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January 23, 2018 12:16
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multi_patch
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| name: "multi_patch_layers" | |
| layer { | |
| name: "left_eye" | |
| type: "Input" | |
| top: "left_eye" | |
| input_param { shape: { dim: 128 dim: 64 dim: 30 dim: 30 } } | |
| } | |
| layer { | |
| name: "right_eye" | |
| type: "Input" | |
| top: "right_eye" | |
| input_param { shape: { dim: 128 dim: 64 dim: 30 dim: 30 } } | |
| } | |
| layer { | |
| name: "nip_top" | |
| type: "Input" | |
| top: "nip_top" | |
| input_param { shape: { dim: 128 dim: 64 dim: 30 dim: 30 } } | |
| } | |
| layer { | |
| name: "left_mouth" | |
| type: "Input" | |
| top: "left_mouth" | |
| input_param { shape: { dim: 128 dim: 64 dim: 30 dim: 36 } } | |
| } | |
| layer { | |
| name: "right_mouth" | |
| type: "Input" | |
| top: "right_mouth" | |
| input_param { shape: { dim: 128 dim: 64 dim: 14 dim: 14 } } | |
| } | |
| layer { | |
| name: "data" | |
| type: "ImageData" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| scale: 0.0078125 | |
| mirror: true | |
| } | |
| image_data_param { | |
| root_folder : "/media/zf/44B47817B4780E24/datasets/facial_expression/AffectNet/Manually_Annotated_Images/" | |
| source: "manully_training.txt" | |
| batch_size: 128 | |
| shuffle: true | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "ImageData" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| scale: 0.0078125 | |
| mirror: true | |
| } | |
| image_data_param { | |
| root_folder : "/media/zf/44B47817B4780E24/datasets/facial_expression/AffectNet/Manually_Annotated_Images/" | |
| source: "manully_validatation.txt" | |
| batch_size: 128 | |
| shuffle: true | |
| } | |
| } | |
| layers { | |
| bottom: "data" | |
| type: "Convolution" | |
| top: "conv1_1" | |
| name: "conv1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu1_1" | |
| type: "ReLU" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| } | |
| layers { | |
| name: "conv1_2" | |
| type: "Convolution" | |
| bottom: "conv1_1" | |
| top: "conv1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu1_2" | |
| type: "ReLU" | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| } | |
| layers { | |
| name: "pool1" | |
| bottom: "conv1_2" | |
| type: "Pooling" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| ######=========CROP_LEFT_EYE============###### | |
| layer { | |
| name: "crop_left_eye" | |
| type: "Crop" | |
| bottom: "pool1" | |
| bottom: "left_eye" | |
| top: "crop_left_eye" | |
| crop_param { | |
| axis: 2 | |
| offset: 36 | |
| offset: 20 | |
| } | |
| } | |
| layer { | |
| name: "le_conv2_1" | |
| type: "Convolution" | |
| bottom: "crop_left_eye" | |
| top: "le_conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "le_relu2_1" | |
| type: "ReLU" | |
| bottom: "le_conv2_1" | |
| top: "le_conv2_1" | |
| } | |
| layer { | |
| name: "le_conv2_2" | |
| type: "Convolution" | |
| bottom: "le_conv2_1" | |
| top: "le_conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "le_relu2_2" | |
| type: "ReLU" | |
| bottom: "le_conv2_2" | |
| top: "le_conv2_2" | |
| } | |
| layer { | |
| name: "le_pool2" | |
| type: "Pooling" | |
| bottom: "le_conv2_2" | |
| top: "le_pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "le_ip1" | |
| type: "InnerProduct" | |
| bottom: "le_pool2" | |
| top: "le_ip1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| } | |
| inner_product_param { | |
| num_output: 512 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "le_relu1" | |
| type: "ReLU" | |
| bottom: "le_ip1" | |
| top: "le_ip1" | |
| } | |
| ######=========CROP_RIGHT_EYE============###### | |
| layer { | |
| name: "crop_right_eye" | |
| type: "Crop" | |
| bottom: "pool1" | |
| bottom: "right_eye" | |
| top: "crop_right_eye" | |
| crop_param { | |
| axis: 2 | |
| offset: 10 | |
| offset: 20 | |
| } | |
| } | |
| layer { | |
| name: "re_conv2_1" | |
| type: "Convolution" | |
| bottom: "crop_right_eye" | |
| top: "re_conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "re_relu2_1" | |
| type: "ReLU" | |
| bottom: "re_conv2_1" | |
| top: "re_conv2_1" | |
| } | |
| layer { | |
| name: "re_conv2_2" | |
| type: "Convolution" | |
| bottom: "re_conv2_1" | |
| top: "re_conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "re_relu2_2" | |
| type: "ReLU" | |
| bottom: "re_conv2_2" | |
| top: "re_conv2_2" | |
| } | |
| layer { | |
| name: "re_pool2" | |
| type: "Pooling" | |
| bottom: "re_conv2_2" | |
| top: "re_pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "re_ip1" | |
| type: "InnerProduct" | |
| bottom: "re_pool2" | |
| top: "re_ip1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| } | |
| inner_product_param { | |
| num_output: 512 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "re_relu1" | |
| type: "ReLU" | |
| bottom: "re_ip1" | |
| top: "re_ip1" | |
| } | |
| ######=========CROP_TOP_NIP============###### | |
| layer { | |
| name: "crop_nip_top" | |
| type: "Crop" | |
| bottom: "pool1" | |
| bottom: "nip_top" | |
| top: "crop_nip_top" | |
| crop_param { | |
| axis: 2 | |
| offset: 20 | |
| offset: 32 | |
| } | |
| } | |
| layer { | |
| name: "nt_conv2_1" | |
| type: "Convolution" | |
| bottom: "crop_nip_top" | |
| top: "nt_conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "nt_relu2_1" | |
| type: "ReLU" | |
| bottom: "nt_conv2_1" | |
| top: "nt_conv2_1" | |
| } | |
| layer { | |
| name: "nt_conv2_2" | |
| type: "Convolution" | |
| bottom: "nt_conv2_1" | |
| top: "nt_conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "nt_relu2_2" | |
| type: "ReLU" | |
| bottom: "nt_conv2_2" | |
| top: "nt_conv2_2" | |
| } | |
| layer { | |
| name: "nt_pool2" | |
| type: "Pooling" | |
| bottom: "nt_conv2_2" | |
| top: "nt_pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "nt_ip1" | |
| type: "InnerProduct" | |
| bottom: "nt_pool2" | |
| top: "nt_ip1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| } | |
| inner_product_param { | |
| num_output: 512 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "nt_relu1" | |
| type: "ReLU" | |
| bottom: "nt_ip1" | |
| top: "nt_ip1" | |
| } | |
| ######=========CROP_LEFT_MOUTH============###### | |
| layer { | |
| name: "crop_left_mouth" | |
| type: "Crop" | |
| bottom: "pool1" | |
| bottom: "left_mouth" | |
| top: "crop_left_mouth" | |
| crop_param { | |
| axis: 2 | |
| offset: 10 | |
| offset: 42 | |
| } | |
| } | |
| layer { | |
| name: "lm_conv2_1" | |
| type: "Convolution" | |
| bottom: "crop_left_mouth" | |
| top: "lm_conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "lm_relu2_1" | |
| type: "ReLU" | |
| bottom: "lm_conv2_1" | |
| top: "lm_conv2_1" | |
| } | |
| layer { | |
| name: "lm_conv2_2" | |
| type: "Convolution" | |
| bottom: "lm_conv2_1" | |
| top: "lm_conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "lm_relu2_2" | |
| type: "ReLU" | |
| bottom: "lm_conv2_2" | |
| top: "lm_conv2_2" | |
| } | |
| layer { | |
| name: "lm_pool2" | |
| type: "Pooling" | |
| bottom: "lm_conv2_2" | |
| top: "lm_pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "lm_ip1" | |
| type: "InnerProduct" | |
| bottom: "lm_pool2" | |
| top: "lm_ip1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| } | |
| inner_product_param { | |
| num_output: 512 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "lm_relu1" | |
| type: "ReLU" | |
| bottom: "lm_ip1" | |
| top: "lm_ip1" | |
| } | |
| ######=========CROP_RIGHT_MOUTH============###### | |
| layer { | |
| name: "crop_right_mouth" | |
| type: "Crop" | |
| bottom: "pool1" | |
| bottom: "right_mouth" | |
| top: "crop_right_mouth" | |
| crop_param { | |
| axis: 2 | |
| offset: 10 | |
| offset: 42 | |
| } | |
| } | |
| layer { | |
| name: "rm_conv2_1" | |
| type: "Convolution" | |
| bottom: "crop_right_mouth" | |
| top: "rm_conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "rm_relu2_1" | |
| type: "ReLU" | |
| bottom: "rm_conv2_1" | |
| top: "rm_conv2_1" | |
| } | |
| layer { | |
| name: "rm_conv2_2" | |
| type: "Convolution" | |
| bottom: "rm_conv2_1" | |
| top: "rm_conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "rm_relu2_2" | |
| type: "ReLU" | |
| bottom: "rm_conv2_2" | |
| top: "rm_conv2_2" | |
| } | |
| layer { | |
| name: "rm_pool2" | |
| type: "Pooling" | |
| bottom: "rm_conv2_2" | |
| top: "rm_pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "rm_ip1" | |
| type: "InnerProduct" | |
| bottom: "rm_pool2" | |
| top: "rm_ip1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| } | |
| inner_product_param { | |
| num_output: 512 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "rm_relu1" | |
| type: "ReLU" | |
| bottom: "rm_ip1" | |
| top: "rm_ip1" | |
| } | |
| layer { | |
| name: "concat_ip" | |
| type: "Concat" | |
| bottom:"le_ip1" | |
| bottom:"re_ip1" | |
| bottom:"nt_ip1" | |
| bottom:"lm_ip1" | |
| bottom:"rm_ip1" | |
| top: "concat_ip" | |
| } | |
| layer { | |
| name: "fc6" | |
| type: "InnerProduct" | |
| bottom: "concat_ip" | |
| top: "fc6" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 7 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "softmax_loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "fc6" | |
| bottom: "label" | |
| top: "softmax_loss" | |
| } | |
| layer { | |
| name: "accuracy_1" | |
| type: "Accuracy" | |
| bottom: "fc6" | |
| bottom: "label" | |
| top: "accuracy_1" | |
| } | |
| layer { | |
| name: "accuracy_2" | |
| type: "Accuracy" | |
| bottom: "fc6" | |
| bottom: "label" | |
| top: "accuracy_2" | |
| } | |
| layer { | |
| name: "accuracy_3" | |
| type: "Accuracy" | |
| bottom: "fc6" | |
| bottom: "label" | |
| top: "accuracy_3" | |
| } |
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