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October 15, 2018 00:53
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| name: "MobileNet-YOLO" | |
| layer { | |
| name: "data" | |
| type: "AnnotatedData" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| scale: 0.007843 | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| force_color: true | |
| resize_param { | |
| prob: 1.0 | |
| resize_mode: WARP | |
| height: 416 | |
| width: 416 | |
| interp_mode: LINEAR | |
| } | |
| } | |
| data_param { | |
| source: "examples/coco/coco_minival_lmdb" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| annotated_data_param { | |
| batch_sampler { | |
| } | |
| label_map_file: "data/coco/labelmap_coco.prototxt" | |
| } | |
| } | |
| layer { | |
| name: "conv0" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv0" | |
| top: "conv0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv0/scale" | |
| type: "Scale" | |
| bottom: "conv0" | |
| top: "conv0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv0/relu" | |
| type: "ReLU" | |
| bottom: "conv0" | |
| top: "conv0" | |
| } | |
| layer { | |
| name: "conv1/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv0" | |
| top: "conv1/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 32 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv1/dw" | |
| top: "conv1/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv1/dw/scale" | |
| type: "Scale" | |
| bottom: "conv1/dw" | |
| top: "conv1/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv1/dw" | |
| top: "conv1/dw" | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "conv1/dw" | |
| top: "conv1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "conv1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv1/scale" | |
| type: "Scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/relu" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "conv2/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv1" | |
| top: "conv2/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 64 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2/dw" | |
| top: "conv2/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2/dw/scale" | |
| type: "Scale" | |
| bottom: "conv2/dw" | |
| top: "conv2/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv2/dw" | |
| top: "conv2/dw" | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "conv2/dw" | |
| top: "conv2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2" | |
| top: "conv2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2/scale" | |
| type: "Scale" | |
| bottom: "conv2" | |
| top: "conv2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/relu" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| } | |
| layer { | |
| name: "conv3/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv2" | |
| top: "conv3/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 128 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3/dw" | |
| top: "conv3/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3/dw/scale" | |
| type: "Scale" | |
| bottom: "conv3/dw" | |
| top: "conv3/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv3/dw" | |
| top: "conv3/dw" | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "conv3/dw" | |
| top: "conv3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3" | |
| top: "conv3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3/scale" | |
| type: "Scale" | |
| bottom: "conv3" | |
| top: "conv3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3/relu" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| } | |
| layer { | |
| name: "conv4/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv3" | |
| top: "conv4/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 128 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4/dw" | |
| top: "conv4/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv4/dw/scale" | |
| type: "Scale" | |
| bottom: "conv4/dw" | |
| top: "conv4/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv4/dw" | |
| top: "conv4/dw" | |
| } | |
| layer { | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv4/dw" | |
| top: "conv4" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4" | |
| top: "conv4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv4/scale" | |
| type: "Scale" | |
| bottom: "conv4" | |
| top: "conv4" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4/relu" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| } | |
| layer { | |
| name: "conv5/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4" | |
| top: "conv5/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5/dw" | |
| top: "conv5/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv5/dw/scale" | |
| type: "Scale" | |
| bottom: "conv5/dw" | |
| top: "conv5/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv5/dw" | |
| top: "conv5/dw" | |
| } | |
| layer { | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv5/dw" | |
| top: "conv5" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5" | |
| top: "conv5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv5/scale" | |
| type: "Scale" | |
| bottom: "conv5" | |
| top: "conv5" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5/relu" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| } | |
| layer { | |
| name: "conv6/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv5" | |
| top: "conv6/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 256 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6/dw" | |
| top: "conv6/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv6/dw/scale" | |
| type: "Scale" | |
| bottom: "conv6/dw" | |
| top: "conv6/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv6/dw" | |
| top: "conv6/dw" | |
| } | |
| layer { | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "conv6/dw" | |
| top: "conv6" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6" | |
| top: "conv6" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv6/scale" | |
| type: "Scale" | |
| bottom: "conv6" | |
| top: "conv6" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6/relu" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| } | |
| layer { | |
| name: "conv7/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6" | |
| top: "conv7/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv7/dw" | |
| top: "conv7/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv7/dw/scale" | |
| type: "Scale" | |
| bottom: "conv7/dw" | |
| top: "conv7/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv7/dw" | |
| top: "conv7/dw" | |
| } | |
| layer { | |
| name: "conv7" | |
| type: "Convolution" | |
| bottom: "conv7/dw" | |
| top: "conv7" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7/bn" | |
| type: "BatchNorm" | |
| bottom: "conv7" | |
| top: "conv7" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv7/scale" | |
| type: "Scale" | |
| bottom: "conv7" | |
| top: "conv7" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7/relu" | |
| type: "ReLU" | |
| bottom: "conv7" | |
| top: "conv7" | |
| } | |
| layer { | |
| name: "conv8/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv7" | |
| top: "conv8/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv8/dw" | |
| top: "conv8/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv8/dw/scale" | |
| type: "Scale" | |
| bottom: "conv8/dw" | |
| top: "conv8/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv8/dw" | |
| top: "conv8/dw" | |
| } | |
| layer { | |
| name: "conv8" | |
| type: "Convolution" | |
| bottom: "conv8/dw" | |
| top: "conv8" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8/bn" | |
| type: "BatchNorm" | |
| bottom: "conv8" | |
| top: "conv8" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv8/scale" | |
| type: "Scale" | |
| bottom: "conv8" | |
| top: "conv8" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8/relu" | |
| type: "ReLU" | |
| bottom: "conv8" | |
| top: "conv8" | |
| } | |
| layer { | |
| name: "conv9/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv8" | |
| top: "conv9/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv9/dw" | |
| top: "conv9/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv9/dw/scale" | |
| type: "Scale" | |
| bottom: "conv9/dw" | |
| top: "conv9/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv9/dw" | |
| top: "conv9/dw" | |
| } | |
| layer { | |
| name: "conv9" | |
| type: "Convolution" | |
| bottom: "conv9/dw" | |
| top: "conv9" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9/bn" | |
| type: "BatchNorm" | |
| bottom: "conv9" | |
| top: "conv9" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv9/scale" | |
| type: "Scale" | |
| bottom: "conv9" | |
| top: "conv9" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9/relu" | |
| type: "ReLU" | |
| bottom: "conv9" | |
| top: "conv9" | |
| } | |
| layer { | |
| name: "conv10/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv9" | |
| top: "conv10/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv10/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv10/dw" | |
| top: "conv10/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv10/dw/scale" | |
| type: "Scale" | |
| bottom: "conv10/dw" | |
| top: "conv10/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv10/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv10/dw" | |
| top: "conv10/dw" | |
| } | |
| layer { | |
| name: "conv10" | |
| type: "Convolution" | |
| bottom: "conv10/dw" | |
| top: "conv10" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv10/bn" | |
| type: "BatchNorm" | |
| bottom: "conv10" | |
| top: "conv10" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv10/scale" | |
| type: "Scale" | |
| bottom: "conv10" | |
| top: "conv10" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv10/relu" | |
| type: "ReLU" | |
| bottom: "conv10" | |
| top: "conv10" | |
| } | |
| layer { | |
| name: "conv11/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv10" | |
| top: "conv11/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv11/dw" | |
| top: "conv11/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv11/dw/scale" | |
| type: "Scale" | |
| bottom: "conv11/dw" | |
| top: "conv11/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv11/dw" | |
| top: "conv11/dw" | |
| } | |
| layer { | |
| name: "conv11" | |
| type: "Convolution" | |
| bottom: "conv11/dw" | |
| top: "conv11" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11/bn" | |
| type: "BatchNorm" | |
| bottom: "conv11" | |
| top: "conv11" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv11/scale" | |
| type: "Scale" | |
| bottom: "conv11" | |
| top: "conv11" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11/relu" | |
| type: "ReLU" | |
| bottom: "conv11" | |
| top: "conv11" | |
| } | |
| layer { | |
| name: "conv12/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv11" | |
| top: "conv12/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv12/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv12/dw" | |
| top: "conv12/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv12/dw/scale" | |
| type: "Scale" | |
| bottom: "conv12/dw" | |
| top: "conv12/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv12/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv12/dw" | |
| top: "conv12/dw" | |
| } | |
| layer { | |
| name: "conv12" | |
| type: "Convolution" | |
| bottom: "conv12/dw" | |
| top: "conv12" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv12/bn" | |
| type: "BatchNorm" | |
| bottom: "conv12" | |
| top: "conv12" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv12/scale" | |
| type: "Scale" | |
| bottom: "conv12" | |
| top: "conv12" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv12/relu" | |
| type: "ReLU" | |
| bottom: "conv12" | |
| top: "conv12" | |
| } | |
| layer { | |
| name: "conv13/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv12" | |
| top: "conv13/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 1024 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv13/dw" | |
| top: "conv13/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv13/dw/scale" | |
| type: "Scale" | |
| bottom: "conv13/dw" | |
| top: "conv13/dw" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv13/dw" | |
| top: "conv13/dw" | |
| } | |
| layer { | |
| name: "conv13" | |
| type: "Convolution" | |
| bottom: "conv13/dw" | |
| top: "conv13" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13/bn" | |
| type: "BatchNorm" | |
| bottom: "conv13" | |
| top: "conv13" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv13/scale" | |
| type: "Scale" | |
| bottom: "conv13" | |
| top: "conv13" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13/relu" | |
| type: "ReLU" | |
| bottom: "conv13" | |
| top: "conv13" | |
| } | |
| layer { | |
| name: "conv16/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv13" | |
| top: "conv16/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 1024 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv16/dw" | |
| top: "conv16/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv16/dw/scale" | |
| type: "Scale" | |
| bottom: "conv16/dw" | |
| top: "conv16/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv16/dw" | |
| top: "conv16/dw" | |
| } | |
| layer { | |
| name: "conv16" | |
| type: "Convolution" | |
| bottom: "conv16/dw" | |
| top: "conv16" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16/bn" | |
| type: "BatchNorm" | |
| bottom: "conv16" | |
| top: "conv16" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv16/scale" | |
| type: "Scale" | |
| bottom: "conv16" | |
| top: "conv16" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16/relu" | |
| type: "ReLU" | |
| bottom: "conv16" | |
| top: "conv16" | |
| } | |
| layer { | |
| name: "upsample" | |
| type: "Deconvolution" | |
| bottom: "conv16" | |
| top: "upsample" | |
| param { lr_mult: 0 decay_mult: 0 } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 4 stride: 2 pad: 1 | |
| group: 512 | |
| weight_filler: { type: "bilinear" } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| name: "conv17/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv11" | |
| top: "conv17/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv17/dw" | |
| top: "conv17/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv17/dw/scale" | |
| type: "Scale" | |
| bottom: "conv17/dw" | |
| top: "conv17/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv17/dw" | |
| top: "conv17/dw" | |
| } | |
| layer { | |
| name: "conv17" | |
| type: "Convolution" | |
| bottom: "conv17/dw" | |
| top: "conv17" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17/bn" | |
| type: "BatchNorm" | |
| bottom: "conv17" | |
| top: "conv17" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv17/scale" | |
| type: "Scale" | |
| bottom: "conv17" | |
| top: "conv17" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17/relu" | |
| type: "ReLU" | |
| bottom: "conv17" | |
| top: "conv17" | |
| } | |
| layer { | |
| name: "conv17/sum" | |
| type: "Eltwise" | |
| bottom: "conv17" | |
| bottom: "upsample" | |
| top: "conv17/sum" | |
| } | |
| layer { | |
| name: "conv18/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv17/sum" | |
| top: "conv18/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv18/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv18/dw" | |
| top: "conv18/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv18/dw/scale" | |
| type: "Scale" | |
| bottom: "conv18/dw" | |
| top: "conv18/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv18/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv18/dw" | |
| top: "conv18/dw" | |
| } | |
| layer { | |
| name: "conv18" | |
| type: "Convolution" | |
| bottom: "conv18/dw" | |
| top: "conv18" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv18/bn" | |
| type: "BatchNorm" | |
| bottom: "conv18" | |
| top: "conv18" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv18/scale" | |
| type: "Scale" | |
| bottom: "conv18" | |
| top: "conv18" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv18/relu" | |
| type: "ReLU" | |
| bottom: "conv18" | |
| top: "conv18" | |
| } | |
| layer { | |
| name: "conv23" | |
| type: "Convolution" | |
| bottom: "conv16" | |
| top: "conv23" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 255 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv24" | |
| type: "Convolution" | |
| bottom: "conv18" | |
| top: "conv24" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 255 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "detection_out" | |
| type: "Yolov3DetectionOutput" | |
| bottom: "conv23" | |
| bottom: "conv24" | |
| top: "detection_out" | |
| include { | |
| phase: TEST | |
| } | |
| yolov3_detection_output_param { | |
| confidence_threshold: 0.001 | |
| nms_threshold: 0.55 | |
| num_classes: 80 | |
| #10,14, 23,27, 37,58, 81,82, 135,169, 344,319 | |
| biases: 10 | |
| biases: 14 | |
| biases: 23 | |
| biases: 27 | |
| biases: 37 | |
| biases: 58 | |
| biases: 81 | |
| biases: 82 | |
| biases: 135 | |
| biases: 169 | |
| biases: 344 | |
| biases: 319 | |
| mask:3 | |
| mask:4 | |
| mask:5 | |
| mask:0 | |
| mask:1 | |
| mask:2 | |
| anchors_scale:32 | |
| anchors_scale:16 | |
| mask_group_num:2 | |
| } | |
| } | |
| layer { | |
| name: "detection_eval" | |
| type: "DetectionEvaluate" | |
| bottom: "detection_out" | |
| bottom: "label" | |
| top: "detection_eval" | |
| include { | |
| phase: TEST | |
| } | |
| detection_evaluate_param { | |
| num_classes: 81 | |
| background_label_id: 0 | |
| overlap_threshold: 0.5 | |
| evaluate_difficult_gt: false | |
| } | |
| } | |
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