights = np.fromfile(path, dtype=np.float32)
IOError: [Errno 2] No such file or directory: 'output/Conv_bn_moving_mean.dat'
i solved it , :-)
How did you solve it??
i solved it , :-)
can you share the methold to resolve this problem? thx~
i solved it , :-)
can you share the methold to resolve this problem? thx~
#==========SSD layers===========
layer {
name: "conv_13/expand_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "conv_13/expand"
top: "conv_13/expand_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 576
bias_term: false
pad: 1
kernel_size: 3
group: 576
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv_13/expand_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv_13/expand_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc/depthwise"
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: "conv_13/expand_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc/depthwise"
}
layer {
name: "conv_13/expand_mbox_loc"
type: "Convolution"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 12
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv_13/expand_mbox_loc_perm"
type: "Permute"
bottom: "conv_13/expand_mbox_loc"
top: "conv_13/expand_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv_13/expand_mbox_loc_flat"
type: "Flatten"
bottom: "conv_13/expand_mbox_loc_perm"
top: "conv_13/expand_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv_13/expand_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "conv_13/expand"
top: "conv_13/expand_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 576
bias_term: false
pad: 1
kernel_size: 3
group: 576
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv_13/expand_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv_13/expand_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf/depthwise"
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: "conv_13/expand_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf/depthwise"
}
layer {
name: "conv_13/expand_mbox_conf"
type: "Convolution"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 273
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv_13/expand_mbox_conf_perm"
type: "Permute"
bottom: "conv_13/expand_mbox_conf"
top: "conv_13/expand_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv_13/expand_mbox_conf_flat"
type: "Flatten"
bottom: "conv_13/expand_mbox_conf_perm"
top: "conv_13/expand_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv_13/expand_mbox_priorbox"
type: "PriorBox"
bottom: "conv_13/expand"
bottom: "data"
top: "conv_13/expand_mbox_priorbox"
prior_box_param {
min_size: 60.0
aspect_ratio: 2.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "Conv_1_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "Conv_1"
top: "Conv_1_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1280
bias_term: false
pad: 1
kernel_size: 3
group: 1280
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "Conv_1_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Conv_1_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc/depthwise"
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: "Conv_1_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc/depthwise"
}
layer {
name: "Conv_1_mbox_loc"
type: "Convolution"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "Conv_1_mbox_loc_perm"
type: "Permute"
bottom: "Conv_1_mbox_loc"
top: "Conv_1_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "Conv_1_mbox_loc_flat"
type: "Flatten"
bottom: "Conv_1_mbox_loc_perm"
top: "Conv_1_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "Conv_1_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "Conv_1"
top: "Conv_1_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1280
bias_term: false
pad: 1
kernel_size: 3
group: 1280
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "Conv_1_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Conv_1_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf/depthwise"
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: "Conv_1_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf/depthwise"
}
layer {
name: "Conv_1_mbox_conf"
type: "Convolution"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "Conv_1_mbox_conf_perm"
type: "Permute"
bottom: "Conv_1_mbox_conf"
top: "Conv_1_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "Conv_1_mbox_conf_flat"
type: "Flatten"
bottom: "Conv_1_mbox_conf_perm"
top: "Conv_1_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "Conv_1_mbox_priorbox"
type: "PriorBox"
bottom: "Conv_1"
bottom: "data"
top: "Conv_1_mbox_priorbox"
prior_box_param {
min_size: 105.0
max_size: 150.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_2_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_2"
top: "layer_19_2_2_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_2_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_2_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc/depthwise"
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: "layer_19_2_2_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_2_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_2_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_2_mbox_loc"
top: "layer_19_2_2_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_2_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_2_mbox_loc_perm"
top: "layer_19_2_2_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_2_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_2"
top: "layer_19_2_2_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_2_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_2_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf/depthwise"
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: "layer_19_2_2_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_2_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_2_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_2_mbox_conf"
top: "layer_19_2_2_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_2_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_2_mbox_conf_perm"
top: "layer_19_2_2_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_2_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_2"
bottom: "data"
top: "layer_19_2_2_mbox_priorbox"
prior_box_param {
min_size: 150.0
max_size: 195.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_3_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_3"
top: "layer_19_2_3_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_3_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_3_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc/depthwise"
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: "layer_19_2_3_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_3_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_3_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_3_mbox_loc"
top: "layer_19_2_3_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_3_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_3_mbox_loc_perm"
top: "layer_19_2_3_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_3_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_3"
top: "layer_19_2_3_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_3_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_3_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf/depthwise"
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: "layer_19_2_3_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_3_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_3_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_3_mbox_conf"
top: "layer_19_2_3_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_3_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_3_mbox_conf_perm"
top: "layer_19_2_3_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_3_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_3"
bottom: "data"
top: "layer_19_2_3_mbox_priorbox"
prior_box_param {
min_size: 195.0
max_size: 240.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_4_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_4"
top: "layer_19_2_4_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_4_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_4_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc/depthwise"
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: "layer_19_2_4_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_4_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_4_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_4_mbox_loc"
top: "layer_19_2_4_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_4_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_4_mbox_loc_perm"
top: "layer_19_2_4_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_4_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_4"
top: "layer_19_2_4_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_4_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_4_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf/depthwise"
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: "layer_19_2_4_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_4_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_4_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_4_mbox_conf"
top: "layer_19_2_4_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_4_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_4_mbox_conf_perm"
top: "layer_19_2_4_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_4_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_4"
bottom: "data"
top: "layer_19_2_4_mbox_priorbox"
prior_box_param {
min_size: 240.0
max_size: 285.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_5_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_5"
top: "layer_19_2_5_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_5_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_5_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc/depthwise"
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: "layer_19_2_5_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_5_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_5_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_5_mbox_loc"
top: "layer_19_2_5_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_5_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_5_mbox_loc_perm"
top: "layer_19_2_5_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_5_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_5"
top: "layer_19_2_5_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_5_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_5_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf/depthwise"
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: "layer_19_2_5_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_5_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_5_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_5_mbox_conf"
top: "layer_19_2_5_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_5_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_5_mbox_conf_perm"
top: "layer_19_2_5_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_5_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_5"
bottom: "data"
top: "layer_19_2_5_mbox_priorbox"
prior_box_param {
min_size: 285.0
max_size: 300.0
aspect_ratio: 2.0
aspect_ratio: 3.0
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: "conv_13/expand_mbox_loc_flat"
bottom: "Conv_1_mbox_loc_flat"
bottom: "layer_19_2_2_mbox_loc_flat"
bottom: "layer_19_2_3_mbox_loc_flat"
bottom: "layer_19_2_4_mbox_loc_flat"
bottom: "layer_19_2_5_mbox_loc_flat"
top: "mbox_loc"
concat_param {
axis: 1
}
}
layer {
name: "mbox_conf"
type: "Concat"
bottom: "conv_13/expand_mbox_conf_flat"
bottom: "Conv_1_mbox_conf_flat"
bottom: "layer_19_2_2_mbox_conf_flat"
bottom: "layer_19_2_3_mbox_conf_flat"
bottom: "layer_19_2_4_mbox_conf_flat"
bottom: "layer_19_2_5_mbox_conf_flat"
top: "mbox_conf"
concat_param {
axis: 1
}
}
layer {
name: "mbox_priorbox"
type: "Concat"
bottom: "conv_13/expand_mbox_priorbox"
bottom: "Conv_1_mbox_priorbox"
bottom: "layer_19_2_2_mbox_priorbox"
bottom: "layer_19_2_3_mbox_priorbox"
bottom: "layer_19_2_4_mbox_priorbox"
bottom: "layer_19_2_5_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: 91
}
}
}
layer {
name: "mbox_conf_sigmoid"
type: "Sigmoid"
bottom: "mbox_conf_reshape"
top: "mbox_conf_sigmoid"
}
layer {
name: "mbox_conf_flatten"
type: "Flatten"
bottom: "mbox_conf_sigmoid"
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: 91
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: 0.35
}
}
用ssdlite->voc里面的deploy.prototxt文件，修改里面的分类为91，以及相应的num_output，然后拷贝到ssdlite文件里，运行相应的py文件就行
i solved it , :-)
can you share the methold to resolve this problem? thx~
#==========SSD layers===========
layer {
name: "conv_13/expand_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "conv_13/expand"
top: "conv_13/expand_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 576
bias_term: false
pad: 1
kernel_size: 3
group: 576
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv_13/expand_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv_13/expand_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc/depthwise"
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: "conv_13/expand_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc/depthwise"
}
layer {
name: "conv_13/expand_mbox_loc"
type: "Convolution"
bottom: "conv_13/expand_mbox_loc/depthwise"
top: "conv_13/expand_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 12
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv_13/expand_mbox_loc_perm"
type: "Permute"
bottom: "conv_13/expand_mbox_loc"
top: "conv_13/expand_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv_13/expand_mbox_loc_flat"
type: "Flatten"
bottom: "conv_13/expand_mbox_loc_perm"
top: "conv_13/expand_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv_13/expand_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "conv_13/expand"
top: "conv_13/expand_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 576
bias_term: false
pad: 1
kernel_size: 3
group: 576
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv_13/expand_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv_13/expand_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf/depthwise"
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: "conv_13/expand_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf/depthwise"
}
layer {
name: "conv_13/expand_mbox_conf"
type: "Convolution"
bottom: "conv_13/expand_mbox_conf/depthwise"
top: "conv_13/expand_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 273
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv_13/expand_mbox_conf_perm"
type: "Permute"
bottom: "conv_13/expand_mbox_conf"
top: "conv_13/expand_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "conv_13/expand_mbox_conf_flat"
type: "Flatten"
bottom: "conv_13/expand_mbox_conf_perm"
top: "conv_13/expand_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "conv_13/expand_mbox_priorbox"
type: "PriorBox"
bottom: "conv_13/expand"
bottom: "data"
top: "conv_13/expand_mbox_priorbox"
prior_box_param {
min_size: 60.0
aspect_ratio: 2.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "Conv_1_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "Conv_1"
top: "Conv_1_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1280
bias_term: false
pad: 1
kernel_size: 3
group: 1280
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "Conv_1_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Conv_1_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc/depthwise"
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: "Conv_1_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc/depthwise"
}
layer {
name: "Conv_1_mbox_loc"
type: "Convolution"
bottom: "Conv_1_mbox_loc/depthwise"
top: "Conv_1_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "Conv_1_mbox_loc_perm"
type: "Permute"
bottom: "Conv_1_mbox_loc"
top: "Conv_1_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "Conv_1_mbox_loc_flat"
type: "Flatten"
bottom: "Conv_1_mbox_loc_perm"
top: "Conv_1_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "Conv_1_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "Conv_1"
top: "Conv_1_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 1280
bias_term: false
pad: 1
kernel_size: 3
group: 1280
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "Conv_1_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Conv_1_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf/depthwise"
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: "Conv_1_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf/depthwise"
}
layer {
name: "Conv_1_mbox_conf"
type: "Convolution"
bottom: "Conv_1_mbox_conf/depthwise"
top: "Conv_1_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "Conv_1_mbox_conf_perm"
type: "Permute"
bottom: "Conv_1_mbox_conf"
top: "Conv_1_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "Conv_1_mbox_conf_flat"
type: "Flatten"
bottom: "Conv_1_mbox_conf_perm"
top: "Conv_1_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "Conv_1_mbox_priorbox"
type: "PriorBox"
bottom: "Conv_1"
bottom: "data"
top: "Conv_1_mbox_priorbox"
prior_box_param {
min_size: 105.0
max_size: 150.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_2_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_2"
top: "layer_19_2_2_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_2_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_2_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc/depthwise"
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: "layer_19_2_2_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_2_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_2_mbox_loc/depthwise"
top: "layer_19_2_2_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_2_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_2_mbox_loc"
top: "layer_19_2_2_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_2_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_2_mbox_loc_perm"
top: "layer_19_2_2_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_2_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_2"
top: "layer_19_2_2_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_2_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_2_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf/depthwise"
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: "layer_19_2_2_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_2_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_2_mbox_conf/depthwise"
top: "layer_19_2_2_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_2_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_2_mbox_conf"
top: "layer_19_2_2_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_2_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_2_mbox_conf_perm"
top: "layer_19_2_2_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_2_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_2"
bottom: "data"
top: "layer_19_2_2_mbox_priorbox"
prior_box_param {
min_size: 150.0
max_size: 195.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_3_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_3"
top: "layer_19_2_3_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_3_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_3_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc/depthwise"
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: "layer_19_2_3_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_3_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_3_mbox_loc/depthwise"
top: "layer_19_2_3_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_3_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_3_mbox_loc"
top: "layer_19_2_3_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_3_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_3_mbox_loc_perm"
top: "layer_19_2_3_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_3_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_3"
top: "layer_19_2_3_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_3_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_3_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf/depthwise"
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: "layer_19_2_3_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_3_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_3_mbox_conf/depthwise"
top: "layer_19_2_3_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_3_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_3_mbox_conf"
top: "layer_19_2_3_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_3_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_3_mbox_conf_perm"
top: "layer_19_2_3_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_3_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_3"
bottom: "data"
top: "layer_19_2_3_mbox_priorbox"
prior_box_param {
min_size: 195.0
max_size: 240.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_4_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_4"
top: "layer_19_2_4_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_4_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_4_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc/depthwise"
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: "layer_19_2_4_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_4_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_4_mbox_loc/depthwise"
top: "layer_19_2_4_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_4_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_4_mbox_loc"
top: "layer_19_2_4_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_4_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_4_mbox_loc_perm"
top: "layer_19_2_4_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_4_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_4"
top: "layer_19_2_4_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_4_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_4_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf/depthwise"
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: "layer_19_2_4_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_4_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_4_mbox_conf/depthwise"
top: "layer_19_2_4_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_4_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_4_mbox_conf"
top: "layer_19_2_4_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_4_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_4_mbox_conf_perm"
top: "layer_19_2_4_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_4_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_4"
bottom: "data"
top: "layer_19_2_4_mbox_priorbox"
prior_box_param {
min_size: 240.0
max_size: 285.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.1
variance: 0.1
variance: 0.2
variance: 0.2
offset: 0.5
}
}
layer {
name: "layer_19_2_5_mbox_loc/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_5"
top: "layer_19_2_5_mbox_loc/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_5_mbox_loc/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_5_mbox_loc/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc/depthwise"
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: "layer_19_2_5_mbox_loc/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc/depthwise"
}
layer {
name: "layer_19_2_5_mbox_loc"
type: "Convolution"
bottom: "layer_19_2_5_mbox_loc/depthwise"
top: "layer_19_2_5_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_5_mbox_loc_perm"
type: "Permute"
bottom: "layer_19_2_5_mbox_loc"
top: "layer_19_2_5_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_5_mbox_loc_flat"
type: "Flatten"
bottom: "layer_19_2_5_mbox_loc_perm"
top: "layer_19_2_5_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_5_mbox_conf/depthwise"
type: "DepthwiseConvolution"
bottom: "layer_19_2_5"
top: "layer_19_2_5_mbox_conf/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "layer_19_2_5_mbox_conf/depthwise/bn"
type: "BatchNorm"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf/depthwise"
batch_norm_param {
eps: 0.001
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "layer_19_2_5_mbox_conf/depthwise/scale"
type: "Scale"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf/depthwise"
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: "layer_19_2_5_mbox_conf/depthwise/relu"
type: "ReLU6"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf/depthwise"
}
layer {
name: "layer_19_2_5_mbox_conf"
type: "Convolution"
bottom: "layer_19_2_5_mbox_conf/depthwise"
top: "layer_19_2_5_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 546
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_19_2_5_mbox_conf_perm"
type: "Permute"
bottom: "layer_19_2_5_mbox_conf"
top: "layer_19_2_5_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "layer_19_2_5_mbox_conf_flat"
type: "Flatten"
bottom: "layer_19_2_5_mbox_conf_perm"
top: "layer_19_2_5_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "layer_19_2_5_mbox_priorbox"
type: "PriorBox"
bottom: "layer_19_2_5"
bottom: "data"
top: "layer_19_2_5_mbox_priorbox"
prior_box_param {
min_size: 285.0
max_size: 300.0
aspect_ratio: 2.0
aspect_ratio: 3.0
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: "conv_13/expand_mbox_loc_flat"
bottom: "Conv_1_mbox_loc_flat"
bottom: "layer_19_2_2_mbox_loc_flat"
bottom: "layer_19_2_3_mbox_loc_flat"
bottom: "layer_19_2_4_mbox_loc_flat"
bottom: "layer_19_2_5_mbox_loc_flat"
top: "mbox_loc"
concat_param {
axis: 1
}
}
layer {
name: "mbox_conf"
type: "Concat"
bottom: "conv_13/expand_mbox_conf_flat"
bottom: "Conv_1_mbox_conf_flat"
bottom: "layer_19_2_2_mbox_conf_flat"
bottom: "layer_19_2_3_mbox_conf_flat"
bottom: "layer_19_2_4_mbox_conf_flat"
bottom: "layer_19_2_5_mbox_conf_flat"
top: "mbox_conf"
concat_param {
axis: 1
}
}
layer {
name: "mbox_priorbox"
type: "Concat"
bottom: "conv_13/expand_mbox_priorbox"
bottom: "Conv_1_mbox_priorbox"
bottom: "layer_19_2_2_mbox_priorbox"
bottom: "layer_19_2_3_mbox_priorbox"
bottom: "layer_19_2_4_mbox_priorbox"
bottom: "layer_19_2_5_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: 91
}
}
}
layer {
name: "mbox_conf_sigmoid"
type: "Sigmoid"
bottom: "mbox_conf_reshape"
top: "mbox_conf_sigmoid"
}
layer {
name: "mbox_conf_flatten"
type: "Flatten"
bottom: "mbox_conf_sigmoid"
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: 91
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: 0.35
}
}
用ssdlite->voc里面的deploy.prototxt文件，修改里面的分类为91，以及相应的num_output，然后拷贝到ssdlite文件里，运行相应的py文件就行
thx a lot~
用ssdlite->voc里面的deploy.prototxt文件，修改里面的分类为91，以及相应的num_output，然后拷贝到ssdlite文件里，运行相应的py文件就行
thx a lot~
emmm, i change the num_output and num_class=91. Maybe i make wrong and i still can not run. Could you please give me a right deploy.prototxt
老哥，我改了不行啊，能不能发deploy.prototxt带带我
用ssdlite->voc里面的deploy.prototxt文件，修改里面的分类为91，以及相应的num_output，然后拷贝到ssdlite文件里，运行相应的py文件就行
thx a lot~
emmm, i change the num_output and num_class=91. Maybe i make wrong and i still can not run. Could you please give me a right deploy.prototxt
老哥，我改了不行啊，能不能发deploy.prototxt带带我
deploy.prototxt我贴出来了，修改相应的layer_x_x_x_mbox_conf和layer_x_x_x_mbox_loc层的num_output ，你对照看一下
用ssdlite->voc里面的deploy.prototxt文件，修改里面的分类为91，以及相应的num_output，然后拷贝到ssdlite文件里，运行相应的py文件就行
thx a lot~
emmm, i change the num_output and num_class=91. Maybe i make wrong and i still can not run. Could you please give me a right deploy.prototxt
老哥，我改了不行啊，能不能发deploy.prototxt带带我deploy.prototxt我贴出来了，修改相应的layer_x_x_x_mbox_conf和layer_x_x_x_mbox_loc层的num_output ，你对照看一下
感谢，我明白怎么弄了