[dnn] Ability to load FSSD pre trained caffe model with "Interp" layer #10985
Description
I'm trying to load a FSSD: Feature Fusion Single Shot Multibox Detector pre trained caffe model.
But I'm getting the following error:
[libprotobuf ERROR /io/opencv/3rdparty/protobuf/src/google/protobuf/text_format.cc:298] Error parsing text-format opencv_caffe.NetParameter: 751:16: Message type "opencv_caffe.LayerParameter" has no field named "interp_param".
OpenCV Error: Unspecified error (FAILED: ReadProtoFromTextFile(param_file, param). Failed to parse NetParameter file: /zoo/caffe-zoo/FSSD_512_COCO/deploy.prototxt) in ReadNetParamsFromTextFileOrDie, file /io/opencv/modules/dnn/src/caffe/caffe_io.cpp, line 1145
Traceback (most recent call last):
File "vigilante/play.py", line 86, in <module>
prototxt='/zoo/caffe-zoo/FSSD_512_COCO/deploy.prototxt')
File "/usr/src/app/vigilante/object_detector.py", line 192, in __init__
self.net = cv2.dnn.readNetFromCaffe(prototxt, caffemodel)
cv2.error: /io/opencv/modules/dnn/src/caffe/caffe_io.cpp:1145: error: (-2) FAILED: ReadProtoFromTextFile(param_file, param). Failed to parse NetParameter file: /zoo/caffe-zoo/FSSD_512_COCO/deploy.prototxt in function ReadNetParamsFromTextFileOrDie
deploy.prototxt
name: "VGG_COCO_SSD_FPN_NO33_WOP512x512_deploy"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 512
dim: 512
}
layer {
name: "conv1_1"
type: "Convolution"
bottom: "data"
top: "conv1_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
dilation: 1
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
dilation: 1
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
dilation: 1
}
}
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: 3
stride: 1
pad: 1
}
}
layer {
name: "fc6"
type: "Convolution"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 1024
pad: 6
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
dilation: 6
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "fc7"
type: "Convolution"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 1024
kernel_size: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "conv6_1"
type: "Convolution"
bottom: "fc7"
top: "conv6_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
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: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv7_2_relu"
type: "ReLU"
bottom: "conv7_2"
top: "conv7_2"
}
layer {
name: "conv4_3_reduce"
type: "Convolution"
bottom: "conv4_3"
top: "conv4_3_reduce"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_3_reduce_relu"
type: "ReLU"
bottom: "conv4_3_reduce"
top: "conv4_3_reduce"
}
layer {
name: "fc7_reduce"
type: "Convolution"
bottom: "fc7"
top: "fc7_reduce"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fc7_reduce_relu"
type: "ReLU"
bottom: "fc7_reduce"
top: "fc7_reduce"
}
layer {
name: "fc7_us"
type: "Interp"
bottom: "fc7_reduce"
top: "fc7_us"
interp_param {
height: 64
width: 64
}
}
layer {
name: "conv7_2_us"
type: "Interp"
bottom: "conv7_2"
top: "conv7_2_us"
interp_param {
height: 64
width: 64
}
}
layer {
name: "fea_concat"
type: "Concat"
bottom: "conv4_3_reduce"
bottom: "fc7_us"
bottom: "conv7_2_us"
top: "fea_concat"
concat_param {
axis: 1
}
}
layer {
name: "fea_concat_bn"
type: "BatchNorm"
bottom: "fea_concat"
top: "fea_concat"
}
layer {
name: "fea_concat_bn_ds_1"
type: "Convolution"
bottom: "fea_concat"
top: "fea_concat_bn_ds_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_1_relu"
type: "ReLU"
bottom: "fea_concat_bn_ds_1"
top: "fea_concat_bn_ds_1"
}
layer {
name: "fea_concat_bn_ds_2"
type: "Convolution"
bottom: "fea_concat_bn_ds_1"
top: "fea_concat_bn_ds_2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_2_relu"
type: "ReLU"
bottom: "fea_concat_bn_ds_2"
top: "fea_concat_bn_ds_2"
}
layer {
name: "fea_concat_bn_ds_4"
type: "Convolution"
bottom: "fea_concat_bn_ds_2"
top: "fea_concat_bn_ds_4"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_4_relu"
type: "ReLU"
bottom: "fea_concat_bn_ds_4"
top: "fea_concat_bn_ds_4"
}
layer {
name: "fea_concat_bn_ds_8"
type: "Convolution"
bottom: "fea_concat_bn_ds_4"
top: "fea_concat_bn_ds_8"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_8_relu"
type: "ReLU"
bottom: "fea_concat_bn_ds_8"
top: "fea_concat_bn_ds_8"
}
layer {
name: "fea_concat_bn_ds_16"
type: "Convolution"
bottom: "fea_concat_bn_ds_8"
top: "fea_concat_bn_ds_16"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_16_relu"
type: "ReLU"
bottom: "fea_concat_bn_ds_16"
top: "fea_concat_bn_ds_16"
}
layer {
name: "fea_concat_bn_ds_32"
type: "Convolution"
bottom: "fea_concat_bn_ds_16"
top: "fea_concat_bn_ds_32"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_32_relu"
type: "ReLU"
bottom: "fea_concat_bn_ds_32"
top: "fea_concat_bn_ds_32"
}
layer {
name: "fea_concat_bn_ds_64"
type: "Convolution"
bottom: "fea_concat_bn_ds_32"
top: "fea_concat_bn_ds_64"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 4
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_64_relu"
type: "ReLU"
bottom: "fea_concat_bn_ds_64"
top: "fea_concat_bn_ds_64"
}
layer {
name: "fea_concat_bn_ds_1_mbox_loc"
type: "Convolution"
bottom: "fea_concat_bn_ds_1"
top: "fea_concat_bn_ds_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: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_1_mbox_loc_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_1_mbox_loc"
top: "fea_concat_bn_ds_1_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_1_mbox_loc_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_1_mbox_loc_perm"
top: "fea_concat_bn_ds_1_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_1_mbox_conf"
type: "Convolution"
bottom: "fea_concat_bn_ds_1"
top: "fea_concat_bn_ds_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: 324
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_1_mbox_conf_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_1_mbox_conf"
top: "fea_concat_bn_ds_1_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_1_mbox_conf_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_1_mbox_conf_perm"
top: "fea_concat_bn_ds_1_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_1_mbox_priorbox"
type: "PriorBox"
bottom: "fea_concat_bn_ds_1"
bottom: "data"
top: "fea_concat_bn_ds_1_mbox_priorbox"
prior_box_param {
min_size: 35.8400001526
max_size: 76.8000030518
aspect_ratio: 2.0
flip: true
clip: false
variance: 0.10000000149
variance: 0.10000000149
variance: 0.20000000298
variance: 0.20000000298
offset: 0.5
}
}
layer {
name: "fea_concat_bn_ds_2_mbox_loc"
type: "Convolution"
bottom: "fea_concat_bn_ds_2"
top: "fea_concat_bn_ds_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
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_2_mbox_loc_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_2_mbox_loc"
top: "fea_concat_bn_ds_2_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_2_mbox_loc_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_2_mbox_loc_perm"
top: "fea_concat_bn_ds_2_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_2_mbox_conf"
type: "Convolution"
bottom: "fea_concat_bn_ds_2"
top: "fea_concat_bn_ds_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: 486
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_2_mbox_conf_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_2_mbox_conf"
top: "fea_concat_bn_ds_2_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_2_mbox_conf_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_2_mbox_conf_perm"
top: "fea_concat_bn_ds_2_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_2_mbox_priorbox"
type: "PriorBox"
bottom: "fea_concat_bn_ds_2"
bottom: "data"
top: "fea_concat_bn_ds_2_mbox_priorbox"
prior_box_param {
min_size: 76.8000030518
max_size: 153.600006104
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.10000000149
variance: 0.10000000149
variance: 0.20000000298
variance: 0.20000000298
offset: 0.5
}
}
layer {
name: "fea_concat_bn_ds_4_mbox_loc"
type: "Convolution"
bottom: "fea_concat_bn_ds_4"
top: "fea_concat_bn_ds_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
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_4_mbox_loc_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_4_mbox_loc"
top: "fea_concat_bn_ds_4_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_4_mbox_loc_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_4_mbox_loc_perm"
top: "fea_concat_bn_ds_4_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_4_mbox_conf"
type: "Convolution"
bottom: "fea_concat_bn_ds_4"
top: "fea_concat_bn_ds_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: 486
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_4_mbox_conf_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_4_mbox_conf"
top: "fea_concat_bn_ds_4_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_4_mbox_conf_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_4_mbox_conf_perm"
top: "fea_concat_bn_ds_4_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_4_mbox_priorbox"
type: "PriorBox"
bottom: "fea_concat_bn_ds_4"
bottom: "data"
top: "fea_concat_bn_ds_4_mbox_priorbox"
prior_box_param {
min_size: 153.600006104
max_size: 230.399993896
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.10000000149
variance: 0.10000000149
variance: 0.20000000298
variance: 0.20000000298
offset: 0.5
}
}
layer {
name: "fea_concat_bn_ds_8_mbox_loc"
type: "Convolution"
bottom: "fea_concat_bn_ds_8"
top: "fea_concat_bn_ds_8_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
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_8_mbox_loc_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_8_mbox_loc"
top: "fea_concat_bn_ds_8_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_8_mbox_loc_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_8_mbox_loc_perm"
top: "fea_concat_bn_ds_8_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_8_mbox_conf"
type: "Convolution"
bottom: "fea_concat_bn_ds_8"
top: "fea_concat_bn_ds_8_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 486
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_8_mbox_conf_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_8_mbox_conf"
top: "fea_concat_bn_ds_8_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_8_mbox_conf_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_8_mbox_conf_perm"
top: "fea_concat_bn_ds_8_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_8_mbox_priorbox"
type: "PriorBox"
bottom: "fea_concat_bn_ds_8"
bottom: "data"
top: "fea_concat_bn_ds_8_mbox_priorbox"
prior_box_param {
min_size: 230.399993896
max_size: 307.200012207
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.10000000149
variance: 0.10000000149
variance: 0.20000000298
variance: 0.20000000298
offset: 0.5
}
}
layer {
name: "fea_concat_bn_ds_16_mbox_loc"
type: "Convolution"
bottom: "fea_concat_bn_ds_16"
top: "fea_concat_bn_ds_16_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
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_16_mbox_loc_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_16_mbox_loc"
top: "fea_concat_bn_ds_16_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_16_mbox_loc_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_16_mbox_loc_perm"
top: "fea_concat_bn_ds_16_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_16_mbox_conf"
type: "Convolution"
bottom: "fea_concat_bn_ds_16"
top: "fea_concat_bn_ds_16_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 486
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_16_mbox_conf_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_16_mbox_conf"
top: "fea_concat_bn_ds_16_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_16_mbox_conf_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_16_mbox_conf_perm"
top: "fea_concat_bn_ds_16_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_16_mbox_priorbox"
type: "PriorBox"
bottom: "fea_concat_bn_ds_16"
bottom: "data"
top: "fea_concat_bn_ds_16_mbox_priorbox"
prior_box_param {
min_size: 307.200012207
max_size: 384.0
aspect_ratio: 2.0
aspect_ratio: 3.0
flip: true
clip: false
variance: 0.10000000149
variance: 0.10000000149
variance: 0.20000000298
variance: 0.20000000298
offset: 0.5
}
}
layer {
name: "fea_concat_bn_ds_32_mbox_loc"
type: "Convolution"
bottom: "fea_concat_bn_ds_32"
top: "fea_concat_bn_ds_32_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_32_mbox_loc_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_32_mbox_loc"
top: "fea_concat_bn_ds_32_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_32_mbox_loc_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_32_mbox_loc_perm"
top: "fea_concat_bn_ds_32_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_32_mbox_conf"
type: "Convolution"
bottom: "fea_concat_bn_ds_32"
top: "fea_concat_bn_ds_32_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 324
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_32_mbox_conf_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_32_mbox_conf"
top: "fea_concat_bn_ds_32_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_32_mbox_conf_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_32_mbox_conf_perm"
top: "fea_concat_bn_ds_32_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_32_mbox_priorbox"
type: "PriorBox"
bottom: "fea_concat_bn_ds_32"
bottom: "data"
top: "fea_concat_bn_ds_32_mbox_priorbox"
prior_box_param {
min_size: 384.0
max_size: 460.799987793
aspect_ratio: 2.0
flip: true
clip: false
variance: 0.10000000149
variance: 0.10000000149
variance: 0.20000000298
variance: 0.20000000298
offset: 0.5
}
}
layer {
name: "fea_concat_bn_ds_64_mbox_loc"
type: "Convolution"
bottom: "fea_concat_bn_ds_64"
top: "fea_concat_bn_ds_64_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_64_mbox_loc_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_64_mbox_loc"
top: "fea_concat_bn_ds_64_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_64_mbox_loc_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_64_mbox_loc_perm"
top: "fea_concat_bn_ds_64_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_64_mbox_conf"
type: "Convolution"
bottom: "fea_concat_bn_ds_64"
top: "fea_concat_bn_ds_64_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 324
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fea_concat_bn_ds_64_mbox_conf_perm"
type: "Permute"
bottom: "fea_concat_bn_ds_64_mbox_conf"
top: "fea_concat_bn_ds_64_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fea_concat_bn_ds_64_mbox_conf_flat"
type: "Flatten"
bottom: "fea_concat_bn_ds_64_mbox_conf_perm"
top: "fea_concat_bn_ds_64_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fea_concat_bn_ds_64_mbox_priorbox"
type: "PriorBox"
bottom: "fea_concat_bn_ds_64"
bottom: "data"
top: "fea_concat_bn_ds_64_mbox_priorbox"
prior_box_param {
min_size: 460.799987793
max_size: 537.599975586
aspect_ratio: 2.0
flip: true
clip: false
variance: 0.10000000149
variance: 0.10000000149
variance: 0.20000000298
variance: 0.20000000298
offset: 0.5
}
}
layer {
name: "mbox_loc"
type: "Concat"
bottom: "fea_concat_bn_ds_1_mbox_loc_flat"
bottom: "fea_concat_bn_ds_2_mbox_loc_flat"
bottom: "fea_concat_bn_ds_4_mbox_loc_flat"
bottom: "fea_concat_bn_ds_8_mbox_loc_flat"
bottom: "fea_concat_bn_ds_16_mbox_loc_flat"
bottom: "fea_concat_bn_ds_32_mbox_loc_flat"
bottom: "fea_concat_bn_ds_64_mbox_loc_flat"
top: "mbox_loc"
concat_param {
axis: 1
}
}
layer {
name: "mbox_conf"
type: "Concat"
bottom: "fea_concat_bn_ds_1_mbox_conf_flat"
bottom: "fea_concat_bn_ds_2_mbox_conf_flat"
bottom: "fea_concat_bn_ds_4_mbox_conf_flat"
bottom: "fea_concat_bn_ds_8_mbox_conf_flat"
bottom: "fea_concat_bn_ds_16_mbox_conf_flat"
bottom: "fea_concat_bn_ds_32_mbox_conf_flat"
bottom: "fea_concat_bn_ds_64_mbox_conf_flat"
top: "mbox_conf"
concat_param {
axis: 1
}
}
layer {
name: "mbox_priorbox"
type: "Concat"
bottom: "fea_concat_bn_ds_1_mbox_priorbox"
bottom: "fea_concat_bn_ds_2_mbox_priorbox"
bottom: "fea_concat_bn_ds_4_mbox_priorbox"
bottom: "fea_concat_bn_ds_8_mbox_priorbox"
bottom: "fea_concat_bn_ds_16_mbox_priorbox"
bottom: "fea_concat_bn_ds_32_mbox_priorbox"
bottom: "fea_concat_bn_ds_64_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: 81
}
}
}
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: 81
share_location: true
background_label_id: 0
nms_param {
nms_threshold: 0.449999988079
top_k: 400
}
save_output_param {
output_directory: "jobs/VGGNet/SSD_FPN_NO33_WOP512x512/1025/predict_ss"
output_name_prefix: "detections_minival_fssd512_"
output_format: "COCO"
label_map_file: "data/coco/labelmap_coco.prototxt"
name_size_file: "data/coco/minival2014_name_size.txt"
num_test_image: 5000
}
code_type: CENTER_SIZE
keep_top_k: 200
confidence_threshold: 0.00999999977648
}
}