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February 27, 2020 13:52
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| name: "VGG_coco_SSD_300x300_train" | |
| layer { | |
| name: "data" | |
| type: "AnnotatedData" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: true | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| force_color: true | |
| resize_param { | |
| prob: 1 | |
| resize_mode: WARP | |
| height: 300 | |
| width: 300 | |
| interp_mode: LINEAR | |
| interp_mode: AREA | |
| interp_mode: NEAREST | |
| interp_mode: CUBIC | |
| interp_mode: LANCZOS4 | |
| } | |
| emit_constraint { | |
| emit_type: CENTER | |
| } | |
| distort_param { | |
| brightness_prob: 0.5 | |
| brightness_delta: 32 | |
| contrast_prob: 0.5 | |
| contrast_lower: 0.5 | |
| contrast_upper: 1.5 | |
| hue_prob: 0.5 | |
| hue_delta: 18 | |
| saturation_prob: 0.5 | |
| saturation_lower: 0.5 | |
| saturation_upper: 1.5 | |
| random_order_prob: 0.0 | |
| } | |
| expand_param { | |
| prob: 0.5 | |
| max_expand_ratio: 4.0 | |
| } | |
| } | |
| data_param { | |
| source: "examples/coco/coco_train_lmdb" | |
| batch_size: 32 | |
| backend: LMDB | |
| } | |
| annotated_data_param { | |
| batch_sampler { | |
| max_sample: 1 | |
| max_trials: 1 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.3 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 0.5 | |
| max_aspect_ratio: 2.0 | |
| } | |
| sample_constraint { | |
| min_jaccard_overlap: 0.1 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.3 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 0.5 | |
| max_aspect_ratio: 2.0 | |
| } | |
| sample_constraint { | |
| min_jaccard_overlap: 0.3 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.3 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 0.5 | |
| max_aspect_ratio: 2.0 | |
| } | |
| sample_constraint { | |
| min_jaccard_overlap: 0.5 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.3 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 0.5 | |
| max_aspect_ratio: 2.0 | |
| } | |
| sample_constraint { | |
| min_jaccard_overlap: 0.7 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.3 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 0.5 | |
| max_aspect_ratio: 2.0 | |
| } | |
| sample_constraint { | |
| min_jaccard_overlap: 0.9 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| batch_sampler { | |
| sampler { | |
| min_scale: 0.3 | |
| max_scale: 1.0 | |
| min_aspect_ratio: 0.5 | |
| max_aspect_ratio: 2.0 | |
| } | |
| sample_constraint { | |
| max_jaccard_overlap: 1.0 | |
| } | |
| max_sample: 1 | |
| max_trials: 50 | |
| } | |
| label_map_file: "data/coco/labelmap_coco.prototxt" | |
| } | |
| } | |
| layer { | |
| name: "conv1_1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu1_1" | |
| type: "ReLU" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| } | |
| layer { | |
| name: "conv1_2" | |
| type: "Convolution" | |
| bottom: "conv1_1" | |
| top: "conv1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu1_2" | |
| type: "ReLU" | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1_2" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu2_1" | |
| type: "ReLU" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| } | |
| layer { | |
| name: "conv2_2" | |
| type: "Convolution" | |
| bottom: "conv2_1" | |
| top: "conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu2_2" | |
| type: "ReLU" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| } | |
| layer { | |
| name: "pool2" | |
| type: "Pooling" | |
| bottom: "conv2_2" | |
| top: "pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1" | |
| type: "Convolution" | |
| bottom: "pool2" | |
| top: "conv3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu3_1" | |
| type: "ReLU" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| } | |
| layer { | |
| name: "conv3_2" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu3_2" | |
| type: "ReLU" | |
| bottom: "conv3_2" | |
| top: "conv3_2" | |
| } | |
| layer { | |
| name: "conv3_3" | |
| type: "Convolution" | |
| bottom: "conv3_2" | |
| top: "conv3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu3_3" | |
| type: "ReLU" | |
| bottom: "conv3_3" | |
| top: "conv3_3" | |
| } | |
| layer { | |
| name: "pool3" | |
| type: "Pooling" | |
| bottom: "conv3_3" | |
| top: "pool3" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1" | |
| type: "Convolution" | |
| bottom: "pool3" | |
| top: "conv4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_1" | |
| type: "ReLU" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| } | |
| layer { | |
| name: "conv4_2" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv4_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_2" | |
| type: "ReLU" | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| } | |
| layer { | |
| name: "conv4_3" | |
| type: "Convolution" | |
| bottom: "conv4_2" | |
| top: "conv4_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_3" | |
| type: "ReLU" | |
| bottom: "conv4_3" | |
| top: "conv4_3" | |
| } | |
| layer { | |
| name: "pool4" | |
| type: "Pooling" | |
| bottom: "conv4_3" | |
| top: "pool4" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1" | |
| type: "Convolution" | |
| bottom: "pool4" | |
| top: "conv5_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu5_1" | |
| type: "ReLU" | |
| bottom: "conv5_1" | |
| top: "conv5_1" | |
| } | |
| layer { | |
| name: "conv5_2" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv5_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu5_2" | |
| type: "ReLU" | |
| bottom: "conv5_2" | |
| top: "conv5_2" | |
| } | |
| layer { | |
| name: "conv5_3" | |
| type: "Convolution" | |
| bottom: "conv5_2" | |
| top: "conv5_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu5_3" | |
| type: "ReLU" | |
| bottom: "conv5_3" | |
| top: "conv5_3" | |
| } | |
| layer { | |
| name: "pool5" | |
| type: "Pooling" | |
| bottom: "conv5_3" | |
| top: "pool5" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc6" | |
| type: "Convolution" | |
| bottom: "pool5" | |
| top: "fc6" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 6 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| dilation: 6 | |
| } | |
| } | |
| layer { | |
| name: "relu6" | |
| type: "ReLU" | |
| bottom: "fc6" | |
| top: "fc6" | |
| } | |
| layer { | |
| name: "fc7" | |
| type: "Convolution" | |
| bottom: "fc6" | |
| top: "fc7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu7" | |
| type: "ReLU" | |
| bottom: "fc7" | |
| top: "fc7" | |
| } | |
| layer { | |
| name: "conv6_1" | |
| type: "Convolution" | |
| bottom: "fc7" | |
| top: "conv6_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_1_relu" | |
| type: "ReLU" | |
| bottom: "conv6_1" | |
| top: "conv6_1" | |
| } | |
| layer { | |
| name: "conv6_2" | |
| type: "Convolution" | |
| bottom: "conv6_1" | |
| top: "conv6_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_relu" | |
| type: "ReLU" | |
| bottom: "conv6_2" | |
| top: "conv6_2" | |
| } | |
| layer { | |
| name: "conv7_1" | |
| type: "Convolution" | |
| bottom: "conv6_2" | |
| top: "conv7_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_1_relu" | |
| type: "ReLU" | |
| bottom: "conv7_1" | |
| top: "conv7_1" | |
| } | |
| layer { | |
| name: "conv7_2" | |
| type: "Convolution" | |
| bottom: "conv7_1" | |
| top: "conv7_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_relu" | |
| type: "ReLU" | |
| bottom: "conv7_2" | |
| top: "conv7_2" | |
| } | |
| layer { | |
| name: "conv8_1" | |
| type: "Convolution" | |
| bottom: "conv7_2" | |
| top: "conv8_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_1_relu" | |
| type: "ReLU" | |
| bottom: "conv8_1" | |
| top: "conv8_1" | |
| } | |
| layer { | |
| name: "conv8_2" | |
| type: "Convolution" | |
| bottom: "conv8_1" | |
| top: "conv8_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_relu" | |
| type: "ReLU" | |
| bottom: "conv8_2" | |
| top: "conv8_2" | |
| } | |
| layer { | |
| name: "conv9_1" | |
| type: "Convolution" | |
| bottom: "conv8_2" | |
| top: "conv9_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_1_relu" | |
| type: "ReLU" | |
| bottom: "conv9_1" | |
| top: "conv9_1" | |
| } | |
| layer { | |
| name: "conv9_2" | |
| type: "Convolution" | |
| bottom: "conv9_1" | |
| top: "conv9_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_relu" | |
| type: "ReLU" | |
| bottom: "conv9_2" | |
| top: "conv9_2" | |
| } | |
| layer { | |
| name: "conv4_3_norm" | |
| type: "Normalize" | |
| bottom: "conv4_3" | |
| top: "conv4_3_norm" | |
| norm_param { | |
| across_spatial: false | |
| scale_filler { | |
| type: "constant" | |
| value: 20 | |
| } | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv4_3_norm" | |
| top: "conv4_3_norm_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv4_3_norm_mbox_loc" | |
| top: "conv4_3_norm_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv4_3_norm_mbox_loc_perm" | |
| top: "conv4_3_norm_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv4_3_norm" | |
| top: "conv4_3_norm_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 324 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv4_3_norm_mbox_conf" | |
| top: "conv4_3_norm_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv4_3_norm_mbox_conf_perm" | |
| top: "conv4_3_norm_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv4_3_norm" | |
| bottom: "data" | |
| top: "conv4_3_norm_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 21.0 | |
| max_size: 45.0 | |
| aspect_ratio: 2 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 8 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_loc" | |
| type: "Convolution" | |
| bottom: "fc7" | |
| top: "fc7_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "fc7_mbox_loc" | |
| top: "fc7_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "fc7_mbox_loc_perm" | |
| top: "fc7_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_conf" | |
| type: "Convolution" | |
| bottom: "fc7" | |
| top: "fc7_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 486 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "fc7_mbox_conf" | |
| top: "fc7_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "fc7_mbox_conf_perm" | |
| top: "fc7_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "fc7" | |
| bottom: "data" | |
| top: "fc7_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 45.0 | |
| max_size: 99.0 | |
| aspect_ratio: 2 | |
| aspect_ratio: 3 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 16 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv6_2" | |
| top: "conv6_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv6_2_mbox_loc" | |
| top: "conv6_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv6_2_mbox_loc_perm" | |
| top: "conv6_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv6_2" | |
| top: "conv6_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 486 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv6_2_mbox_conf" | |
| top: "conv6_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv6_2_mbox_conf_perm" | |
| top: "conv6_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv6_2" | |
| bottom: "data" | |
| top: "conv6_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 99.0 | |
| max_size: 153.0 | |
| aspect_ratio: 2 | |
| aspect_ratio: 3 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 32 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv7_2" | |
| top: "conv7_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv7_2_mbox_loc" | |
| top: "conv7_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv7_2_mbox_loc_perm" | |
| top: "conv7_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv7_2" | |
| top: "conv7_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 486 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv7_2_mbox_conf" | |
| top: "conv7_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv7_2_mbox_conf_perm" | |
| top: "conv7_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv7_2" | |
| bottom: "data" | |
| top: "conv7_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 153.0 | |
| max_size: 207.0 | |
| aspect_ratio: 2 | |
| aspect_ratio: 3 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 64 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv8_2" | |
| top: "conv8_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv8_2_mbox_loc" | |
| top: "conv8_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv8_2_mbox_loc_perm" | |
| top: "conv8_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv8_2" | |
| top: "conv8_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 324 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv8_2_mbox_conf" | |
| top: "conv8_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv8_2_mbox_conf_perm" | |
| top: "conv8_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv8_2" | |
| bottom: "data" | |
| top: "conv8_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 207.0 | |
| max_size: 261.0 | |
| aspect_ratio: 2 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 100 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv9_2" | |
| top: "conv9_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv9_2_mbox_loc" | |
| top: "conv9_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv9_2_mbox_loc_perm" | |
| top: "conv9_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv9_2" | |
| top: "conv9_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 324 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv9_2_mbox_conf" | |
| top: "conv9_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv9_2_mbox_conf_perm" | |
| top: "conv9_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv9_2" | |
| bottom: "data" | |
| top: "conv9_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 261.0 | |
| max_size: 315.0 | |
| aspect_ratio: 2 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 300 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "mbox_loc" | |
| type: "Concat" | |
| bottom: "conv4_3_norm_mbox_loc_flat" | |
| bottom: "fc7_mbox_loc_flat" | |
| bottom: "conv6_2_mbox_loc_flat" | |
| bottom: "conv7_2_mbox_loc_flat" | |
| bottom: "conv8_2_mbox_loc_flat" | |
| bottom: "conv9_2_mbox_loc_flat" | |
| top: "mbox_loc" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf" | |
| type: "Concat" | |
| bottom: "conv4_3_norm_mbox_conf_flat" | |
| bottom: "fc7_mbox_conf_flat" | |
| bottom: "conv6_2_mbox_conf_flat" | |
| bottom: "conv7_2_mbox_conf_flat" | |
| bottom: "conv8_2_mbox_conf_flat" | |
| bottom: "conv9_2_mbox_conf_flat" | |
| top: "mbox_conf" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "mbox_priorbox" | |
| type: "Concat" | |
| bottom: "conv4_3_norm_mbox_priorbox" | |
| bottom: "fc7_mbox_priorbox" | |
| bottom: "conv6_2_mbox_priorbox" | |
| bottom: "conv7_2_mbox_priorbox" | |
| bottom: "conv8_2_mbox_priorbox" | |
| bottom: "conv9_2_mbox_priorbox" | |
| top: "mbox_priorbox" | |
| concat_param { | |
| axis: 2 | |
| } | |
| } | |
| layer { | |
| name: "mbox_loss" | |
| type: "MultiBoxLoss" | |
| bottom: "mbox_loc" | |
| bottom: "mbox_conf" | |
| bottom: "mbox_priorbox" | |
| bottom: "label" | |
| top: "mbox_loss" | |
| include { | |
| phase: TRAIN | |
| } | |
| propagate_down: true | |
| propagate_down: true | |
| propagate_down: false | |
| propagate_down: false | |
| loss_param { | |
| normalization: VALID | |
| } | |
| multibox_loss_param { | |
| loc_loss_type: SMOOTH_L1 | |
| conf_loss_type: SOFTMAX | |
| loc_weight: 1.0 | |
| num_classes: 81 | |
| share_location: true | |
| match_type: PER_PREDICTION | |
| overlap_threshold: 0.5 | |
| use_prior_for_matching: true | |
| background_label_id: 0 | |
| use_difficult_gt: false | |
| neg_pos_ratio: 3.0 | |
| neg_overlap: 0.5 | |
| code_type: CENTER_SIZE | |
| ignore_cross_boundary_bbox: false | |
| mining_type: MAX_NEGATIVE | |
| } | |
| } |
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