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May 25, 2018 02:27
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MobileNetv2-YOLOv2 prototxt
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| name: "MobileNetv2-YOLOv2Loss" | |
| layer { | |
| name: "data" | |
| type: "AnnotatedData" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| scale: 0.007843 | |
| mirror: true | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| mean_value: 127.5 | |
| resize_param { | |
| prob: 1.0 | |
| resize_mode: WARP | |
| height: 416 | |
| width: 416 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| emit_constraint { | |
| emit_type: CENTER | |
| } | |
| distort_param { | |
| brightness_prob: 0.5 | |
| brightness_delta: 32.0 | |
| contrast_prob: 0.5 | |
| contrast_lower: 0.5 | |
| contrast_upper: 1.5 | |
| hue_prob: 0.5 | |
| hue_delta: 18.0 | |
| saturation_prob: 0.5 | |
| saturation_lower: 0.5 | |
| saturation_upper: 1.5 | |
| random_order_prob: 0.0 | |
| } | |
| expand_param { | |
| prob: 0.2 | |
| max_expand_ratio: 1.2 | |
| } | |
| } | |
| data_param { | |
| source: "examples/VOC0712/VOC0712_trainval_lmdb" | |
| batch_size: 12 | |
| backend: LMDB | |
| } | |
| annotated_data_param { | |
| yolo_data_type : 1 | |
| batch_sampler { | |
| max_sample: 1 | |
| max_trials: 1 | |
| use_original_image: 1 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.8 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 1 | |
| max_aspect_ratio: 1 | |
| } | |
| sample_constraint { | |
| min_jaccard_overlap: 0.8 | |
| max_jaccard_overlap: 1.0 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.8 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 1 | |
| max_aspect_ratio: 1 | |
| } | |
| sample_constraint { | |
| min_jaccard_overlap: 0.9 | |
| max_jaccard_overlap: 1.0 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| label_map_file: "data/VOC0712/labelmap_voc.prototxt" | |
| } | |
| } | |
| layer { | |
| name: "Conv" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "Conv" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Conv/bn" | |
| type: "BatchNorm" | |
| bottom: "Conv" | |
| top: "Conv" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "Conv/scale" | |
| type: "Scale" | |
| bottom: "Conv" | |
| top: "Conv" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Conv/relu" | |
| type: "ReLU6" | |
| bottom: "Conv" | |
| top: "Conv" | |
| } | |
| layer { | |
| name: "conv/depthwise" | |
| type: "Convolution" | |
| bottom: "Conv" | |
| top: "conv/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 32 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv/depthwise" | |
| top: "conv/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv/depthwise" | |
| top: "conv/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv/depthwise" | |
| top: "conv/depthwise" | |
| } | |
| layer { | |
| name: "conv/project" | |
| type: "Convolution" | |
| bottom: "conv/depthwise" | |
| top: "conv/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv/project" | |
| top: "conv/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv/project/scale" | |
| type: "Scale" | |
| bottom: "conv/project" | |
| top: "conv/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_1/expand" | |
| type: "Convolution" | |
| bottom: "conv/project" | |
| top: "conv_1/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_1/expand" | |
| top: "conv_1/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_1/expand" | |
| top: "conv_1/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_1/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_1/expand" | |
| top: "conv_1/expand" | |
| } | |
| layer { | |
| name: "conv_1/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_1/expand" | |
| top: "conv_1/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 96 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_1/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_1/depthwise" | |
| top: "conv_1/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_1/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_1/depthwise" | |
| top: "conv_1/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_1/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_1/depthwise" | |
| top: "conv_1/depthwise" | |
| } | |
| layer { | |
| name: "conv_1/project" | |
| type: "Convolution" | |
| bottom: "conv_1/depthwise" | |
| top: "conv_1/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_1/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_1/project" | |
| top: "conv_1/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_1/project/scale" | |
| type: "Scale" | |
| bottom: "conv_1/project" | |
| top: "conv_1/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_2/expand" | |
| type: "Convolution" | |
| bottom: "conv_1/project" | |
| top: "conv_2/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_2/expand" | |
| top: "conv_2/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_2/expand" | |
| top: "conv_2/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_2/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_2/expand" | |
| top: "conv_2/expand" | |
| } | |
| layer { | |
| name: "conv_2/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_2/expand" | |
| top: "conv_2/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 144 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_2/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_2/depthwise" | |
| top: "conv_2/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_2/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_2/depthwise" | |
| top: "conv_2/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_2/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_2/depthwise" | |
| top: "conv_2/depthwise" | |
| } | |
| layer { | |
| name: "conv_2/project" | |
| type: "Convolution" | |
| bottom: "conv_2/depthwise" | |
| top: "conv_2/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_2/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_2/project" | |
| top: "conv_2/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_2/project/scale" | |
| type: "Scale" | |
| bottom: "conv_2/project" | |
| top: "conv_2/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_2/sum" | |
| type: "Eltwise" | |
| bottom: "conv_1/project" | |
| bottom: "conv_2/project" | |
| top: "conv_2" | |
| } | |
| layer { | |
| name: "conv_3/expand" | |
| type: "Convolution" | |
| bottom: "conv_2" | |
| top: "conv_3/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_3/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_3/expand" | |
| top: "conv_3/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_3/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_3/expand" | |
| top: "conv_3/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_3/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_3/expand" | |
| top: "conv_3/expand" | |
| } | |
| layer { | |
| name: "conv_3/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_3/expand" | |
| top: "conv_3/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 144 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_3/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_3/depthwise" | |
| top: "conv_3/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_3/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_3/depthwise" | |
| top: "conv_3/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_3/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_3/depthwise" | |
| top: "conv_3/depthwise" | |
| } | |
| layer { | |
| name: "conv_3/project" | |
| type: "Convolution" | |
| bottom: "conv_3/depthwise" | |
| top: "conv_3/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_3/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_3/project" | |
| top: "conv_3/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_3/project/scale" | |
| type: "Scale" | |
| bottom: "conv_3/project" | |
| top: "conv_3/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_4/expand" | |
| type: "Convolution" | |
| bottom: "conv_3/project" | |
| top: "conv_4/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_4/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_4/expand" | |
| top: "conv_4/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_4/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_4/expand" | |
| top: "conv_4/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_4/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_4/expand" | |
| top: "conv_4/expand" | |
| } | |
| layer { | |
| name: "conv_4/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_4/expand" | |
| top: "conv_4/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_4/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_4/depthwise" | |
| top: "conv_4/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_4/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_4/depthwise" | |
| top: "conv_4/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_4/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_4/depthwise" | |
| top: "conv_4/depthwise" | |
| } | |
| layer { | |
| name: "conv_4/project" | |
| type: "Convolution" | |
| bottom: "conv_4/depthwise" | |
| top: "conv_4/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_4/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_4/project" | |
| top: "conv_4/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_4/project/scale" | |
| type: "Scale" | |
| bottom: "conv_4/project" | |
| top: "conv_4/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_4/sum" | |
| type: "Eltwise" | |
| bottom: "conv_3/project" | |
| bottom: "conv_4/project" | |
| top: "conv_4" | |
| } | |
| layer { | |
| name: "conv_5/expand" | |
| type: "Convolution" | |
| bottom: "conv_4" | |
| top: "conv_5/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_5/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_5/expand" | |
| top: "conv_5/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_5/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_5/expand" | |
| top: "conv_5/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_5/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_5/expand" | |
| top: "conv_5/expand" | |
| } | |
| layer { | |
| name: "conv_5/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_5/expand" | |
| top: "conv_5/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_5/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_5/depthwise" | |
| top: "conv_5/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_5/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_5/depthwise" | |
| top: "conv_5/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_5/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_5/depthwise" | |
| top: "conv_5/depthwise" | |
| } | |
| layer { | |
| name: "conv_5/project" | |
| type: "Convolution" | |
| bottom: "conv_5/depthwise" | |
| top: "conv_5/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_5/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_5/project" | |
| top: "conv_5/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_5/project/scale" | |
| type: "Scale" | |
| bottom: "conv_5/project" | |
| top: "conv_5/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_5/sum" | |
| type: "Eltwise" | |
| bottom: "conv_4" | |
| bottom: "conv_5/project" | |
| top: "conv_5" | |
| } | |
| layer { | |
| name: "conv_6/expand" | |
| type: "Convolution" | |
| bottom: "conv_5" | |
| top: "conv_6/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_6/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_6/expand" | |
| top: "conv_6/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_6/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_6/expand" | |
| top: "conv_6/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_6/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_6/expand" | |
| top: "conv_6/expand" | |
| } | |
| layer { | |
| name: "conv_6/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_6/expand" | |
| top: "conv_6/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 192 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_6/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_6/depthwise" | |
| top: "conv_6/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_6/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_6/depthwise" | |
| top: "conv_6/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_6/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_6/depthwise" | |
| top: "conv_6/depthwise" | |
| } | |
| layer { | |
| name: "conv_6/project" | |
| type: "Convolution" | |
| bottom: "conv_6/depthwise" | |
| top: "conv_6/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_6/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_6/project" | |
| top: "conv_6/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_6/project/scale" | |
| type: "Scale" | |
| bottom: "conv_6/project" | |
| top: "conv_6/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_7/expand" | |
| type: "Convolution" | |
| bottom: "conv_6/project" | |
| top: "conv_7/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_7/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_7/expand" | |
| top: "conv_7/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_7/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_7/expand" | |
| top: "conv_7/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_7/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_7/expand" | |
| top: "conv_7/expand" | |
| } | |
| layer { | |
| name: "conv_7/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_7/expand" | |
| top: "conv_7/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_7/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_7/depthwise" | |
| top: "conv_7/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_7/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_7/depthwise" | |
| top: "conv_7/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_7/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_7/depthwise" | |
| top: "conv_7/depthwise" | |
| } | |
| layer { | |
| name: "conv_7/project" | |
| type: "Convolution" | |
| bottom: "conv_7/depthwise" | |
| top: "conv_7/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_7/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_7/project" | |
| top: "conv_7/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_7/project/scale" | |
| type: "Scale" | |
| bottom: "conv_7/project" | |
| top: "conv_7/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_7/sum" | |
| type: "Eltwise" | |
| bottom: "conv_6/project" | |
| bottom: "conv_7/project" | |
| top: "conv_7" | |
| } | |
| layer { | |
| name: "conv_8/expand" | |
| type: "Convolution" | |
| bottom: "conv_7" | |
| top: "conv_8/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_8/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_8/expand" | |
| top: "conv_8/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_8/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_8/expand" | |
| top: "conv_8/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_8/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_8/expand" | |
| top: "conv_8/expand" | |
| } | |
| layer { | |
| name: "conv_8/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_8/expand" | |
| top: "conv_8/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_8/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_8/depthwise" | |
| top: "conv_8/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_8/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_8/depthwise" | |
| top: "conv_8/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_8/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_8/depthwise" | |
| top: "conv_8/depthwise" | |
| } | |
| layer { | |
| name: "conv_8/project" | |
| type: "Convolution" | |
| bottom: "conv_8/depthwise" | |
| top: "conv_8/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_8/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_8/project" | |
| top: "conv_8/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_8/project/scale" | |
| type: "Scale" | |
| bottom: "conv_8/project" | |
| top: "conv_8/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_8/sum" | |
| type: "Eltwise" | |
| bottom: "conv_7" | |
| bottom: "conv_8/project" | |
| top: "conv_8" | |
| } | |
| layer { | |
| name: "conv_9/expand" | |
| type: "Convolution" | |
| bottom: "conv_8" | |
| top: "conv_9/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_9/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_9/expand" | |
| top: "conv_9/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_9/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_9/expand" | |
| top: "conv_9/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_9/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_9/expand" | |
| top: "conv_9/expand" | |
| } | |
| layer { | |
| name: "conv_9/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_9/expand" | |
| top: "conv_9/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_9/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_9/depthwise" | |
| top: "conv_9/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_9/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_9/depthwise" | |
| top: "conv_9/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_9/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_9/depthwise" | |
| top: "conv_9/depthwise" | |
| } | |
| layer { | |
| name: "conv_9/project" | |
| type: "Convolution" | |
| bottom: "conv_9/depthwise" | |
| top: "conv_9/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_9/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_9/project" | |
| top: "conv_9/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_9/project/scale" | |
| type: "Scale" | |
| bottom: "conv_9/project" | |
| top: "conv_9/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_9/sum" | |
| type: "Eltwise" | |
| bottom: "conv_8" | |
| bottom: "conv_9/project" | |
| top: "conv_9" | |
| } | |
| layer { | |
| name: "conv_10/expand" | |
| type: "Convolution" | |
| bottom: "conv_9" | |
| top: "conv_10/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_10/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_10/expand" | |
| top: "conv_10/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_10/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_10/expand" | |
| top: "conv_10/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_10/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_10/expand" | |
| top: "conv_10/expand" | |
| } | |
| layer { | |
| name: "conv_10/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_10/expand" | |
| top: "conv_10/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_10/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_10/depthwise" | |
| top: "conv_10/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_10/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_10/depthwise" | |
| top: "conv_10/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_10/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_10/depthwise" | |
| top: "conv_10/depthwise" | |
| } | |
| layer { | |
| name: "conv_10/project" | |
| type: "Convolution" | |
| bottom: "conv_10/depthwise" | |
| top: "conv_10/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_10/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_10/project" | |
| top: "conv_10/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_10/project/scale" | |
| type: "Scale" | |
| bottom: "conv_10/project" | |
| top: "conv_10/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_11/expand" | |
| type: "Convolution" | |
| bottom: "conv_10/project" | |
| top: "conv_11/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_11/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_11/expand" | |
| top: "conv_11/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_11/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_11/expand" | |
| top: "conv_11/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_11/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_11/expand" | |
| top: "conv_11/expand" | |
| } | |
| layer { | |
| name: "conv_11/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_11/expand" | |
| top: "conv_11/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_11/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_11/depthwise" | |
| top: "conv_11/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_11/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_11/depthwise" | |
| top: "conv_11/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_11/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_11/depthwise" | |
| top: "conv_11/depthwise" | |
| } | |
| layer { | |
| name: "conv_11/project" | |
| type: "Convolution" | |
| bottom: "conv_11/depthwise" | |
| top: "conv_11/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_11/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_11/project" | |
| top: "conv_11/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_11/project/scale" | |
| type: "Scale" | |
| bottom: "conv_11/project" | |
| top: "conv_11/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_11/sum" | |
| type: "Eltwise" | |
| bottom: "conv_10/project" | |
| bottom: "conv_11/project" | |
| top: "conv_11" | |
| } | |
| layer { | |
| name: "conv_12/expand" | |
| type: "Convolution" | |
| bottom: "conv_11" | |
| top: "conv_12/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_12/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_12/expand" | |
| top: "conv_12/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_12/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_12/expand" | |
| top: "conv_12/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_12/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_12/expand" | |
| top: "conv_12/expand" | |
| } | |
| layer { | |
| name: "conv_12/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_12/expand" | |
| top: "conv_12/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_12/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_12/depthwise" | |
| top: "conv_12/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_12/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_12/depthwise" | |
| top: "conv_12/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_12/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_12/depthwise" | |
| top: "conv_12/depthwise" | |
| } | |
| layer { | |
| name: "conv_12/project" | |
| type: "Convolution" | |
| bottom: "conv_12/depthwise" | |
| top: "conv_12/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_12/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_12/project" | |
| top: "conv_12/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_12/project/scale" | |
| type: "Scale" | |
| bottom: "conv_12/project" | |
| top: "conv_12/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_12/sum" | |
| type: "Eltwise" | |
| bottom: "conv_11" | |
| bottom: "conv_12/project" | |
| top: "conv_12" | |
| } | |
| layer { | |
| name: "conv_13/expand" | |
| type: "Convolution" | |
| bottom: "conv_12" | |
| top: "conv_13/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_13/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_13/expand" | |
| top: "conv_13/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_13/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_13/expand" | |
| top: "conv_13/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_13/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_13/expand" | |
| top: "conv_13/expand" | |
| } | |
| layer { | |
| name: "conv_13/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_13/expand" | |
| top: "conv_13/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 576 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_13/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_13/depthwise" | |
| top: "conv_13/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_13/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_13/depthwise" | |
| top: "conv_13/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_13/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_13/depthwise" | |
| top: "conv_13/depthwise" | |
| } | |
| layer { | |
| name: "conv_13/project" | |
| type: "Convolution" | |
| bottom: "conv_13/depthwise" | |
| top: "conv_13/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_13/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_13/project" | |
| top: "conv_13/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_13/project/scale" | |
| type: "Scale" | |
| bottom: "conv_13/project" | |
| top: "conv_13/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_14/expand" | |
| type: "Convolution" | |
| bottom: "conv_13/project" | |
| top: "conv_14/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_14/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_14/expand" | |
| top: "conv_14/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_14/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_14/expand" | |
| top: "conv_14/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_14/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_14/expand" | |
| top: "conv_14/expand" | |
| } | |
| layer { | |
| name: "conv_14/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_14/expand" | |
| top: "conv_14/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_14/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_14/depthwise" | |
| top: "conv_14/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_14/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_14/depthwise" | |
| top: "conv_14/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_14/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_14/depthwise" | |
| top: "conv_14/depthwise" | |
| } | |
| layer { | |
| name: "conv_14/project" | |
| type: "Convolution" | |
| bottom: "conv_14/depthwise" | |
| top: "conv_14/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_14/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_14/project" | |
| top: "conv_14/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_14/project/scale" | |
| type: "Scale" | |
| bottom: "conv_14/project" | |
| top: "conv_14/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_14/sum" | |
| type: "Eltwise" | |
| bottom: "conv_13/project" | |
| bottom: "conv_14/project" | |
| top: "conv_14" | |
| } | |
| layer { | |
| name: "conv_15/expand" | |
| type: "Convolution" | |
| bottom: "conv_14" | |
| top: "conv_15/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_15/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_15/expand" | |
| top: "conv_15/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_15/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_15/expand" | |
| top: "conv_15/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_15/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_15/expand" | |
| top: "conv_15/expand" | |
| } | |
| layer { | |
| name: "conv_15/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_15/expand" | |
| top: "conv_15/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_15/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_15/depthwise" | |
| top: "conv_15/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_15/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_15/depthwise" | |
| top: "conv_15/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_15/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_15/depthwise" | |
| top: "conv_15/depthwise" | |
| } | |
| layer { | |
| name: "conv_15/project" | |
| type: "Convolution" | |
| bottom: "conv_15/depthwise" | |
| top: "conv_15/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_15/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_15/project" | |
| top: "conv_15/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_15/project/scale" | |
| type: "Scale" | |
| bottom: "conv_15/project" | |
| top: "conv_15/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_15/sum" | |
| type: "Eltwise" | |
| bottom: "conv_14" | |
| bottom: "conv_15/project" | |
| top: "conv_15" | |
| } | |
| layer { | |
| name: "conv_16/expand" | |
| type: "Convolution" | |
| bottom: "conv_15" | |
| top: "conv_16/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_16/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_16/expand" | |
| top: "conv_16/expand" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_16/expand/scale" | |
| type: "Scale" | |
| bottom: "conv_16/expand" | |
| top: "conv_16/expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_16/expand/relu" | |
| type: "ReLU6" | |
| bottom: "conv_16/expand" | |
| top: "conv_16/expand" | |
| } | |
| layer { | |
| name: "conv_16/depthwise" | |
| type: "Convolution" | |
| bottom: "conv_16/expand" | |
| top: "conv_16/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_16/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_16/depthwise" | |
| top: "conv_16/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_16/depthwise/scale" | |
| type: "Scale" | |
| bottom: "conv_16/depthwise" | |
| top: "conv_16/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_16/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "conv_16/depthwise" | |
| top: "conv_16/depthwise" | |
| } | |
| layer { | |
| name: "conv_16/project" | |
| type: "Convolution" | |
| bottom: "conv_16/depthwise" | |
| top: "conv_16/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv_16/project/bn" | |
| type: "BatchNorm" | |
| bottom: "conv_16/project" | |
| top: "conv_16/project" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv_16/project/scale" | |
| type: "Scale" | |
| bottom: "conv_16/project" | |
| top: "conv_16/project" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Conv_1" | |
| type: "Convolution" | |
| bottom: "conv_16/project" | |
| top: "Conv_1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 1280 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Conv_1/bn" | |
| type: "BatchNorm" | |
| bottom: "Conv_1" | |
| top: "Conv_1" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "Conv_1/scale" | |
| type: "Scale" | |
| bottom: "Conv_1" | |
| top: "Conv_1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Conv_1/relu" | |
| type: "ReLU6" | |
| bottom: "Conv_1" | |
| top: "Conv_1" | |
| } | |
| layer { | |
| name: "layer_16" | |
| type: "Convolution" | |
| bottom: "Conv_1" | |
| top: "layer_16" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_16/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_16" | |
| top: "layer_16" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_16/scale" | |
| type: "Scale" | |
| bottom: "layer_16" | |
| top: "layer_16" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_16/relu" | |
| type: "ReLU6" | |
| bottom: "layer_16" | |
| top: "layer_16" | |
| } | |
| layer { | |
| name: "layer_17/depthwise" | |
| type: "Convolution" | |
| bottom: "layer_16" | |
| top: "layer_17/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_17/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_17/depthwise" | |
| top: "layer_17/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_17/depthwise/scale" | |
| type: "Scale" | |
| bottom: "layer_17/depthwise" | |
| top: "layer_17/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_17/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "layer_17/depthwise" | |
| top: "layer_17/depthwise" | |
| } | |
| layer { | |
| name: "layer_17" | |
| type: "Convolution" | |
| bottom: "layer_17/depthwise" | |
| top: "layer_17" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_17/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_17" | |
| top: "layer_17" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_17/scale" | |
| type: "Scale" | |
| bottom: "layer_17" | |
| top: "layer_17" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_17/relu" | |
| type: "ReLU6" | |
| bottom: "layer_17" | |
| top: "layer_17" | |
| } | |
| layer { | |
| name: "layer_18" | |
| type: "Convolution" | |
| bottom: "layer_17" | |
| top: "layer_18" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_18/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_18" | |
| top: "layer_18" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_18/scale" | |
| type: "Scale" | |
| bottom: "layer_18" | |
| top: "layer_18" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_18/relu" | |
| type: "ReLU6" | |
| bottom: "layer_18" | |
| top: "layer_18" | |
| } | |
| layer { | |
| name: "layer_19/depthwise" | |
| type: "Convolution" | |
| bottom: "layer_18" | |
| top: "layer_19/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_19/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_19/depthwise" | |
| top: "layer_19/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_19/depthwise/scale" | |
| type: "Scale" | |
| bottom: "layer_19/depthwise" | |
| top: "layer_19/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_19/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "layer_19/depthwise" | |
| top: "layer_19/depthwise" | |
| } | |
| layer { | |
| name: "layer_19" | |
| type: "Convolution" | |
| bottom: "layer_19/depthwise" | |
| top: "layer_19" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_19/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_19" | |
| top: "layer_19" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_19/scale" | |
| type: "Scale" | |
| bottom: "layer_19" | |
| top: "layer_19" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_19/relu" | |
| type: "ReLU6" | |
| bottom: "layer_19" | |
| top: "layer_19" | |
| } | |
| layer { | |
| name: "layer_20" | |
| type: "Convolution" | |
| bottom: "layer_19" | |
| top: "layer_20" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_20/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_20" | |
| top: "layer_20" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_20/scale" | |
| type: "Scale" | |
| bottom: "layer_20" | |
| top: "layer_20" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_20/relu" | |
| type: "ReLU6" | |
| bottom: "layer_20" | |
| top: "layer_20" | |
| } | |
| layer { | |
| name: "layer_21/depthwise" | |
| type: "Convolution" | |
| bottom: "layer_20" | |
| top: "layer_21/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_21/depthwise/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_21/depthwise" | |
| top: "layer_21/depthwise" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_21/depthwise/scale" | |
| type: "Scale" | |
| bottom: "layer_21/depthwise" | |
| top: "layer_21/depthwise" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_21/depthwise/relu" | |
| type: "ReLU6" | |
| bottom: "layer_21/depthwise" | |
| top: "layer_21/depthwise" | |
| } | |
| layer { | |
| name: "layer_21" | |
| type: "Convolution" | |
| bottom: "layer_21/depthwise" | |
| top: "layer_21" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_21/bn" | |
| type: "BatchNorm" | |
| bottom: "layer_21" | |
| top: "layer_21" | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "layer_21/scale" | |
| type: "Scale" | |
| bottom: "layer_21" | |
| top: "layer_21" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_21/relu" | |
| type: "ReLU6" | |
| bottom: "layer_21" | |
| top: "layer_21" | |
| } | |
| layer { | |
| name: "conv22_indoor" | |
| type: "Convolution" | |
| bottom: "layer_21" | |
| top: "conv22" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 125 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Region_Loss" | |
| type: "RegionLoss" | |
| bottom: "conv22" | |
| bottom: "label" | |
| top: "det_loss" | |
| loss_weight: 1 | |
| region_loss_param { | |
| side: 13 | |
| num_class: 20 | |
| coords: 4 | |
| num: 5 | |
| softmax: 1 | |
| jitter: 0.2 | |
| rescore: 1 | |
| object_scale: 5.0 | |
| noobject_scale: 1.0 | |
| class_scale: 1.0 | |
| coord_scale: 1.0 | |
| absolute: 1 | |
| thresh: 0.5 | |
| random: 0 | |
| biases: 1.08 | |
| biases: 1.19 | |
| biases: 3.42 | |
| biases: 4.41 | |
| biases: 6.63 | |
| biases: 11.38 | |
| biases: 9.42 | |
| biases: 5.11 | |
| biases: 16.62 | |
| biases: 10.52 | |
| } | |
| } | |
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