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December 28, 2016 09:17
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deeplab_largeFOV_test
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| # VGG 16-layer network convolutional finetuning | |
| # Network modified to have smaller receptive field (128 pixels) | |
| # and smaller stride (8 pixels) when run in convolutional mode. | |
| # | |
| # In this model we also change max pooling size in the first 4 layers | |
| # from 2 to 3 while retaining stride = 2 | |
| # which makes it easier to exactly align responses at different layers. | |
| # | |
| name: "DeepLab-LargeFOV" | |
| layers { | |
| name: "data" | |
| type: IMAGE_SEG_DATA | |
| top: "data" | |
| top: "label" | |
| top: "data_dim" # used for CRF layer, otherwise not necessary | |
| image_data_param { | |
| root_folder: "exper/voc12/data" | |
| source: "exper/voc12/list/val.txt" | |
| batch_size: 1 | |
| has_label: false | |
| } | |
| transform_param { | |
| mean_value: 104.008 | |
| mean_value: 116.669 | |
| mean_value: 122.675 | |
| crop_size: 513 | |
| mirror: false | |
| } | |
| include: { phase: TEST } | |
| } | |
| ### NETWORK ### | |
| layers { | |
| bottom: "data" | |
| top: "conv1_1" | |
| name: "conv1_1" | |
| type: CONVOLUTION | |
| convolution_param { | |
| 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 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layers { | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| name: "relu1_2" | |
| type: RELU | |
| } | |
| layers { | |
| bottom: "conv1_2" | |
| top: "pool1" | |
| name: "pool1" | |
| type: POOLING | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| } | |
| } | |
| layers { | |
| bottom: "pool1" | |
| top: "conv2_1" | |
| name: "conv2_1" | |
| type: CONVOLUTION | |
| convolution_param { | |
| 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 | |
| convolution_param { | |
| 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: 3 | |
| stride: 2 | |
| pad: 1 | |
| } | |
| } | |
| layers { | |
| bottom: "pool2" | |
| top: "conv3_1" | |
| name: "conv3_1" | |
| type: CONVOLUTION | |
| convolution_param { | |
| 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 | |
| convolution_param { | |
| 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 | |
| convolution_param { | |
| 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: 3 | |
| stride: 2 | |
| pad: 1 | |
| } | |
| } | |
| layers { | |
| bottom: "pool3" | |
| top: "conv4_1" | |
| name: "conv4_1" | |
| type: CONVOLUTION | |
| convolution_param { | |
| 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 | |
| convolution_param { | |
| 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 | |
| convolution_param { | |
| 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: 3 | |
| pad: 1 | |
| #stride: 2 | |
| stride: 1 | |
| } | |
| } | |
| layers { | |
| bottom: "pool4" | |
| top: "conv5_1" | |
| name: "conv5_1" | |
| type: CONVOLUTION | |
| convolution_param { | |
| num_output: 512 | |
| #pad: 1 | |
| pad: 2 | |
| hole: 2 | |
| 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 | |
| convolution_param { | |
| num_output: 512 | |
| #pad: 1 | |
| pad: 2 | |
| hole: 2 | |
| 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 | |
| convolution_param { | |
| num_output: 512 | |
| #pad: 1 | |
| pad: 2 | |
| hole: 2 | |
| 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 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layers { | |
| bottom: "pool5" | |
| top: "pool5a" | |
| name: "pool5a" | |
| type: POOLING | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layers { | |
| bottom: "pool5a" | |
| top: "fc6" | |
| name: "fc6" | |
| type: CONVOLUTION | |
| strict_dim: false | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 12 | |
| hole: 12 | |
| kernel_size: 3 | |
| } | |
| } | |
| 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 | |
| strict_dim: false | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| } | |
| } | |
| 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 { | |
| bottom: "fc7" | |
| top: "fc8_exper/voc12" | |
| name: "fc8_exper/voc12" | |
| type: CONVOLUTION | |
| strict_dim: false | |
| convolution_param { | |
| num_output: 21 | |
| kernel_size: 1 | |
| } | |
| } | |
| layers { | |
| bottom: "fc8_exper/voc12" | |
| top: "fc8_interp" | |
| name: "fc8_interp" | |
| type: INTERP | |
| interp_param { | |
| zoom_factor: 8 | |
| } | |
| } | |
| layers { | |
| name: "fc8_mat" | |
| type: MAT_WRITE | |
| bottom: "fc8_interp" | |
| mat_write_param { | |
| prefix: "exper/voc12/features/DeepLab-LargeFOV/val/fc8/" | |
| source: "exper/voc12/list/val_id.txt" | |
| strip: 0 | |
| period: 1 | |
| } | |
| include: { phase: TEST } | |
| } | |
| layers { | |
| bottom: "fc8_interp" | |
| bottom: "data_dim" | |
| bottom: "data" | |
| top: "crf_inf" | |
| name: "crf" | |
| type: DENSE_CRF | |
| dense_crf_param { | |
| max_iter: 10 | |
| pos_w: 3 | |
| pos_xy_std: 3 | |
| bi_w: 5 | |
| bi_xy_std: 50 | |
| bi_rgb_std: 10 | |
| } | |
| include: { phase: TEST } | |
| } | |
| layers { | |
| name: "crf_mat" | |
| type: MAT_WRITE | |
| bottom: "crf_inf" | |
| mat_write_param { | |
| prefix: "exper/voc12/features/DeepLab-LargeFOV/val/crf/" | |
| source: "exper/voc12/list/val_id.txt" | |
| strip: 0 | |
| period: 1 | |
| } | |
| include: { phase: TEST } | |
| } | |
| layers { | |
| bottom: "label" | |
| name: "silence" | |
| type: SILENCE | |
| include: { phase: TEST } | |
| } |
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