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August 2, 2018 11:52
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FCN16s Prototxt formatted. Netscope compatible (https://dgschwend.github.io/netscope/#/gist/23ef986f46258fa3303129dabf8066a5).
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name: 'FCN 16s' | |
layer { | |
type: 'data' | |
name: 'data' | |
top: 'data' | |
input_param { | |
shape { | |
dim: 1 | |
dim: 3 | |
dim: 500 | |
dim: 500 | |
} | |
} | |
force_backward: true | |
} | |
layers { | |
bottom: 'data' | |
top: 'conv1_1' | |
name: 'conv1_1' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv1_1' | |
top: 'conv1_1' | |
name: 'relu1_1' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv1_1' | |
top: 'conv1_2' | |
name: 'conv1_2' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv1_2' | |
top: 'conv1_2' | |
name: 'relu1_2' | |
type: RELU | |
} | |
layers { | |
name: 'pool1' | |
bottom: 'conv1_2' | |
top: 'pool1' | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layers { | |
name: 'conv2_1' | |
bottom: 'pool1' | |
top: 'conv2_1' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv2_1' | |
top: 'conv2_1' | |
name: 'relu2_1' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv2_1' | |
top: 'conv2_2' | |
name: 'conv2_2' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv2_2' | |
top: 'conv2_2' | |
name: 'relu2_2' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv2_2' | |
top: 'pool2' | |
name: 'pool2' | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layers { | |
bottom: 'pool2' | |
top: 'conv3_1' | |
name: 'conv3_1' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv3_1' | |
top: 'conv3_1' | |
name: 'relu3_1' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv3_1' | |
top: 'conv3_2' | |
name: 'conv3_2' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv3_2' | |
top: 'conv3_2' | |
name: 'relu3_2' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv3_2' | |
top: 'conv3_3' | |
name: 'conv3_3' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv3_3' | |
top: 'conv3_3' | |
name: 'relu3_3' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv3_3' | |
top: 'pool3' | |
name: 'pool3' | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layers { | |
bottom: 'pool3' | |
top: 'conv4_1' | |
name: 'conv4_1' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv4_1' | |
top: 'conv4_1' | |
name: 'relu4_1' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv4_1' | |
top: 'conv4_2' | |
name: 'conv4_2' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv4_2' | |
top: 'conv4_2' | |
name: 'relu4_2' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv4_2' | |
top: 'conv4_3' | |
name: 'conv4_3' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv4_3' | |
top: 'conv4_3' | |
name: 'relu4_3' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv4_3' | |
top: 'pool4' | |
name: 'pool4' | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layers { | |
bottom: 'pool4' | |
top: 'conv5_1' | |
name: 'conv5_1' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv5_1' | |
top: 'conv5_1' | |
name: 'relu5_1' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv5_1' | |
top: 'conv5_2' | |
name: 'conv5_2' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv5_2' | |
top: 'conv5_2' | |
name: 'relu5_2' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv5_2' | |
top: 'conv5_3' | |
name: 'conv5_3' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layers { | |
bottom: 'conv5_3' | |
top: 'conv5_3' | |
name: 'relu5_3' | |
type: RELU | |
} | |
layers { | |
bottom: 'conv5_3' | |
top: 'pool5' | |
name: 'pool5' | |
type: POOLING | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layers { | |
bottom: 'pool5' | |
top: 'fc6' | |
name: 'fc6' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
kernel_size: 7 | |
num_output: 4096 | |
} | |
} | |
layers { | |
bottom: 'fc6' | |
top: 'fc6' | |
name: 'relu6' | |
type: RELU | |
} | |
layers { | |
bottom: 'fc6' | |
top: 'fc6' | |
name: 'drop6' | |
type: DROPOUT | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
layers { | |
bottom: 'fc6' | |
top: 'fc7' | |
name: 'fc7' | |
type: CONVOLUTION | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
kernel_size: 1 | |
num_output: 4096 | |
} | |
} | |
layers { | |
bottom: 'fc7' | |
top: 'fc7' | |
name: 'relu7' | |
type: RELU | |
} | |
layers { | |
bottom: 'fc7' | |
top: 'fc7' | |
name: 'drop7' | |
type: DROPOUT | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
layers { | |
name: 'score' | |
type: CONVOLUTION | |
bottom: 'fc7' | |
top: 'score' | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 21 | |
kernel_size: 1 | |
} | |
} | |
layers { | |
type: DECONVOLUTION | |
name: 'score2' | |
bottom: 'score' | |
top: 'score2' | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
kernel_size: 4 | |
stride: 2 | |
num_output: 21 | |
} | |
} | |
layers { | |
name: 'score-pool4' | |
type: CONVOLUTION | |
bottom: 'pool4' | |
top: 'score-pool4' | |
blobs_lr: 1 | |
blobs_lr: 2 | |
weight_decay: 1 | |
weight_decay: 0 | |
convolution_param { | |
engine: CAFFE | |
num_output: 21 | |
kernel_size: 1 | |
} | |
} | |
layers { | |
type: CROP | |
name: 'score-pool4c' | |
bottom: 'score-pool4' | |
top: 'score-pool44c' | |
bottom: 'score2' | |
} | |
layers { | |
type: ELTWISE | |
name: 'score-fuse' | |
bottom: 'score2' | |
bottom: 'score-pool4c' | |
top: 'score-fuse' | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layers { | |
type: DECONVOLUTION | |
name: 'bigscore' | |
bottom: 'score-fuse' | |
top: 'bigscore' | |
blobs_lr: 0 | |
blobs_lr: 0 | |
convolution_param { | |
num_output: 21 | |
kernel_size: 32 | |
stride: 16 | |
} | |
} | |
layers { | |
type: CROP | |
name: 'upscore' | |
bottom: 'bigscore' | |
bottom: 'data' | |
top: 'upscore' | |
} | |
layers { | |
type: SOFTMAX | |
name: 'output' | |
bottom: 'upscore' | |
} |
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