input: "image" input_dim: 1 # Original: 2 input_dim: 3 # It crashes if not left to 3 input_dim: 1 # Original: 368 input_dim: 1 # Original: 368 layer { name: "conv1_1" type: "Convolution" bottom: "image" top: "conv1_1" param { lr_mult: 1.0 decay_mult: 1 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 64 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 64 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 256 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 256 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 256 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 256 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 512 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 512 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 512 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } layer { name: "relu4_3" type: "ReLU" bottom: "conv4_3" top: "conv4_3" } layer { name: "conv4_4" type: "Convolution" bottom: "conv4_3" top: "conv4_4" param { lr_mult: 1.0 decay_mult: 1 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 512 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } layer { name: "relu4_4" type: "ReLU" bottom: "conv4_4" top: "conv4_4" } layer { name: "conv5_1" type: "Convolution" bottom: "conv4_4" top: "conv5_1" param { lr_mult: 1.0 decay_mult: 1 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 512 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } 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 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 512 pad: 1 kernel_size: 3 weight_filler { type: "xavier" } bias_filler { type: "constant" } dilation: 1 } } layer { name: "relu5_2" type: "ReLU" bottom: "conv5_2" top: "conv5_2" } layer { name: "conv5_3_CPM" type: "Convolution" bottom: "conv5_2" top: "conv5_3_CPM" param { lr_mult: 1.0 decay_mult: 1 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 1 kernel_size: 3 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "relu5_4_stage1_3" type: "ReLU" bottom: "conv5_3_CPM" top: "conv5_3_CPM" } layer { name: "conv6_1_CPM" type: "Convolution" bottom: "conv5_3_CPM" top: "conv6_1_CPM" param { lr_mult: 1.0 decay_mult: 1 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 512 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "relu6_4_stage1_1" type: "ReLU" bottom: "conv6_1_CPM" top: "conv6_1_CPM" } layer { name: "conv6_2_CPM" type: "Convolution" bottom: "conv6_1_CPM" top: "conv6_2_CPM" param { lr_mult: 1.0 decay_mult: 1 } param { lr_mult: 2.0 decay_mult: 0 } convolution_param { num_output: 22 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "concat_stage2" type: "Concat" bottom: "conv6_2_CPM" bottom: "conv5_3_CPM" top: "concat_stage2" concat_param { axis: 1 } } layer { name: "Mconv1_stage2" type: "Convolution" bottom: "concat_stage2" top: "Mconv1_stage2" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_2_stage2_1" type: "ReLU" bottom: "Mconv1_stage2" top: "Mconv1_stage2" } layer { name: "Mconv2_stage2" type: "Convolution" bottom: "Mconv1_stage2" top: "Mconv2_stage2" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_3_stage2_2" type: "ReLU" bottom: "Mconv2_stage2" top: "Mconv2_stage2" } layer { name: "Mconv3_stage2" type: "Convolution" bottom: "Mconv2_stage2" top: "Mconv3_stage2" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_4_stage2_3" type: "ReLU" bottom: "Mconv3_stage2" top: "Mconv3_stage2" } layer { name: "Mconv4_stage2" type: "Convolution" bottom: "Mconv3_stage2" top: "Mconv4_stage2" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_5_stage2_4" type: "ReLU" bottom: "Mconv4_stage2" top: "Mconv4_stage2" } layer { name: "Mconv5_stage2" type: "Convolution" bottom: "Mconv4_stage2" top: "Mconv5_stage2" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_6_stage2_5" type: "ReLU" bottom: "Mconv5_stage2" top: "Mconv5_stage2" } layer { name: "Mconv6_stage2" type: "Convolution" bottom: "Mconv5_stage2" top: "Mconv6_stage2" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_7_stage2_6" type: "ReLU" bottom: "Mconv6_stage2" top: "Mconv6_stage2" } layer { name: "Mconv7_stage2" type: "Convolution" bottom: "Mconv6_stage2" top: "Mconv7_stage2" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 22 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "concat_stage3" type: "Concat" bottom: "Mconv7_stage2" bottom: "conv5_3_CPM" top: "concat_stage3" concat_param { axis: 1 } } layer { name: "Mconv1_stage3" type: "Convolution" bottom: "concat_stage3" top: "Mconv1_stage3" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_2_stage3_1" type: "ReLU" bottom: "Mconv1_stage3" top: "Mconv1_stage3" } layer { name: "Mconv2_stage3" type: "Convolution" bottom: "Mconv1_stage3" top: "Mconv2_stage3" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_3_stage3_2" type: "ReLU" bottom: "Mconv2_stage3" top: "Mconv2_stage3" } layer { name: "Mconv3_stage3" type: "Convolution" bottom: "Mconv2_stage3" top: "Mconv3_stage3" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_4_stage3_3" type: "ReLU" bottom: "Mconv3_stage3" top: "Mconv3_stage3" } layer { name: "Mconv4_stage3" type: "Convolution" bottom: "Mconv3_stage3" top: "Mconv4_stage3" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_5_stage3_4" type: "ReLU" bottom: "Mconv4_stage3" top: "Mconv4_stage3" } layer { name: "Mconv5_stage3" type: "Convolution" bottom: "Mconv4_stage3" top: "Mconv5_stage3" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_6_stage3_5" type: "ReLU" bottom: "Mconv5_stage3" top: "Mconv5_stage3" } layer { name: "Mconv6_stage3" type: "Convolution" bottom: "Mconv5_stage3" top: "Mconv6_stage3" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_7_stage3_6" type: "ReLU" bottom: "Mconv6_stage3" top: "Mconv6_stage3" } layer { name: "Mconv7_stage3" type: "Convolution" bottom: "Mconv6_stage3" top: "Mconv7_stage3" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 22 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "concat_stage4" type: "Concat" bottom: "Mconv7_stage3" bottom: "conv5_3_CPM" top: "concat_stage4" concat_param { axis: 1 } } layer { name: "Mconv1_stage4" type: "Convolution" bottom: "concat_stage4" top: "Mconv1_stage4" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_2_stage4_1" type: "ReLU" bottom: "Mconv1_stage4" top: "Mconv1_stage4" } layer { name: "Mconv2_stage4" type: "Convolution" bottom: "Mconv1_stage4" top: "Mconv2_stage4" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_3_stage4_2" type: "ReLU" bottom: "Mconv2_stage4" top: "Mconv2_stage4" } layer { name: "Mconv3_stage4" type: "Convolution" bottom: "Mconv2_stage4" top: "Mconv3_stage4" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_4_stage4_3" type: "ReLU" bottom: "Mconv3_stage4" top: "Mconv3_stage4" } layer { name: "Mconv4_stage4" type: "Convolution" bottom: "Mconv3_stage4" top: "Mconv4_stage4" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_5_stage4_4" type: "ReLU" bottom: "Mconv4_stage4" top: "Mconv4_stage4" } layer { name: "Mconv5_stage4" type: "Convolution" bottom: "Mconv4_stage4" top: "Mconv5_stage4" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_6_stage4_5" type: "ReLU" bottom: "Mconv5_stage4" top: "Mconv5_stage4" } layer { name: "Mconv6_stage4" type: "Convolution" bottom: "Mconv5_stage4" top: "Mconv6_stage4" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_7_stage4_6" type: "ReLU" bottom: "Mconv6_stage4" top: "Mconv6_stage4" } layer { name: "Mconv7_stage4" type: "Convolution" bottom: "Mconv6_stage4" top: "Mconv7_stage4" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 22 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "concat_stage5" type: "Concat" bottom: "Mconv7_stage4" bottom: "conv5_3_CPM" top: "concat_stage5" concat_param { axis: 1 } } layer { name: "Mconv1_stage5" type: "Convolution" bottom: "concat_stage5" top: "Mconv1_stage5" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_2_stage5_1" type: "ReLU" bottom: "Mconv1_stage5" top: "Mconv1_stage5" } layer { name: "Mconv2_stage5" type: "Convolution" bottom: "Mconv1_stage5" top: "Mconv2_stage5" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_3_stage5_2" type: "ReLU" bottom: "Mconv2_stage5" top: "Mconv2_stage5" } layer { name: "Mconv3_stage5" type: "Convolution" bottom: "Mconv2_stage5" top: "Mconv3_stage5" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_4_stage5_3" type: "ReLU" bottom: "Mconv3_stage5" top: "Mconv3_stage5" } layer { name: "Mconv4_stage5" type: "Convolution" bottom: "Mconv3_stage5" top: "Mconv4_stage5" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_5_stage5_4" type: "ReLU" bottom: "Mconv4_stage5" top: "Mconv4_stage5" } layer { name: "Mconv5_stage5" type: "Convolution" bottom: "Mconv4_stage5" top: "Mconv5_stage5" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_6_stage5_5" type: "ReLU" bottom: "Mconv5_stage5" top: "Mconv5_stage5" } layer { name: "Mconv6_stage5" type: "Convolution" bottom: "Mconv5_stage5" top: "Mconv6_stage5" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_7_stage5_6" type: "ReLU" bottom: "Mconv6_stage5" top: "Mconv6_stage5" } layer { name: "Mconv7_stage5" type: "Convolution" bottom: "Mconv6_stage5" top: "Mconv7_stage5" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 22 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "concat_stage6" type: "Concat" bottom: "Mconv7_stage5" bottom: "conv5_3_CPM" top: "concat_stage6" concat_param { axis: 1 } } layer { name: "Mconv1_stage6" type: "Convolution" bottom: "concat_stage6" top: "Mconv1_stage6" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_2_stage6_1" type: "ReLU" bottom: "Mconv1_stage6" top: "Mconv1_stage6" } layer { name: "Mconv2_stage6" type: "Convolution" bottom: "Mconv1_stage6" top: "Mconv2_stage6" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_3_stage6_2" type: "ReLU" bottom: "Mconv2_stage6" top: "Mconv2_stage6" } layer { name: "Mconv3_stage6" type: "Convolution" bottom: "Mconv2_stage6" top: "Mconv3_stage6" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_4_stage6_3" type: "ReLU" bottom: "Mconv3_stage6" top: "Mconv3_stage6" } layer { name: "Mconv4_stage6" type: "Convolution" bottom: "Mconv3_stage6" top: "Mconv4_stage6" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_5_stage6_4" type: "ReLU" bottom: "Mconv4_stage6" top: "Mconv4_stage6" } layer { name: "Mconv5_stage6" type: "Convolution" bottom: "Mconv4_stage6" top: "Mconv5_stage6" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 3 kernel_size: 7 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_6_stage6_5" type: "ReLU" bottom: "Mconv5_stage6" top: "Mconv5_stage6" } layer { name: "Mconv6_stage6" type: "Convolution" bottom: "Mconv5_stage6" top: "Mconv6_stage6" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 128 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } } layer { name: "Mrelu1_7_stage6_6" type: "ReLU" bottom: "Mconv6_stage6" top: "Mconv6_stage6" } layer { name: "Mconv7_stage6" type: "Convolution" bottom: "Mconv6_stage6" # top: "Mconv7_stage6" top: "net_output" param { lr_mult: 4.0 decay_mult: 1 } param { lr_mult: 8.0 decay_mult: 0 } convolution_param { num_output: 22 pad: 0 kernel_size: 1 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" } dilation: 1 } }