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name: 'FCN' |
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input: 'data' |
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input_dim: 1 |
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input_dim: 3 |
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input_dim: 500 |
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input_dim: 500 |
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force_backward: true |
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layers { bottom: 'data' top: 'conv1_1' name: 'conv1_1' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 64 pad: 100 kernel_size: 3 } } |
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layers { bottom: 'conv1_1' top: 'conv1_1' name: 'relu1_1' type: RELU } |
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layers { bottom: 'conv1_1' top: 'conv1_2' name: 'conv1_2' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 64 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv1_2' top: 'conv1_2' name: 'relu1_2' type: RELU } |
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layers { name: 'pool1' bottom: 'conv1_2' top: 'pool1' type: POOLING |
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pooling_param { pool: MAX kernel_size: 2 stride: 2 } } |
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layers { name: 'conv2_1' bottom: 'pool1' top: 'conv2_1' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 128 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv2_1' top: 'conv2_1' name: 'relu2_1' type: RELU } |
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layers { bottom: 'conv2_1' top: 'conv2_2' name: 'conv2_2' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 128 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv2_2' top: 'conv2_2' name: 'relu2_2' type: RELU } |
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layers { bottom: 'conv2_2' top: 'pool2' name: 'pool2' type: POOLING |
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pooling_param { pool: MAX kernel_size: 2 stride: 2 } } |
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layers { bottom: 'pool2' top: 'conv3_1' name: 'conv3_1' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 256 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv3_1' top: 'conv3_1' name: 'relu3_1' type: RELU } |
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layers { bottom: 'conv3_1' top: 'conv3_2' name: 'conv3_2' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 256 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv3_2' top: 'conv3_2' name: 'relu3_2' type: RELU } |
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layers { bottom: 'conv3_2' top: 'conv3_3' name: 'conv3_3' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 256 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv3_3' top: 'conv3_3' name: 'relu3_3' type: RELU } |
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layers { bottom: 'conv3_3' top: 'pool3' name: 'pool3' type: POOLING |
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pooling_param { pool: MAX kernel_size: 2 stride: 2 } } |
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layers { bottom: 'pool3' top: 'conv4_1' name: 'conv4_1' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv4_1' top: 'conv4_1' name: 'relu4_1' type: RELU } |
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layers { bottom: 'conv4_1' top: 'conv4_2' name: 'conv4_2' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv4_2' top: 'conv4_2' name: 'relu4_2' type: RELU } |
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layers { bottom: 'conv4_2' top: 'conv4_3' name: 'conv4_3' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv4_3' top: 'conv4_3' name: 'relu4_3' type: RELU } |
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layers { bottom: 'conv4_3' top: 'pool4' name: 'pool4' type: POOLING |
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pooling_param { pool: MAX kernel_size: 2 stride: 2 } } |
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layers { bottom: 'pool4' top: 'conv5_1' name: 'conv5_1' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv5_1' top: 'conv5_1' name: 'relu5_1' type: RELU } |
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layers { bottom: 'conv5_1' top: 'conv5_2' name: 'conv5_2' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv5_2' top: 'conv5_2' name: 'relu5_2' type: RELU } |
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layers { bottom: 'conv5_2' top: 'conv5_3' name: 'conv5_3' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } } |
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layers { bottom: 'conv5_3' top: 'conv5_3' name: 'relu5_3' type: RELU } |
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layers { bottom: 'conv5_3' top: 'pool5' name: 'pool5' type: POOLING |
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pooling_param { pool: MAX kernel_size: 2 stride: 2 } } |
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layers { bottom: 'pool5' top: 'fc6' name: 'fc6' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE kernel_size: 7 num_output: 4096 } } |
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layers { bottom: 'fc6' top: 'fc6' name: 'relu6' type: RELU } |
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layers { bottom: 'fc6' top: 'fc6' name: 'drop6' type: DROPOUT |
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dropout_param { dropout_ratio: 0.5 } } |
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layers { bottom: 'fc6' top: 'fc7' name: 'fc7' type: CONVOLUTION |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE kernel_size: 1 num_output: 4096 } } |
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layers { bottom: 'fc7' top: 'fc7' name: 'relu7' type: RELU } |
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layers { bottom: 'fc7' top: 'fc7' name: 'drop7' type: DROPOUT |
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dropout_param { dropout_ratio: 0.5 } } |
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layers { name: 'score-fr' type: CONVOLUTION bottom: 'fc7' top: 'score' |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 21 kernel_size: 1 } } |
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layers { type: DECONVOLUTION name: 'score2' bottom: 'score' top: 'score2' |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { kernel_size: 4 stride: 2 num_output: 21 } } |
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layers { name: 'score-pool4' type: CONVOLUTION bottom: 'pool4' top: 'score-pool4' |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 21 kernel_size: 1 } } |
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layers { type: CROP name: 'crop' bottom: 'score-pool4' bottom: 'score2' |
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top: 'score-pool4c' } |
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layers { type: ELTWISE name: 'fuse' bottom: 'score2' bottom: 'score-pool4c' |
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top: 'score-fused' |
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eltwise_param { operation: SUM } } |
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layers { type: DECONVOLUTION name: 'score4' bottom: 'score-fused' |
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top: 'score4' |
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blobs_lr: 1 weight_decay: 1 |
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convolution_param { bias_term: false kernel_size: 4 stride: 2 num_output: 21 } } |
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layers { name: 'score-pool3' type: CONVOLUTION bottom: 'pool3' top: 'score-pool3' |
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blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 |
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convolution_param { engine: CAFFE num_output: 21 kernel_size: 1 } } |
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layers { type: CROP name: 'crop' bottom: 'score-pool3' bottom: 'score4' |
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top: 'score-pool3c' } |
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layers { type: ELTWISE name: 'fuse' bottom: 'score4' bottom: 'score-pool3c' |
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top: 'score-final' |
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eltwise_param { operation: SUM } } |
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layers { type: DECONVOLUTION name: 'upsample' |
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bottom: 'score-final' top: 'bigscore' |
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blobs_lr: 0 |
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convolution_param { bias_term: false num_output: 21 kernel_size: 16 stride: 8 } } |
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layers { type: CROP name: 'crop' bottom: 'bigscore' bottom: 'data' top: 'upscore' } |
Haven't the train_val.prototxt and solver.prototxt been made public yet?