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- name: "Fisher Yu's Context Train Net @ PASCAL VOC 2012"
- layer {
- name: "data"
- type: "BinLabelData"
- top: "data"
- top: "label"
- bin_label_data_param {
- bin_list_path: "PASCAL_VOC2012"
- label_list_path: "PASCAL_VOC2012"
- batch_size: 14
- shuffle: true
- label_slice {
- dim: 66
- dim: 66
- stride: 8
- stride: 8
- }
- }
- }
- layer {
- name: "ctx_conv1_1"
- type: "Convolution"
- bottom: "data"
- top: "ctx_conv1_1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- pad: 1
- kernel_size: 3
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "ctx_relu1_1"
- type: "ReLU"
- bottom: "ctx_conv1_1"
- top: "ctx_conv1_1"
- }
- layer {
- name: "ctx_conv1_2"
- type: "Convolution"
- bottom: "ctx_conv1_1"
- top: "ctx_conv1_2"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- pad: 1
- kernel_size: 3
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "ctx_relu1_2"
- type: "ReLU"
- bottom: "ctx_conv1_2"
- top: "ctx_conv1_2"
- }
- layer {
- name: "ctx_conv2_1"
- type: "Convolution"
- bottom: "ctx_conv1_2"
- top: "ctx_conv2_1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- pad: 2
- kernel_size: 3
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- dilation: 2
- }
- }
- layer {
- name: "ctx_relu2_1"
- type: "ReLU"
- bottom: "ctx_conv2_1"
- top: "ctx_conv2_1"
- }
- layer {
- name: "ctx_conv3_1"
- type: "Convolution"
- bottom: "ctx_conv2_1"
- top: "ctx_conv3_1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- pad: 4
- kernel_size: 3
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- dilation: 4
- }
- }
- layer {
- name: "ctx_relu3_1"
- type: "ReLU"
- bottom: "ctx_conv3_1"
- top: "ctx_conv3_1"
- }
- layer {
- name: "ctx_conv4_1"
- type: "Convolution"
- bottom: "ctx_conv3_1"
- top: "ctx_conv4_1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- pad: 8
- kernel_size: 3
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- dilation: 8
- }
- }
- layer {
- name: "ctx_relu4_1"
- type: "ReLU"
- bottom: "ctx_conv4_1"
- top: "ctx_conv4_1"
- }
- layer {
- name: "ctx_conv5_1"
- type: "Convolution"
- bottom: "ctx_conv4_1"
- top: "ctx_conv5_1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- pad: 16
- kernel_size: 3
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- dilation: 16
- }
- }
- layer {
- name: "ctx_relu5_1"
- type: "ReLU"
- bottom: "ctx_conv5_1"
- top: "ctx_conv5_1"
- }
- layer {
- name: "ctx_fc1"
- type: "Convolution"
- bottom: "ctx_conv5_1"
- top: "ctx_fc1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- pad: 1
- kernel_size: 3
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "ctx_fc1_relu"
- type: "ReLU"
- bottom: "ctx_fc1"
- top: "ctx_fc1"
- }
- layer {
- name: "ctx_final"
- type: "Convolution"
- bottom: "ctx_fc1"
- top: "ctx_final"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 21
- kernel_size: 1
- weight_filler {
- type: "identity"
- std: 0.01
- num_groups: 21
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "loss"
- type: "SoftmaxWithLoss"
- bottom: "ctx_final"
- bottom: "label"
- top: "loss"
- loss_param {
- ignore_label: 255
- normalization: VALID
- }
- }
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