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October 6, 2016 05:54
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name: "VGG_VOC0712_SSD_300x300_no_dilation_train" | |
layer { | |
name: "data" | |
type: "AnnotatedData" | |
top: "data" | |
top: "label" | |
include { | |
phase: TRAIN | |
} | |
transform_param { | |
mirror: true | |
mean_value: 104 | |
mean_value: 117 | |
mean_value: 123 | |
resize_param { | |
prob: 1 | |
resize_mode: WARP | |
height: 300 | |
width: 300 | |
interp_mode: LINEAR | |
interp_mode: AREA | |
interp_mode: NEAREST | |
interp_mode: CUBIC | |
interp_mode: LANCZOS4 | |
} | |
emit_constraint { | |
emit_type: CENTER | |
} | |
} | |
data_param { | |
source: "examples/VOC0712/VOC0712_trainval_lmdb" | |
batch_size: 16 | |
backend: LMDB | |
} | |
annotated_data_param { | |
batch_sampler { | |
max_sample: 1 | |
max_trials: 1 | |
} | |
batch_sampler { | |
sampler { | |
min_scale: 0.3 | |
max_scale: 1.0 | |
min_aspect_ratio: 0.5 | |
max_aspect_ratio: 2.0 | |
} | |
sample_constraint { | |
min_jaccard_overlap: 0.1 | |
} | |
max_sample: 1 | |
max_trials: 50 | |
} | |
batch_sampler { | |
sampler { | |
min_scale: 0.3 | |
max_scale: 1.0 | |
min_aspect_ratio: 0.5 | |
max_aspect_ratio: 2.0 | |
} | |
sample_constraint { | |
min_jaccard_overlap: 0.3 | |
} | |
max_sample: 1 | |
max_trials: 50 | |
} | |
batch_sampler { | |
sampler { | |
min_scale: 0.3 | |
max_scale: 1.0 | |
min_aspect_ratio: 0.5 | |
max_aspect_ratio: 2.0 | |
} | |
sample_constraint { | |
min_jaccard_overlap: 0.5 | |
} | |
max_sample: 1 | |
max_trials: 50 | |
} | |
batch_sampler { | |
sampler { | |
min_scale: 0.3 | |
max_scale: 1.0 | |
min_aspect_ratio: 0.5 | |
max_aspect_ratio: 2.0 | |
} | |
sample_constraint { | |
min_jaccard_overlap: 0.7 | |
} | |
max_sample: 1 | |
max_trials: 50 | |
} | |
batch_sampler { | |
sampler { | |
min_scale: 0.3 | |
max_scale: 1.0 | |
min_aspect_ratio: 0.5 | |
max_aspect_ratio: 2.0 | |
} | |
sample_constraint { | |
min_jaccard_overlap: 0.9 | |
} | |
max_sample: 1 | |
max_trials: 50 | |
} | |
batch_sampler { | |
sampler { | |
min_scale: 0.3 | |
max_scale: 1.0 | |
min_aspect_ratio: 0.5 | |
max_aspect_ratio: 2.0 | |
} | |
sample_constraint { | |
max_jaccard_overlap: 1.0 | |
} | |
max_sample: 1 | |
max_trials: 50 | |
} | |
label_map_file: "data/VOC0712/labelmap_voc.prototxt" | |
} | |
} | |
layer { | |
name: "conv1_1" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1_1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1_1" | |
type: "ReLU" | |
bottom: "conv1_1" | |
top: "conv1_1" | |
} | |
layer { | |
name: "conv1_2" | |
type: "Convolution" | |
bottom: "conv1_1" | |
top: "conv1_2" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1_2" | |
type: "ReLU" | |
bottom: "conv1_2" | |
top: "conv1_2" | |
} | |
layer { | |
name: "pool1" | |
type: "Pooling" | |
bottom: "conv1_2" | |
top: "pool1" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "conv2_1" | |
type: "Convolution" | |
bottom: "pool1" | |
top: "conv2_1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_1" | |
type: "ReLU" | |
bottom: "conv2_1" | |
top: "conv2_1" | |
} | |
layer { | |
name: "conv2_2" | |
type: "Convolution" | |
bottom: "conv2_1" | |
top: "conv2_2" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_2" | |
type: "ReLU" | |
bottom: "conv2_2" | |
top: "conv2_2" | |
} | |
layer { | |
name: "pool2" | |
type: "Pooling" | |
bottom: "conv2_2" | |
top: "pool2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "conv3_1" | |
type: "Convolution" | |
bottom: "pool2" | |
top: "conv3_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_1" | |
type: "ReLU" | |
bottom: "conv3_1" | |
top: "conv3_1" | |
} | |
layer { | |
name: "conv3_2" | |
type: "Convolution" | |
bottom: "conv3_1" | |
top: "conv3_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 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_2" | |
type: "ReLU" | |
bottom: "conv3_2" | |
top: "conv3_2" | |
} | |
layer { | |
name: "conv3_3" | |
type: "Convolution" | |
bottom: "conv3_2" | |
top: "conv3_3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_3" | |
type: "ReLU" | |
bottom: "conv3_3" | |
top: "conv3_3" | |
} | |
layer { | |
name: "pool3" | |
type: "Pooling" | |
bottom: "conv3_3" | |
top: "pool3" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "conv4_1" | |
type: "Convolution" | |
bottom: "pool3" | |
top: "conv4_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_1" | |
type: "ReLU" | |
bottom: "conv4_1" | |
top: "conv4_1" | |
} | |
layer { | |
name: "conv4_2" | |
type: "Convolution" | |
bottom: "conv4_1" | |
top: "conv4_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 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_2" | |
type: "ReLU" | |
bottom: "conv4_2" | |
top: "conv4_2" | |
} | |
layer { | |
name: "conv4_3" | |
type: "Convolution" | |
bottom: "conv4_2" | |
top: "conv4_3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_3" | |
type: "ReLU" | |
bottom: "conv4_3" | |
top: "conv4_3" | |
} | |
layer { | |
name: "pool4" | |
type: "Pooling" | |
bottom: "conv4_3" | |
top: "pool4" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "conv5_1" | |
type: "Convolution" | |
bottom: "pool4" | |
top: "conv5_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_1" | |
type: "ReLU" | |
bottom: "conv5_1" | |
top: "conv5_1" | |
} | |
layer { | |
name: "conv5_2" | |
type: "Convolution" | |
bottom: "conv5_1" | |
top: "conv5_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 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_2" | |
type: "ReLU" | |
bottom: "conv5_2" | |
top: "conv5_2" | |
} | |
layer { | |
name: "conv5_3" | |
type: "Convolution" | |
bottom: "conv5_2" | |
top: "conv5_3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_3" | |
type: "ReLU" | |
bottom: "conv5_3" | |
top: "conv5_3" | |
} | |
layer { | |
name: "pool5" | |
type: "Pooling" | |
bottom: "conv5_3" | |
top: "pool5" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "fc6" | |
type: "Convolution" | |
bottom: "pool5" | |
top: "fc6" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 1024 | |
pad: 3 | |
kernel_size: 3 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
dilation: 3 | |
} | |
} | |
layer { | |
name: "relu6" | |
type: "ReLU" | |
bottom: "fc6" | |
top: "fc6" | |
} | |
layer { | |
name: "fc7" | |
type: "Convolution" | |
bottom: "fc6" | |
top: "fc7" | |
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: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu7" | |
type: "ReLU" | |
bottom: "fc7" | |
top: "fc7" | |
} | |
layer { | |
name: "conv6_1" | |
type: "Convolution" | |
bottom: "fc7" | |
top: "conv6_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv6_1_relu" | |
type: "ReLU" | |
bottom: "conv6_1" | |
top: "conv6_1" | |
} | |
layer { | |
name: "conv6_2" | |
type: "Convolution" | |
bottom: "conv6_1" | |
top: "conv6_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: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv6_2_relu" | |
type: "ReLU" | |
bottom: "conv6_2" | |
top: "conv6_2" | |
} | |
layer { | |
name: "conv7_1" | |
type: "Convolution" | |
bottom: "conv6_2" | |
top: "conv7_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv7_1_relu" | |
type: "ReLU" | |
bottom: "conv7_1" | |
top: "conv7_1" | |
} | |
layer { | |
name: "conv7_2" | |
type: "Convolution" | |
bottom: "conv7_1" | |
top: "conv7_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: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv7_2_relu" | |
type: "ReLU" | |
bottom: "conv7_2" | |
top: "conv7_2" | |
} | |
layer { | |
name: "conv8_1" | |
type: "Convolution" | |
bottom: "conv7_2" | |
top: "conv8_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv8_1_relu" | |
type: "ReLU" | |
bottom: "conv8_1" | |
top: "conv8_1" | |
} | |
layer { | |
name: "conv8_2" | |
type: "Convolution" | |
bottom: "conv8_1" | |
top: "conv8_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: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv8_2_relu" | |
type: "ReLU" | |
bottom: "conv8_2" | |
top: "conv8_2" | |
} | |
layer { | |
name: "pool6" | |
type: "Pooling" | |
bottom: "conv8_2" | |
top: "pool6" | |
pooling_param { | |
pool: AVE | |
global_pooling: true | |
} | |
} | |
layer { | |
name: "conv4_3_norm" | |
type: "Normalize" | |
bottom: "conv4_3" | |
top: "conv4_3_norm" | |
norm_param { | |
across_spatial: false | |
scale_filler { | |
type: "constant" | |
value: 20 | |
} | |
channel_shared: false | |
} | |
} | |
layer { | |
name: "conv4_3_norm_mbox_loc" | |
type: "Convolution" | |
bottom: "conv4_3_norm" | |
top: "conv4_3_norm_mbox_loc" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 12 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv4_3_norm_mbox_loc_perm" | |
type: "Permute" | |
bottom: "conv4_3_norm_mbox_loc" | |
top: "conv4_3_norm_mbox_loc_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv4_3_norm_mbox_loc_flat" | |
type: "Flatten" | |
bottom: "conv4_3_norm_mbox_loc_perm" | |
top: "conv4_3_norm_mbox_loc_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv4_3_norm_mbox_conf" | |
type: "Convolution" | |
bottom: "conv4_3_norm" | |
top: "conv4_3_norm_mbox_conf" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 63 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv4_3_norm_mbox_conf_perm" | |
type: "Permute" | |
bottom: "conv4_3_norm_mbox_conf" | |
top: "conv4_3_norm_mbox_conf_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv4_3_norm_mbox_conf_flat" | |
type: "Flatten" | |
bottom: "conv4_3_norm_mbox_conf_perm" | |
top: "conv4_3_norm_mbox_conf_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv4_3_norm_mbox_priorbox" | |
type: "PriorBox" | |
bottom: "conv4_3_norm" | |
bottom: "data" | |
top: "conv4_3_norm_mbox_priorbox" | |
prior_box_param { | |
min_size: 30.0 | |
aspect_ratio: 2 | |
flip: true | |
clip: true | |
variance: 0.1 | |
variance: 0.1 | |
variance: 0.2 | |
variance: 0.2 | |
} | |
} | |
layer { | |
name: "fc7_mbox_loc" | |
type: "Convolution" | |
bottom: "fc7" | |
top: "fc7_mbox_loc" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "fc7_mbox_loc_perm" | |
type: "Permute" | |
bottom: "fc7_mbox_loc" | |
top: "fc7_mbox_loc_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "fc7_mbox_loc_flat" | |
type: "Flatten" | |
bottom: "fc7_mbox_loc_perm" | |
top: "fc7_mbox_loc_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "fc7_mbox_conf" | |
type: "Convolution" | |
bottom: "fc7" | |
top: "fc7_mbox_conf" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 126 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "fc7_mbox_conf_perm" | |
type: "Permute" | |
bottom: "fc7_mbox_conf" | |
top: "fc7_mbox_conf_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "fc7_mbox_conf_flat" | |
type: "Flatten" | |
bottom: "fc7_mbox_conf_perm" | |
top: "fc7_mbox_conf_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "fc7_mbox_priorbox" | |
type: "PriorBox" | |
bottom: "fc7" | |
bottom: "data" | |
top: "fc7_mbox_priorbox" | |
prior_box_param { | |
min_size: 60.0 | |
max_size: 114.0 | |
aspect_ratio: 2 | |
aspect_ratio: 3 | |
flip: true | |
clip: true | |
variance: 0.1 | |
variance: 0.1 | |
variance: 0.2 | |
variance: 0.2 | |
} | |
} | |
layer { | |
name: "conv6_2_mbox_loc" | |
type: "Convolution" | |
bottom: "conv6_2" | |
top: "conv6_2_mbox_loc" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv6_2_mbox_loc_perm" | |
type: "Permute" | |
bottom: "conv6_2_mbox_loc" | |
top: "conv6_2_mbox_loc_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv6_2_mbox_loc_flat" | |
type: "Flatten" | |
bottom: "conv6_2_mbox_loc_perm" | |
top: "conv6_2_mbox_loc_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv6_2_mbox_conf" | |
type: "Convolution" | |
bottom: "conv6_2" | |
top: "conv6_2_mbox_conf" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 126 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv6_2_mbox_conf_perm" | |
type: "Permute" | |
bottom: "conv6_2_mbox_conf" | |
top: "conv6_2_mbox_conf_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv6_2_mbox_conf_flat" | |
type: "Flatten" | |
bottom: "conv6_2_mbox_conf_perm" | |
top: "conv6_2_mbox_conf_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv6_2_mbox_priorbox" | |
type: "PriorBox" | |
bottom: "conv6_2" | |
bottom: "data" | |
top: "conv6_2_mbox_priorbox" | |
prior_box_param { | |
min_size: 114.0 | |
max_size: 168.0 | |
aspect_ratio: 2 | |
aspect_ratio: 3 | |
flip: true | |
clip: true | |
variance: 0.1 | |
variance: 0.1 | |
variance: 0.2 | |
variance: 0.2 | |
} | |
} | |
layer { | |
name: "conv7_2_mbox_loc" | |
type: "Convolution" | |
bottom: "conv7_2" | |
top: "conv7_2_mbox_loc" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv7_2_mbox_loc_perm" | |
type: "Permute" | |
bottom: "conv7_2_mbox_loc" | |
top: "conv7_2_mbox_loc_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv7_2_mbox_loc_flat" | |
type: "Flatten" | |
bottom: "conv7_2_mbox_loc_perm" | |
top: "conv7_2_mbox_loc_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv7_2_mbox_conf" | |
type: "Convolution" | |
bottom: "conv7_2" | |
top: "conv7_2_mbox_conf" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 126 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv7_2_mbox_conf_perm" | |
type: "Permute" | |
bottom: "conv7_2_mbox_conf" | |
top: "conv7_2_mbox_conf_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv7_2_mbox_conf_flat" | |
type: "Flatten" | |
bottom: "conv7_2_mbox_conf_perm" | |
top: "conv7_2_mbox_conf_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv7_2_mbox_priorbox" | |
type: "PriorBox" | |
bottom: "conv7_2" | |
bottom: "data" | |
top: "conv7_2_mbox_priorbox" | |
prior_box_param { | |
min_size: 168.0 | |
max_size: 222.0 | |
aspect_ratio: 2 | |
aspect_ratio: 3 | |
flip: true | |
clip: true | |
variance: 0.1 | |
variance: 0.1 | |
variance: 0.2 | |
variance: 0.2 | |
} | |
} | |
layer { | |
name: "conv8_2_mbox_loc" | |
type: "Convolution" | |
bottom: "conv8_2" | |
top: "conv8_2_mbox_loc" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv8_2_mbox_loc_perm" | |
type: "Permute" | |
bottom: "conv8_2_mbox_loc" | |
top: "conv8_2_mbox_loc_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv8_2_mbox_loc_flat" | |
type: "Flatten" | |
bottom: "conv8_2_mbox_loc_perm" | |
top: "conv8_2_mbox_loc_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv8_2_mbox_conf" | |
type: "Convolution" | |
bottom: "conv8_2" | |
top: "conv8_2_mbox_conf" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 126 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv8_2_mbox_conf_perm" | |
type: "Permute" | |
bottom: "conv8_2_mbox_conf" | |
top: "conv8_2_mbox_conf_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "conv8_2_mbox_conf_flat" | |
type: "Flatten" | |
bottom: "conv8_2_mbox_conf_perm" | |
top: "conv8_2_mbox_conf_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "conv8_2_mbox_priorbox" | |
type: "PriorBox" | |
bottom: "conv8_2" | |
bottom: "data" | |
top: "conv8_2_mbox_priorbox" | |
prior_box_param { | |
min_size: 222.0 | |
max_size: 276.0 | |
aspect_ratio: 2 | |
aspect_ratio: 3 | |
flip: true | |
clip: true | |
variance: 0.1 | |
variance: 0.1 | |
variance: 0.2 | |
variance: 0.2 | |
} | |
} | |
layer { | |
name: "pool6_mbox_loc" | |
type: "Convolution" | |
bottom: "pool6" | |
top: "pool6_mbox_loc" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 24 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "pool6_mbox_loc_perm" | |
type: "Permute" | |
bottom: "pool6_mbox_loc" | |
top: "pool6_mbox_loc_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "pool6_mbox_loc_flat" | |
type: "Flatten" | |
bottom: "pool6_mbox_loc_perm" | |
top: "pool6_mbox_loc_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "pool6_mbox_conf" | |
type: "Convolution" | |
bottom: "pool6" | |
top: "pool6_mbox_conf" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 126 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "pool6_mbox_conf_perm" | |
type: "Permute" | |
bottom: "pool6_mbox_conf" | |
top: "pool6_mbox_conf_perm" | |
permute_param { | |
order: 0 | |
order: 2 | |
order: 3 | |
order: 1 | |
} | |
} | |
layer { | |
name: "pool6_mbox_conf_flat" | |
type: "Flatten" | |
bottom: "pool6_mbox_conf_perm" | |
top: "pool6_mbox_conf_flat" | |
flatten_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "pool6_mbox_priorbox" | |
type: "PriorBox" | |
bottom: "pool6" | |
bottom: "data" | |
top: "pool6_mbox_priorbox" | |
prior_box_param { | |
min_size: 276.0 | |
max_size: 330.0 | |
aspect_ratio: 2 | |
aspect_ratio: 3 | |
flip: true | |
clip: true | |
variance: 0.1 | |
variance: 0.1 | |
variance: 0.2 | |
variance: 0.2 | |
} | |
} | |
layer { | |
name: "mbox_loc" | |
type: "Concat" | |
bottom: "conv4_3_norm_mbox_loc_flat" | |
bottom: "fc7_mbox_loc_flat" | |
bottom: "conv6_2_mbox_loc_flat" | |
bottom: "conv7_2_mbox_loc_flat" | |
bottom: "conv8_2_mbox_loc_flat" | |
bottom: "pool6_mbox_loc_flat" | |
top: "mbox_loc" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "mbox_conf" | |
type: "Concat" | |
bottom: "conv4_3_norm_mbox_conf_flat" | |
bottom: "fc7_mbox_conf_flat" | |
bottom: "conv6_2_mbox_conf_flat" | |
bottom: "conv7_2_mbox_conf_flat" | |
bottom: "conv8_2_mbox_conf_flat" | |
bottom: "pool6_mbox_conf_flat" | |
top: "mbox_conf" | |
concat_param { | |
axis: 1 | |
} | |
} | |
layer { | |
name: "mbox_priorbox" | |
type: "Concat" | |
bottom: "conv4_3_norm_mbox_priorbox" | |
bottom: "fc7_mbox_priorbox" | |
bottom: "conv6_2_mbox_priorbox" | |
bottom: "conv7_2_mbox_priorbox" | |
bottom: "conv8_2_mbox_priorbox" | |
bottom: "pool6_mbox_priorbox" | |
top: "mbox_priorbox" | |
concat_param { | |
axis: 2 | |
} | |
} | |
layer { | |
name: "mbox_loss" | |
type: "MultiBoxLoss" | |
bottom: "mbox_loc" | |
bottom: "mbox_conf" | |
bottom: "mbox_priorbox" | |
bottom: "label" | |
top: "mbox_loss" | |
include { | |
phase: TRAIN | |
} | |
propagate_down: true | |
propagate_down: true | |
propagate_down: false | |
propagate_down: false | |
loss_param { | |
normalization: VALID | |
} | |
multibox_loss_param { | |
loc_loss_type: SMOOTH_L1 | |
conf_loss_type: SOFTMAX | |
loc_weight: 1.0 | |
num_classes: 21 | |
share_location: true | |
match_type: PER_PREDICTION | |
overlap_threshold: 0.5 | |
use_prior_for_matching: true | |
background_label_id: 0 | |
use_difficult_gt: true | |
do_neg_mining: true | |
neg_pos_ratio: 3.0 | |
neg_overlap: 0.5 | |
code_type: CENTER_SIZE | |
} | |
} | |
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