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pose_training.prototxt
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executable file
·5573 lines (5573 loc) · 89.1 KB
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layer {
name: "image"
type: "OPData"
top: "image"
top: "label"
data_param {
batch_size: 10
backend: LMDB
}
op_transform_param {
stride: 8
max_degree_rotations: "45;45;45;45;45;45;45;45;45"
crop_size_x: 480
crop_size_y: 480
center_perterb_max: 40.0
center_swap_prob: 0.0
scale_prob: 1.0
scale_mins: "0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.333333333333;0.666666666667;0.5;0.666666666667"
scale_maxs: "1.5;1.5;2.5;1.5;1.5;2.5;1.5;1.5;2.5;1.5;1.5;1.5;4.5;4.0;4.5"
target_dist: 0.600000023842
number_max_occlusions: "2;2;2;0;0;0;0;0;0"
sigmas: "7.0;7.0;7.0;7.0;7.0;7.0;7.0;7.0;7.0"
models: "COCO_135_23;COCO_135_17;MPII_135_16;FACE_135_70;FACE_135_70;FACE_135_70;HAND_135_21;HAND_135_42;DOME_135"
sources: "/home/gines/devel/openpose_train/dataset/lmdb_coco2017_foot;/home/gines/devel/openpose_train/dataset/lmdb_coco;/home/gines/devel/openpose_train/dataset/lmdb_mpii;/home/gines/devel/openpose_train/dataset/lmdb_face_frgc;/home/gines/devel/openpose_train/dataset/lmdb_face_multipie;/home/gines/devel/openpose_train/dataset/lmdb_face_mask_out;/home/gines/devel/openpose_train/dataset/lmdb_hand_dome;/home/gines/devel/openpose_train/dataset/lmdb_hand_mpii;/home/gines/devel/openpose_train/dataset/lmdb_dome135"
probabilities: "0.05;0.73;0.05;0.005;0.01;0.005;0.005;0.05;0.075"
source_background: "/home/gines/devel/openpose_train/dataset/lmdb_background"
prob_only_background: 0.019999999553
media_directory: "/media/posefs0c/panopticdb/a4/hdImgs/"
normalization: 0
add_distance: false
}
}
layer {
name: "vec_weight"
type: "Slice"
bottom: "label"
top: "vec_weight"
top: "heat_weight"
top: "vec_temp"
top: "heat_temp"
slice_param {
slice_point: 304
slice_point: 439
slice_point: 743
axis: 1
}
}
layer {
name: "label_heat"
type: "Eltwise"
bottom: "heat_weight"
bottom: "heat_temp"
top: "label_heat"
eltwise_param {
operation: PROD
}
}
layer {
name: "label_vec"
type: "Eltwise"
bottom: "vec_weight"
bottom: "vec_temp"
top: "label_vec"
eltwise_param {
operation: PROD
}
}
layer {
name: "conv1_1"
type: "Convolution"
bottom: "image"
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "relu1_2"
type: "ReLU"
bottom: "conv1_2"
top: "conv1_2"
}
layer {
name: "pool1_stage1"
type: "Pooling"
bottom: "conv1_2"
top: "pool1_stage1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv2_1"
type: "Convolution"
bottom: "pool1_stage1"
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "relu2_2"
type: "ReLU"
bottom: "conv2_2"
top: "conv2_2"
}
layer {
name: "pool2_stage1"
type: "Pooling"
bottom: "conv2_2"
top: "pool2_stage1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv3_1"
type: "Convolution"
bottom: "pool2_stage1"
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "relu3_3"
type: "ReLU"
bottom: "conv3_3"
top: "conv3_3"
}
layer {
name: "conv3_4"
type: "Convolution"
bottom: "conv3_3"
top: "conv3_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
weight_filler {
type: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "relu3_4"
type: "ReLU"
bottom: "conv3_4"
top: "conv3_4"
}
layer {
name: "pool3_stage1"
type: "Pooling"
bottom: "conv3_4"
top: "pool3_stage1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv4_1"
type: "Convolution"
bottom: "pool3_stage1"
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
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: "gaussian"
std: 0.00999999977648
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "prelu4_2"
type: "PReLU"
bottom: "conv4_2"
top: "conv4_2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "conv4_3_CPM"
type: "Convolution"
bottom: "conv4_2"
top: "conv4_3_CPM"
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"
}
}
}
layer {
name: "prelu4_3_CPM"
type: "PReLU"
bottom: "conv4_3_CPM"
top: "conv4_3_CPM"
param {
lr_mult: 1.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "conv4_4_CPM"
type: "Convolution"
bottom: "conv4_3_CPM"
top: "conv4_4_CPM"
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"
}
}
}
layer {
name: "prelu4_4_CPM"
type: "PReLU"
bottom: "conv4_4_CPM"
top: "conv4_4_CPM"
param {
lr_mult: 1.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv1_stage0_L2_0"
type: "Convolution"
bottom: "conv4_4_CPM"
top: "Mconv1_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu1_stage0_L2_0"
type: "PReLU"
bottom: "Mconv1_stage0_L2_0"
top: "Mconv1_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv1_stage0_L2_1"
type: "Convolution"
bottom: "Mconv1_stage0_L2_0"
top: "Mconv1_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu1_stage0_L2_1"
type: "PReLU"
bottom: "Mconv1_stage0_L2_1"
top: "Mconv1_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv1_stage0_L2_2"
type: "Convolution"
bottom: "Mconv1_stage0_L2_1"
top: "Mconv1_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu1_stage0_L2_2"
type: "PReLU"
bottom: "Mconv1_stage0_L2_2"
top: "Mconv1_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv1_stage0_L2_concat"
type: "Concat"
bottom: "Mconv1_stage0_L2_0"
bottom: "Mconv1_stage0_L2_1"
bottom: "Mconv1_stage0_L2_2"
top: "Mconv1_stage0_L2_concat"
concat_param {
axis: 1
}
}
layer {
name: "Mconv2_stage0_L2_0"
type: "Convolution"
bottom: "Mconv1_stage0_L2_concat"
top: "Mconv2_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu2_stage0_L2_0"
type: "PReLU"
bottom: "Mconv2_stage0_L2_0"
top: "Mconv2_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv2_stage0_L2_1"
type: "Convolution"
bottom: "Mconv2_stage0_L2_0"
top: "Mconv2_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu2_stage0_L2_1"
type: "PReLU"
bottom: "Mconv2_stage0_L2_1"
top: "Mconv2_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv2_stage0_L2_2"
type: "Convolution"
bottom: "Mconv2_stage0_L2_1"
top: "Mconv2_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu2_stage0_L2_2"
type: "PReLU"
bottom: "Mconv2_stage0_L2_2"
top: "Mconv2_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv2_stage0_L2_concat"
type: "Concat"
bottom: "Mconv2_stage0_L2_0"
bottom: "Mconv2_stage0_L2_1"
bottom: "Mconv2_stage0_L2_2"
top: "Mconv2_stage0_L2_concat"
concat_param {
axis: 1
}
}
layer {
name: "Mconv3_stage0_L2_0"
type: "Convolution"
bottom: "Mconv2_stage0_L2_concat"
top: "Mconv3_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu3_stage0_L2_0"
type: "PReLU"
bottom: "Mconv3_stage0_L2_0"
top: "Mconv3_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv3_stage0_L2_1"
type: "Convolution"
bottom: "Mconv3_stage0_L2_0"
top: "Mconv3_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu3_stage0_L2_1"
type: "PReLU"
bottom: "Mconv3_stage0_L2_1"
top: "Mconv3_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv3_stage0_L2_2"
type: "Convolution"
bottom: "Mconv3_stage0_L2_1"
top: "Mconv3_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu3_stage0_L2_2"
type: "PReLU"
bottom: "Mconv3_stage0_L2_2"
top: "Mconv3_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv3_stage0_L2_concat"
type: "Concat"
bottom: "Mconv3_stage0_L2_0"
bottom: "Mconv3_stage0_L2_1"
bottom: "Mconv3_stage0_L2_2"
top: "Mconv3_stage0_L2_concat"
concat_param {
axis: 1
}
}
layer {
name: "Mconv4_stage0_L2_0"
type: "Convolution"
bottom: "Mconv3_stage0_L2_concat"
top: "Mconv4_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu4_stage0_L2_0"
type: "PReLU"
bottom: "Mconv4_stage0_L2_0"
top: "Mconv4_stage0_L2_0"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv4_stage0_L2_1"
type: "Convolution"
bottom: "Mconv4_stage0_L2_0"
top: "Mconv4_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu4_stage0_L2_1"
type: "PReLU"
bottom: "Mconv4_stage0_L2_1"
top: "Mconv4_stage0_L2_1"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv4_stage0_L2_2"
type: "Convolution"
bottom: "Mconv4_stage0_L2_1"
top: "Mconv4_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
param {
lr_mult: 8.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Mprelu4_stage0_L2_2"
type: "PReLU"
bottom: "Mconv4_stage0_L2_2"
top: "Mconv4_stage0_L2_2"
param {
lr_mult: 4.0
decay_mult: 1.0
}
prelu_param {
channel_shared: false
}
}
layer {
name: "Mconv4_stage0_L2_concat"
type: "Concat"
bottom: "Mconv4_stage0_L2_0"
bottom: "Mconv4_stage0_L2_1"
bottom: "Mconv4_stage0_L2_2"
top: "Mconv4_stage0_L2_concat"
concat_param {