Last active
December 28, 2018 10:44
-
-
Save eric612/e04e2722e0bfc930a6312dbefa06280c to your computer and use it in GitHub Desktop.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: "MobileNetv2-YOLO" | |
| 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 | |
| force_color: true | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 608 | |
| width: 608 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 416 | |
| width: 416 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 320 | |
| width: 320 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 352 | |
| width: 352 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 384 | |
| width: 384 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 448 | |
| width: 448 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 480 | |
| width: 480 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 512 | |
| width: 512 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 544 | |
| width: 544 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: LANCZOS4 | |
| } | |
| resize_param { | |
| prob: 0.1 | |
| resize_mode: FIT_LARGE_SIZE_AND_PAD | |
| height: 576 | |
| width: 576 | |
| 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 | |
| } | |
| } | |
| data_param { | |
| source: "examples/coco/coco_train_lmdb" | |
| batch_size: 3 | |
| backend: LMDB | |
| } | |
| annotated_data_param { | |
| yolo_data_type : 1 | |
| yolo_data_jitter : 0.3 | |
| label_map_file: "data/coco/labelmap_coco.prototxt" | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| 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 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv1/scale" | |
| type: "Scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "conv2_1/expand" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "conv2_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/expand" | |
| top: "conv2_1/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv2_1/expand" | |
| top: "conv2_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_1/expand" | |
| type: "ReLU" | |
| bottom: "conv2_1/expand" | |
| top: "conv2_1/expand" | |
| } | |
| layer { | |
| name: "conv2_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv2_1/expand" | |
| top: "conv2_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 32 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/dwise" | |
| top: "conv2_1/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv2_1/dwise" | |
| top: "conv2_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv2_1/dwise" | |
| top: "conv2_1/dwise" | |
| } | |
| layer { | |
| name: "conv2_1/linear" | |
| type: "Convolution" | |
| bottom: "conv2_1/dwise" | |
| top: "conv2_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/linear" | |
| top: "conv2_1/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv2_1/linear" | |
| top: "conv2_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/expand" | |
| type: "Convolution" | |
| bottom: "conv2_1/linear" | |
| top: "conv2_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/expand" | |
| top: "conv2_2/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv2_2/expand" | |
| top: "conv2_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_2/expand" | |
| type: "ReLU" | |
| bottom: "conv2_2/expand" | |
| top: "conv2_2/expand" | |
| } | |
| layer { | |
| name: "conv2_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv2_2/expand" | |
| top: "conv2_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 96 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/dwise" | |
| top: "conv2_2/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv2_2/dwise" | |
| top: "conv2_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv2_2/dwise" | |
| top: "conv2_2/dwise" | |
| } | |
| layer { | |
| name: "conv2_2/linear" | |
| type: "Convolution" | |
| bottom: "conv2_2/dwise" | |
| top: "conv2_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/linear" | |
| top: "conv2_2/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv2_2/linear" | |
| top: "conv2_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/expand" | |
| type: "Convolution" | |
| bottom: "conv2_2/linear" | |
| top: "conv3_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/expand" | |
| top: "conv3_1/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv3_1/expand" | |
| top: "conv3_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_1/expand" | |
| type: "ReLU" | |
| bottom: "conv3_1/expand" | |
| top: "conv3_1/expand" | |
| } | |
| layer { | |
| name: "conv3_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv3_1/expand" | |
| top: "conv3_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 144 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/dwise" | |
| top: "conv3_1/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv3_1/dwise" | |
| top: "conv3_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv3_1/dwise" | |
| top: "conv3_1/dwise" | |
| } | |
| layer { | |
| name: "conv3_1/linear" | |
| type: "Convolution" | |
| bottom: "conv3_1/dwise" | |
| top: "conv3_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/linear" | |
| top: "conv3_1/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv3_1/linear" | |
| top: "conv3_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_1" | |
| type: "Eltwise" | |
| bottom: "conv2_2/linear" | |
| bottom: "conv3_1/linear" | |
| top: "block_3_1" | |
| } | |
| layer { | |
| name: "conv3_2/expand" | |
| type: "Convolution" | |
| bottom: "block_3_1" | |
| top: "conv3_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/expand" | |
| top: "conv3_2/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv3_2/expand" | |
| top: "conv3_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_2/expand" | |
| type: "ReLU" | |
| bottom: "conv3_2/expand" | |
| top: "conv3_2/expand" | |
| } | |
| layer { | |
| name: "conv3_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv3_2/expand" | |
| top: "conv3_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 144 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/dwise" | |
| top: "conv3_2/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv3_2/dwise" | |
| top: "conv3_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv3_2/dwise" | |
| top: "conv3_2/dwise" | |
| } | |
| layer { | |
| name: "conv3_2/linear" | |
| type: "Convolution" | |
| bottom: "conv3_2/dwise" | |
| top: "conv3_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/linear" | |
| top: "conv3_2/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv3_2/linear" | |
| top: "conv3_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/expand" | |
| type: "Convolution" | |
| bottom: "conv3_2/linear" | |
| top: "conv4_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/expand" | |
| top: "conv4_1/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_1/expand" | |
| top: "conv4_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_1/expand" | |
| type: "ReLU" | |
| bottom: "conv4_1/expand" | |
| top: "conv4_1/expand" | |
| } | |
| layer { | |
| name: "conv4_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_1/expand" | |
| top: "conv4_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/dwise" | |
| top: "conv4_1/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_1/dwise" | |
| top: "conv4_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_1/dwise" | |
| top: "conv4_1/dwise" | |
| } | |
| layer { | |
| name: "conv4_1/linear" | |
| type: "Convolution" | |
| bottom: "conv4_1/dwise" | |
| top: "conv4_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/linear" | |
| top: "conv4_1/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_1/linear" | |
| top: "conv4_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_1" | |
| type: "Eltwise" | |
| bottom: "conv3_2/linear" | |
| bottom: "conv4_1/linear" | |
| top: "block_4_1" | |
| } | |
| layer { | |
| name: "conv4_2/expand" | |
| type: "Convolution" | |
| bottom: "block_4_1" | |
| top: "conv4_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/expand" | |
| top: "conv4_2/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_2/expand" | |
| top: "conv4_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_2/expand" | |
| type: "ReLU" | |
| bottom: "conv4_2/expand" | |
| top: "conv4_2/expand" | |
| } | |
| layer { | |
| name: "conv4_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_2/expand" | |
| top: "conv4_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/dwise" | |
| top: "conv4_2/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_2/dwise" | |
| top: "conv4_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_2/dwise" | |
| top: "conv4_2/dwise" | |
| } | |
| layer { | |
| name: "conv4_2/linear" | |
| type: "Convolution" | |
| bottom: "conv4_2/dwise" | |
| top: "conv4_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/linear" | |
| top: "conv4_2/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_2/linear" | |
| top: "conv4_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_2" | |
| type: "Eltwise" | |
| bottom: "block_4_1" | |
| bottom: "conv4_2/linear" | |
| top: "block_4_2" | |
| } | |
| layer { | |
| name: "conv4_3/expand" | |
| type: "Convolution" | |
| bottom: "block_4_2" | |
| top: "conv4_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/expand" | |
| top: "conv4_3/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_3/expand" | |
| top: "conv4_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_3/expand" | |
| type: "ReLU" | |
| bottom: "conv4_3/expand" | |
| top: "conv4_3/expand" | |
| } | |
| layer { | |
| name: "conv4_3/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_3/expand" | |
| top: "conv4_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/dwise" | |
| top: "conv4_3/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_3/dwise" | |
| top: "conv4_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_3/dwise" | |
| top: "conv4_3/dwise" | |
| } | |
| layer { | |
| name: "conv4_3/linear" | |
| type: "Convolution" | |
| bottom: "conv4_3/dwise" | |
| top: "conv4_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/linear" | |
| top: "conv4_3/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_3/linear" | |
| top: "conv4_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/expand" | |
| type: "Convolution" | |
| bottom: "conv4_3/linear" | |
| top: "conv4_4/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/expand" | |
| top: "conv4_4/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_4/expand" | |
| top: "conv4_4/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_4/expand" | |
| type: "ReLU" | |
| bottom: "conv4_4/expand" | |
| top: "conv4_4/expand" | |
| } | |
| layer { | |
| name: "conv4_4/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_4/expand" | |
| top: "conv4_4/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/dwise" | |
| top: "conv4_4/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_4/dwise" | |
| top: "conv4_4/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_4/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_4/dwise" | |
| top: "conv4_4/dwise" | |
| } | |
| layer { | |
| name: "conv4_4/linear" | |
| type: "Convolution" | |
| bottom: "conv4_4/dwise" | |
| top: "conv4_4/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/linear" | |
| top: "conv4_4/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_4/linear" | |
| top: "conv4_4/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_4" | |
| type: "Eltwise" | |
| bottom: "conv4_3/linear" | |
| bottom: "conv4_4/linear" | |
| top: "block_4_4" | |
| } | |
| layer { | |
| name: "conv4_5/expand" | |
| type: "Convolution" | |
| bottom: "block_4_4" | |
| top: "conv4_5/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_5/expand" | |
| top: "conv4_5/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_5/expand" | |
| top: "conv4_5/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_5/expand" | |
| type: "ReLU" | |
| bottom: "conv4_5/expand" | |
| top: "conv4_5/expand" | |
| } | |
| layer { | |
| name: "conv4_5/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_5/expand" | |
| top: "conv4_5/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_5/dwise" | |
| top: "conv4_5/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_5/dwise" | |
| top: "conv4_5/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_5/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_5/dwise" | |
| top: "conv4_5/dwise" | |
| } | |
| layer { | |
| name: "conv4_5/linear" | |
| type: "Convolution" | |
| bottom: "conv4_5/dwise" | |
| top: "conv4_5/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_5/linear" | |
| top: "conv4_5/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_5/linear" | |
| top: "conv4_5/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_5" | |
| type: "Eltwise" | |
| bottom: "block_4_4" | |
| bottom: "conv4_5/linear" | |
| top: "block_4_5" | |
| } | |
| layer { | |
| name: "conv4_6/expand" | |
| type: "Convolution" | |
| bottom: "block_4_5" | |
| top: "conv4_6/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_6/expand" | |
| top: "conv4_6/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_6/expand" | |
| top: "conv4_6/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_6/expand" | |
| type: "ReLU" | |
| bottom: "conv4_6/expand" | |
| top: "conv4_6/expand" | |
| } | |
| layer { | |
| name: "conv4_6/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_6/expand" | |
| top: "conv4_6/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_6/dwise" | |
| top: "conv4_6/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_6/dwise" | |
| top: "conv4_6/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_6/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_6/dwise" | |
| top: "conv4_6/dwise" | |
| } | |
| layer { | |
| name: "conv4_6/linear" | |
| type: "Convolution" | |
| bottom: "conv4_6/dwise" | |
| top: "conv4_6/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_6/linear" | |
| top: "conv4_6/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_6/linear" | |
| top: "conv4_6/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_6" | |
| type: "Eltwise" | |
| bottom: "block_4_5" | |
| bottom: "conv4_6/linear" | |
| top: "block_4_6" | |
| } | |
| layer { | |
| name: "conv4_7/expand" | |
| type: "Convolution" | |
| bottom: "block_4_6" | |
| top: "conv4_7/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_7/expand" | |
| top: "conv4_7/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_7/expand" | |
| top: "conv4_7/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_7/expand" | |
| type: "ReLU" | |
| bottom: "conv4_7/expand" | |
| top: "conv4_7/expand" | |
| } | |
| layer { | |
| name: "conv4_7/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_7/expand" | |
| top: "conv4_7/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_7/dwise" | |
| top: "conv4_7/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_7/dwise" | |
| top: "conv4_7/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_7/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_7/dwise" | |
| top: "conv4_7/dwise" | |
| } | |
| layer { | |
| name: "conv4_7/linear" | |
| type: "Convolution" | |
| bottom: "conv4_7/dwise" | |
| top: "conv4_7/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_7/linear" | |
| top: "conv4_7/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_7/linear" | |
| top: "conv4_7/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/expand" | |
| type: "Convolution" | |
| bottom: "conv4_7/linear" | |
| top: "conv5_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/expand" | |
| top: "conv5_1/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv5_1/expand" | |
| top: "conv5_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_1/expand" | |
| type: "ReLU" | |
| bottom: "conv5_1/expand" | |
| top: "conv5_1/expand" | |
| } | |
| layer { | |
| name: "conv5_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv5_1/expand" | |
| top: "conv5_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/dwise" | |
| top: "conv5_1/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv5_1/dwise" | |
| top: "conv5_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_1/dwise" | |
| top: "conv5_1/dwise" | |
| } | |
| layer { | |
| name: "conv5_1/linear" | |
| type: "Convolution" | |
| bottom: "conv5_1/dwise" | |
| top: "conv5_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/linear" | |
| top: "conv5_1/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv5_1/linear" | |
| top: "conv5_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_5_1" | |
| type: "Eltwise" | |
| bottom: "conv4_7/linear" | |
| bottom: "conv5_1/linear" | |
| top: "block_5_1" | |
| } | |
| layer { | |
| name: "conv5_2/expand" | |
| type: "Convolution" | |
| bottom: "block_5_1" | |
| top: "conv5_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/expand" | |
| top: "conv5_2/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv5_2/expand" | |
| top: "conv5_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_2/expand" | |
| type: "ReLU" | |
| bottom: "conv5_2/expand" | |
| top: "conv5_2/expand" | |
| } | |
| layer { | |
| name: "conv5_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv5_2/expand" | |
| top: "conv5_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/dwise" | |
| top: "conv5_2/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv5_2/dwise" | |
| top: "conv5_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_2/dwise" | |
| top: "conv5_2/dwise" | |
| } | |
| layer { | |
| name: "conv5_2/linear" | |
| type: "Convolution" | |
| bottom: "conv5_2/dwise" | |
| top: "conv5_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/linear" | |
| top: "conv5_2/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv5_2/linear" | |
| top: "conv5_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_5_2" | |
| type: "Eltwise" | |
| bottom: "block_5_1" | |
| bottom: "conv5_2/linear" | |
| top: "block_5_2" | |
| } | |
| layer { | |
| name: "conv5_3/expand" | |
| type: "Convolution" | |
| bottom: "block_5_2" | |
| top: "conv5_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/expand" | |
| top: "conv5_3/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/expand/scale" | |
| type: "Scale" | |
| bottom: "conv5_3/expand" | |
| top: "conv5_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_3/expand" | |
| type: "ReLU" | |
| bottom: "conv5_3/expand" | |
| top: "conv5_3/expand" | |
| } | |
| layer { | |
| name: "conv5_3/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv5_3/expand" | |
| top: "conv5_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/dwise" | |
| top: "conv5_3/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv5_3/dwise" | |
| top: "conv5_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_3/dwise" | |
| top: "conv5_3/dwise" | |
| } | |
| layer { | |
| name: "conv5_3/linear" | |
| type: "Convolution" | |
| bottom: "conv5_3/dwise" | |
| top: "conv5_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/linear" | |
| top: "conv5_3/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/linear/scale" | |
| type: "Scale" | |
| bottom: "conv5_3/linear" | |
| top: "conv5_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/expand" | |
| type: "Convolution" | |
| bottom: "conv5_3/linear" | |
| top: "conv6_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_1/expand" | |
| top: "conv6_1/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv6_1/expand" | |
| top: "conv6_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_1/expand" | |
| type: "ReLU" | |
| bottom: "conv6_1/expand" | |
| top: "conv6_1/expand" | |
| } | |
| layer { | |
| name: "conv6_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6_1/expand" | |
| top: "conv6_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_1/dwise" | |
| top: "conv6_1/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv6_1/dwise" | |
| top: "conv6_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_1/dwise" | |
| top: "conv6_1/dwise" | |
| } | |
| layer { | |
| name: "conv6_1/linear" | |
| type: "Convolution" | |
| bottom: "conv6_1/dwise" | |
| top: "conv6_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_1/linear" | |
| top: "conv6_1/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv6_1/linear" | |
| top: "conv6_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_6_1" | |
| type: "Eltwise" | |
| bottom: "conv5_3/linear" | |
| bottom: "conv6_1/linear" | |
| top: "block_6_1" | |
| } | |
| layer { | |
| name: "conv6_2/expand" | |
| type: "Convolution" | |
| bottom: "block_6_1" | |
| top: "conv6_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_2/expand" | |
| top: "conv6_2/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv6_2/expand" | |
| top: "conv6_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_2/expand" | |
| type: "ReLU" | |
| bottom: "conv6_2/expand" | |
| top: "conv6_2/expand" | |
| } | |
| layer { | |
| name: "conv6_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6_2/expand" | |
| top: "conv6_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_2/dwise" | |
| top: "conv6_2/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv6_2/dwise" | |
| top: "conv6_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_2/dwise" | |
| top: "conv6_2/dwise" | |
| } | |
| layer { | |
| name: "conv6_2/linear" | |
| type: "Convolution" | |
| bottom: "conv6_2/dwise" | |
| top: "conv6_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_2/linear" | |
| top: "conv6_2/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv6_2/linear" | |
| top: "conv6_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_6_2" | |
| type: "Eltwise" | |
| bottom: "block_6_1" | |
| bottom: "conv6_2/linear" | |
| top: "block_6_2" | |
| } | |
| layer { | |
| name: "conv6_3/expand" | |
| type: "Convolution" | |
| bottom: "block_6_2" | |
| top: "conv6_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_3/expand" | |
| top: "conv6_3/expand" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/expand/scale" | |
| type: "Scale" | |
| bottom: "conv6_3/expand" | |
| top: "conv6_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_3/expand" | |
| type: "ReLU" | |
| bottom: "conv6_3/expand" | |
| top: "conv6_3/expand" | |
| } | |
| layer { | |
| name: "conv6_3/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6_3/expand" | |
| top: "conv6_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_3/dwise" | |
| top: "conv6_3/dwise" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv6_3/dwise" | |
| top: "conv6_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_3/dwise" | |
| top: "conv6_3/dwise" | |
| } | |
| layer { | |
| name: "conv6_3/linear" | |
| type: "Convolution" | |
| bottom: "conv6_3/dwise" | |
| top: "conv6_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_3/linear" | |
| top: "conv6_3/linear" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/linear/scale" | |
| type: "Scale" | |
| bottom: "conv6_3/linear" | |
| top: "conv6_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv6_4" | |
| type: "Convolution" | |
| bottom: "conv6_3/linear" | |
| top: "conv6_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1280 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_4/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_4" | |
| top: "conv6_4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_4/scale" | |
| type: "Scale" | |
| bottom: "conv6_4" | |
| top: "conv6_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_4" | |
| type: "ReLU" | |
| bottom: "conv6_4" | |
| top: "conv6_4" | |
| } | |
| layer { | |
| name: "conv15/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6_4" | |
| top: "conv15/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1280 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 1280 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv15/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv15/dw" | |
| top: "conv15/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv15/dw/scale" | |
| type: "Scale" | |
| bottom: "conv15/dw" | |
| top: "conv15/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: "conv15/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv15/dw" | |
| top: "conv15/dw" | |
| } | |
| layer { | |
| name: "conv15" | |
| type: "Convolution" | |
| bottom: "conv15/dw" | |
| top: "conv15" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1280 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv15/bn" | |
| type: "BatchNorm" | |
| bottom: "conv15" | |
| top: "conv15" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv15/scale" | |
| type: "Scale" | |
| bottom: "conv15" | |
| top: "conv15" | |
| 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: "conv15/relu" | |
| type: "ReLU" | |
| bottom: "conv15" | |
| top: "conv15" | |
| } | |
| layer { | |
| name: "upsample" | |
| type: "Deconvolution" | |
| bottom: "conv15" | |
| top: "upsample" | |
| param { lr_mult: 0 decay_mult: 0 } | |
| convolution_param { | |
| num_output: 640 | |
| group: 640 | |
| kernel_size: 1 stride: 2 pad: 0 | |
| weight_filler: { | |
| type: "constant" | |
| value : 1 | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| name: "maxpool" | |
| top: "maxpool" | |
| bottom: "upsample" | |
| type: "Pooling" | |
| pooling_param { | |
| kernel_size: 2 | |
| stride: 1 | |
| pool: MAX | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv16/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "maxpool" | |
| top: "conv16/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 640 | |
| 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: 640 | |
| 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: "conv17/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "block_5_2" | |
| top: "conv17/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 96 | |
| 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: 640 | |
| 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: "conv16" | |
| bottom: "conv17" | |
| 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: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 640 | |
| 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: 640 | |
| 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: "upsample2" | |
| type: "Deconvolution" | |
| bottom: "conv18" | |
| top: "upsample2" | |
| param { lr_mult: 0 decay_mult: 0 } | |
| convolution_param { | |
| num_output: 320 | |
| group: 320 | |
| kernel_size: 1 stride: 2 pad: 0 | |
| weight_filler: { | |
| type: "constant" | |
| value : 1 | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| name: "maxpool2" | |
| top: "maxpool2" | |
| bottom: "upsample2" | |
| type: "Pooling" | |
| pooling_param { | |
| kernel_size: 2 | |
| stride: 1 | |
| pool: MAX | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv19/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "maxpool2" | |
| top: "conv19/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 320 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv19/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv19/dw" | |
| top: "conv19/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv19/dw/scale" | |
| type: "Scale" | |
| bottom: "conv19/dw" | |
| top: "conv19/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: "conv19/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv19/dw" | |
| top: "conv19/dw" | |
| } | |
| layer { | |
| name: "conv19" | |
| type: "Convolution" | |
| bottom: "conv19/dw" | |
| top: "conv19" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv19/bn" | |
| type: "BatchNorm" | |
| bottom: "conv19" | |
| top: "conv19" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv19/scale" | |
| type: "Scale" | |
| bottom: "conv19" | |
| top: "conv19" | |
| 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: "conv19/relu" | |
| type: "ReLU" | |
| bottom: "conv19" | |
| top: "conv19" | |
| } | |
| layer { | |
| name: "conv20/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "block_4_6" | |
| top: "conv20/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 64 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv20/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv20/dw" | |
| top: "conv20/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv20/dw/scale" | |
| type: "Scale" | |
| bottom: "conv20/dw" | |
| top: "conv20/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: "conv20/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv20/dw" | |
| top: "conv20/dw" | |
| } | |
| layer { | |
| name: "conv20" | |
| type: "Convolution" | |
| bottom: "conv20/dw" | |
| top: "conv20" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv20/bn" | |
| type: "BatchNorm" | |
| bottom: "conv20" | |
| top: "conv20" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv20/scale" | |
| type: "Scale" | |
| bottom: "conv20" | |
| top: "conv20" | |
| 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: "conv20/relu" | |
| type: "ReLU" | |
| bottom: "conv20" | |
| top: "conv20" | |
| } | |
| layer { | |
| name: "conv20/sum" | |
| type: "Eltwise" | |
| bottom: "conv19" | |
| bottom: "conv20" | |
| top: "conv20/sum" | |
| } | |
| layer { | |
| name: "conv21/dw" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv20/sum" | |
| top: "conv21/dw" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 320 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv21/dw/bn" | |
| type: "BatchNorm" | |
| bottom: "conv21/dw" | |
| top: "conv21/dw" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv21/dw/scale" | |
| type: "Scale" | |
| bottom: "conv21/dw" | |
| top: "conv21/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: "conv21/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv21/dw" | |
| top: "conv21/dw" | |
| } | |
| layer { | |
| name: "conv21" | |
| type: "Convolution" | |
| bottom: "conv21/dw" | |
| top: "conv21" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv21/bn" | |
| type: "BatchNorm" | |
| bottom: "conv21" | |
| top: "conv21" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv21/scale" | |
| type: "Scale" | |
| bottom: "conv21" | |
| top: "conv21" | |
| 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: "conv21/relu" | |
| type: "ReLU" | |
| bottom: "conv21" | |
| top: "conv21" | |
| } | |
| layer { | |
| name: "conv22" | |
| type: "Convolution" | |
| bottom: "conv15" | |
| top: "conv22" | |
| 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: "conv23" | |
| type: "Convolution" | |
| bottom: "conv18" | |
| 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: "conv21" | |
| 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: "Yolov3Loss1" | |
| type: "Yolov3" | |
| bottom: "conv22" | |
| bottom: "label" | |
| top: "det_loss1" | |
| loss_weight: 1 | |
| yolov3_param { | |
| side: 13 | |
| num_class: 80 | |
| num: 3 | |
| object_scale: 5.0 | |
| noobject_scale: 1.0 | |
| class_scale: 1.0 | |
| coord_scale: 1.0 | |
| thresh: 0.7 | |
| anchors_scale : 32 | |
| #10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 | |
| biases: 10 | |
| biases: 13 | |
| biases: 16 | |
| biases: 30 | |
| biases: 33 | |
| biases: 23 | |
| biases: 30 | |
| biases: 61 | |
| biases: 62 | |
| biases: 45 | |
| biases: 59 | |
| biases: 119 | |
| biases: 116 | |
| biases: 90 | |
| biases: 156 | |
| biases: 198 | |
| biases: 373 | |
| biases: 326 | |
| mask:6 | |
| mask:7 | |
| mask:8 | |
| } | |
| } | |
| layer { | |
| name: "Yolov3Loss2" | |
| type: "Yolov3" | |
| bottom: "conv23" | |
| bottom: "label" | |
| top: "det_loss2" | |
| loss_weight: 1 | |
| yolov3_param { | |
| side: 26 | |
| num_class: 80 | |
| num: 3 | |
| object_scale: 5.0 | |
| noobject_scale: 1.0 | |
| class_scale: 1.0 | |
| coord_scale: 1.0 | |
| thresh: 0.7 | |
| anchors_scale : 16 | |
| #10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 | |
| biases: 10 | |
| biases: 13 | |
| biases: 16 | |
| biases: 30 | |
| biases: 33 | |
| biases: 23 | |
| biases: 30 | |
| biases: 61 | |
| biases: 62 | |
| biases: 45 | |
| biases: 59 | |
| biases: 119 | |
| biases: 116 | |
| biases: 90 | |
| biases: 156 | |
| biases: 198 | |
| biases: 373 | |
| biases: 326 | |
| mask:3 | |
| mask:4 | |
| mask:5 | |
| } | |
| } | |
| layer { | |
| name: "Yolov3Loss3" | |
| type: "Yolov3" | |
| bottom: "conv24" | |
| bottom: "label" | |
| top: "det_loss3" | |
| loss_weight: 1 | |
| yolov3_param { | |
| side: 26 | |
| num_class: 80 | |
| num: 3 | |
| object_scale: 5.0 | |
| noobject_scale: 1.0 | |
| class_scale: 1.0 | |
| coord_scale: 1.0 | |
| thresh: 0.6 | |
| anchors_scale : 8 | |
| #10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326 | |
| biases: 10 | |
| biases: 13 | |
| biases: 16 | |
| biases: 30 | |
| biases: 33 | |
| biases: 23 | |
| biases: 30 | |
| biases: 61 | |
| biases: 62 | |
| biases: 45 | |
| biases: 59 | |
| biases: 119 | |
| biases: 116 | |
| biases: 90 | |
| biases: 156 | |
| biases: 198 | |
| biases: 373 | |
| biases: 326 | |
| mask:0 | |
| mask:1 | |
| mask:2 | |
| } | |
| } |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment