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July 8, 2017 17:21
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| name: "DNetSqueezeNet" | |
| layer { | |
| name: "train_data" | |
| type: "Data" | |
| top: "data" | |
| data_param { | |
| backend: LMDB | |
| source: "examples/kitti/kitti_train_images.lmdb" | |
| batch_size: 8 | |
| } | |
| include: { phase: TRAIN } | |
| } | |
| layer { | |
| name: "train_label" | |
| type: "Data" | |
| top: "label" | |
| data_param { | |
| backend: LMDB | |
| source: "examples/kitti/kitti_train_labels.lmdb" | |
| batch_size: 8 | |
| } | |
| include: { phase: TRAIN } | |
| } | |
| layer { | |
| name: "val_data" | |
| type: "Data" | |
| top: "data" | |
| data_param { | |
| backend: LMDB | |
| source: "examples/kitti/kitti_test_images.lmdb" | |
| batch_size: 6 | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "val_label" | |
| type: "Data" | |
| top: "label" | |
| data_param { | |
| backend: LMDB | |
| source: "examples/kitti/kitti_test_labels.lmdb" | |
| batch_size: 6 | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "deploy_data" | |
| type: "Input" | |
| top: "data" | |
| input_param { | |
| shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 240 | |
| dim: 320 | |
| } | |
| } | |
| include: { phase: TEST not_stage: "val" } | |
| } | |
| # Data transformation layers | |
| layer { | |
| name: "train_transform" | |
| type: "DetectNetTransformation" | |
| bottom: "data" | |
| bottom: "label" | |
| top: "transformed_data" | |
| top: "transformed_label" | |
| detectnet_groundtruth_param: { | |
| stride: 4 | |
| scale_cvg: 0.4 | |
| gridbox_type: GRIDBOX_MIN | |
| coverage_type: RECTANGULAR | |
| min_cvg_len: 20 | |
| obj_norm: true | |
| image_size_x: 320 | |
| image_size_y: 240 | |
| crop_bboxes: false | |
| object_class: { src: 4 dst: 0} # obj class 4 -> cvg index 0 | |
| object_class: { src: 3 dst: 1} # obj class 3 -> cvg index 1 | |
| object_class: { src: 1 dst: 2} # obj class 1 -> cvg index 2 | |
| } | |
| detectnet_augmentation_param: { | |
| crop_prob: 1 | |
| shift_x: 32 | |
| shift_y: 32 | |
| flip_prob: 0.5 | |
| rotation_prob: 0 | |
| max_rotate_degree: 5 | |
| scale_prob: 0.4 | |
| scale_min: 0.8 | |
| scale_max: 1.2 | |
| hue_rotation_prob: 0.8 | |
| hue_rotation: 30 | |
| desaturation_prob: 0.8 | |
| desaturation_max: 0.8 | |
| } | |
| transform_param: { | |
| mean_value: 127 | |
| } | |
| include: { phase: TRAIN } | |
| } | |
| layer { | |
| name: "val_transform" | |
| type: "DetectNetTransformation" | |
| bottom: "data" | |
| bottom: "label" | |
| top: "transformed_data" | |
| top: "transformed_label" | |
| detectnet_groundtruth_param: { | |
| stride: 4 | |
| scale_cvg: 0.4 | |
| gridbox_type: GRIDBOX_MIN | |
| coverage_type: RECTANGULAR | |
| min_cvg_len: 20 | |
| obj_norm: true | |
| image_size_x: 320 | |
| image_size_y: 240 | |
| crop_bboxes: false | |
| object_class: { src: 4 dst: 0} # obj class 4 -> cvg index 0 | |
| object_class: { src: 3 dst: 1} # obj class 3 -> cvg index 1 | |
| object_class: { src: 1 dst: 2} # obj class 1 -> cvg index 2 | |
| } | |
| transform_param: { | |
| mean_value: 127 | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "deploy_transform" | |
| type: "Power" | |
| bottom: "data" | |
| top: "transformed_data" | |
| power_param { | |
| shift: -127 | |
| } | |
| include: { phase: TEST not_stage: "val" } | |
| } | |
| # Label conversion layers | |
| layer { | |
| name: "slice-label" | |
| type: "Slice" | |
| bottom: "transformed_label" | |
| top: "foreground-label" | |
| top: "bbox-label" | |
| top: "size-label" | |
| top: "obj-label" | |
| top: "coverage-label" | |
| slice_param { | |
| slice_dim: 1 | |
| slice_point: 1 | |
| slice_point: 5 | |
| slice_point: 7 | |
| slice_point: 8 | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "coverage-block" | |
| type: "Concat" | |
| bottom: "foreground-label" | |
| bottom: "foreground-label" | |
| bottom: "foreground-label" | |
| bottom: "foreground-label" | |
| top: "coverage-block" | |
| concat_param { | |
| concat_dim: 1 | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "size-block" | |
| type: "Concat" | |
| bottom: "size-label" | |
| bottom: "size-label" | |
| top: "size-block" | |
| concat_param { | |
| concat_dim: 1 | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "obj-block" | |
| type: "Concat" | |
| bottom: "obj-label" | |
| bottom: "obj-label" | |
| bottom: "obj-label" | |
| bottom: "obj-label" | |
| top: "obj-block" | |
| concat_param { | |
| concat_dim: 1 | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "bb-label-norm" | |
| type: "Eltwise" | |
| bottom: "bbox-label" | |
| bottom: "size-block" | |
| top: "bbox-label-norm" | |
| eltwise_param { | |
| operation: PROD | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "bb-obj-norm" | |
| type: "Eltwise" | |
| bottom: "bbox-label-norm" | |
| bottom: "obj-block" | |
| top: "bbox-obj-label-norm" | |
| eltwise_param { | |
| operation: PROD | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| ###################################################################### | |
| # Start of convolutional network | |
| ###################################################################### | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "transformed_data" | |
| top: "conv1" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu_conv1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "fire2/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "fire2/squeeze1x1" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire2/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire2/squeeze1x1" | |
| top: "fire2/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire2/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire2/squeeze1x1" | |
| top: "fire2/expand1x1" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire2/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire2/expand1x1" | |
| top: "fire2/expand1x1" | |
| } | |
| layer { | |
| name: "fire2/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire2/squeeze1x1" | |
| top: "fire2/expand3x3" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire2/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire2/expand3x3" | |
| top: "fire2/expand3x3" | |
| } | |
| layer { | |
| name: "fire2/concat" | |
| type: "Concat" | |
| bottom: "fire2/expand1x1" | |
| bottom: "fire2/expand3x3" | |
| top: "fire2/concat" | |
| } | |
| layer { | |
| name: "fire3/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "fire2/concat" | |
| top: "fire3/squeeze1x1" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire3/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire3/squeeze1x1" | |
| top: "fire3/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire3/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire3/squeeze1x1" | |
| top: "fire3/expand1x1" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire3/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire3/expand1x1" | |
| top: "fire3/expand1x1" | |
| } | |
| layer { | |
| name: "fire3/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire3/squeeze1x1" | |
| top: "fire3/expand3x3" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire3/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire3/expand3x3" | |
| top: "fire3/expand3x3" | |
| } | |
| layer { | |
| name: "fire3/concat" | |
| type: "Concat" | |
| bottom: "fire3/expand1x1" | |
| bottom: "fire3/expand3x3" | |
| top: "fire3/concat" | |
| } | |
| layer { | |
| name: "fire4/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "fire3/concat" | |
| top: "fire4/squeeze1x1" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire4/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire4/squeeze1x1" | |
| top: "fire4/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire4/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire4/squeeze1x1" | |
| top: "fire4/expand1x1" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire4/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire4/expand1x1" | |
| top: "fire4/expand1x1" | |
| } | |
| layer { | |
| name: "fire4/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire4/squeeze1x1" | |
| top: "fire4/expand3x3" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire4/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire4/expand3x3" | |
| top: "fire4/expand3x3" | |
| } | |
| layer { | |
| name: "fire4/concat" | |
| type: "Concat" | |
| bottom: "fire4/expand1x1" | |
| bottom: "fire4/expand3x3" | |
| top: "fire4/concat" | |
| } | |
| layer { | |
| name: "fire5/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "fire4/concat" | |
| top: "fire5/squeeze1x1" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire5/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire5/squeeze1x1" | |
| top: "fire5/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire5/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire5/squeeze1x1" | |
| top: "fire5/expand1x1" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire5/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire5/expand1x1" | |
| top: "fire5/expand1x1" | |
| } | |
| layer { | |
| name: "fire5/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire5/squeeze1x1" | |
| top: "fire5/expand3x3" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire5/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire5/expand3x3" | |
| top: "fire5/expand3x3" | |
| } | |
| layer { | |
| name: "fire5/concat" | |
| type: "Concat" | |
| bottom: "fire5/expand1x1" | |
| bottom: "fire5/expand3x3" | |
| top: "fire5/concat" | |
| } | |
| layer { | |
| name: "fire6/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "fire5/concat" | |
| top: "fire6/squeeze1x1" | |
| convolution_param { | |
| num_output: 48 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire6/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire6/squeeze1x1" | |
| top: "fire6/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire6/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire6/squeeze1x1" | |
| top: "fire6/expand1x1" | |
| convolution_param { | |
| num_output: 192 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire6/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire6/expand1x1" | |
| top: "fire6/expand1x1" | |
| } | |
| layer { | |
| name: "fire6/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire6/squeeze1x1" | |
| top: "fire6/expand3x3" | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire6/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire6/expand3x3" | |
| top: "fire6/expand3x3" | |
| } | |
| layer { | |
| name: "fire6/concat" | |
| type: "Concat" | |
| bottom: "fire6/expand1x1" | |
| bottom: "fire6/expand3x3" | |
| top: "fire6/concat" | |
| } | |
| layer { | |
| name: "fire7/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "fire6/concat" | |
| top: "fire7/squeeze1x1" | |
| convolution_param { | |
| num_output: 48 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire7/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire7/squeeze1x1" | |
| top: "fire7/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire7/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire7/squeeze1x1" | |
| top: "fire7/expand1x1" | |
| convolution_param { | |
| num_output: 192 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire7/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire7/expand1x1" | |
| top: "fire7/expand1x1" | |
| } | |
| layer { | |
| name: "fire7/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire7/squeeze1x1" | |
| top: "fire7/expand3x3" | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire7/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire7/expand3x3" | |
| top: "fire7/expand3x3" | |
| } | |
| layer { | |
| name: "fire7/concat" | |
| type: "Concat" | |
| bottom: "fire7/expand1x1" | |
| bottom: "fire7/expand3x3" | |
| top: "fire7/concat" | |
| } | |
| layer { | |
| name: "fire8/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "fire7/concat" | |
| top: "fire8/squeeze1x1" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire8/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire8/squeeze1x1" | |
| top: "fire8/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire8/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire8/squeeze1x1" | |
| top: "fire8/expand1x1" | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire8/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire8/expand1x1" | |
| top: "fire8/expand1x1" | |
| } | |
| layer { | |
| name: "fire8/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire8/squeeze1x1" | |
| top: "fire8/expand3x3" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire8/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire8/expand3x3" | |
| top: "fire8/expand3x3" | |
| } | |
| layer { | |
| name: "fire8/concat" | |
| type: "Concat" | |
| bottom: "fire8/expand1x1" | |
| bottom: "fire8/expand3x3" | |
| top: "fire8/concat" | |
| } | |
| layer { | |
| name: "fire9/squeeze1x1" | |
| type: "Convolution" | |
| bottom: "fire8/concat" | |
| top: "fire9/squeeze1x1" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire9/relu_squeeze1x1" | |
| type: "ReLU" | |
| bottom: "fire9/squeeze1x1" | |
| top: "fire9/squeeze1x1" | |
| } | |
| layer { | |
| name: "fire9/expand1x1" | |
| type: "Convolution" | |
| bottom: "fire9/squeeze1x1" | |
| top: "fire9/expand1x1" | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire9/relu_expand1x1" | |
| type: "ReLU" | |
| bottom: "fire9/expand1x1" | |
| top: "fire9/expand1x1" | |
| } | |
| layer { | |
| name: "fire9/expand3x3" | |
| type: "Convolution" | |
| bottom: "fire9/squeeze1x1" | |
| top: "fire9/expand3x3" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fire9/relu_expand3x3" | |
| type: "ReLU" | |
| bottom: "fire9/expand3x3" | |
| top: "fire9/expand3x3" | |
| } | |
| layer { | |
| name: "fire9/concat" | |
| type: "Concat" | |
| bottom: "fire9/expand1x1" | |
| bottom: "fire9/expand3x3" | |
| top: "fire9/concat" | |
| } | |
| layer { | |
| name: "drop9" | |
| type: "Dropout" | |
| bottom: "fire9/concat" | |
| top: "fire9/concat" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv10" | |
| type: "Convolution" | |
| bottom: "fire9/concat" | |
| top: "conv10" | |
| convolution_param { | |
| num_output: 1000 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| mean: 0.0 | |
| std: 0.01 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu_conv10" | |
| type: "ReLU" | |
| bottom: "conv10" | |
| top: "conv10" | |
| } | |
| layer { | |
| name: "cvg/classifier" | |
| type: "Convolution" | |
| bottom: "conv10" | |
| top: "cvg/classifier" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 3 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0. | |
| } | |
| } | |
| } | |
| layer { | |
| name: "coverage/sig" | |
| type: "Sigmoid" | |
| bottom: "cvg/classifier" | |
| top: "coverage" | |
| } | |
| layer { | |
| name: "bbox/regressor" | |
| type: "Convolution" | |
| bottom: "conv10" | |
| top: "bboxes" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 4 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.03 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0. | |
| } | |
| } | |
| } | |
| ###################################################################### | |
| # End of convolutional network | |
| ###################################################################### | |
| # Convert bboxes | |
| layer { | |
| name: "bbox_mask" | |
| type: "Eltwise" | |
| bottom: "bboxes" | |
| bottom: "coverage-block" | |
| top: "bboxes-masked" | |
| eltwise_param { | |
| operation: PROD | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "bbox-norm" | |
| type: "Eltwise" | |
| bottom: "bboxes-masked" | |
| bottom: "size-block" | |
| top: "bboxes-masked-norm" | |
| eltwise_param { | |
| operation: PROD | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "bbox-obj-norm" | |
| type: "Eltwise" | |
| bottom: "bboxes-masked-norm" | |
| bottom: "obj-block" | |
| top: "bboxes-obj-masked-norm" | |
| eltwise_param { | |
| operation: PROD | |
| } | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| # Loss layers | |
| layer { | |
| name: "bbox_loss" | |
| type: "L1Loss" | |
| bottom: "bboxes-obj-masked-norm" | |
| bottom: "bbox-obj-label-norm" | |
| top: "loss_bbox" | |
| loss_weight: 2 | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| name: "coverage_loss" | |
| type: "EuclideanLoss" | |
| bottom: "coverage" | |
| bottom: "coverage-label" | |
| top: "loss_coverage" | |
| include { phase: TRAIN } | |
| include { phase: TEST stage: "val" } | |
| } | |
| # Cluster bboxes | |
| layer { | |
| type: 'Python' | |
| name: 'cluster' | |
| bottom: 'coverage' | |
| bottom: 'bboxes' | |
| top: 'bbox-list-class0' | |
| top: 'bbox-list-class1' | |
| top: 'bbox-list-class2' | |
| python_param { | |
| module: 'caffe.layers.detectnet.clustering' | |
| layer: 'ClusterDetections' | |
| param_str : '320, 240, 4, 0.4, 2, 0.02, 0, 3' | |
| } | |
| include: { phase: TEST } | |
| } | |
| # Calculate mean average precision | |
| layer { | |
| type: 'Python' | |
| name: 'cluster_gt' | |
| bottom: 'coverage-label' | |
| bottom: 'bbox-label' | |
| top: 'bbox-list-label-class0' | |
| top: 'bbox-list-label-class1' | |
| top: 'bbox-list-label-class2' | |
| python_param { | |
| module: 'caffe.layers.detectnet.clustering' | |
| layer: 'ClusterGroundtruth' | |
| param_str : '320, 240, 4, 3' | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| type: 'Python' | |
| name: 'score-class0' | |
| bottom: 'bbox-list-label-class0' | |
| bottom: 'bbox-list-class0' | |
| top: 'bbox-list-scored-class0' | |
| python_param { | |
| module: 'caffe.layers.detectnet.mean_ap' | |
| layer: 'ScoreDetections' | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| type: 'Python' | |
| name: 'mAP-class0' | |
| bottom: 'bbox-list-scored-class0' | |
| top: 'mAP-class0' | |
| top: 'precision-class0' | |
| top: 'recall-class0' | |
| python_param { | |
| module: 'caffe.layers.detectnet.mean_ap' | |
| layer: 'mAP' | |
| param_str : '320, 240, 4' | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| type: 'Python' | |
| name: 'score-class1' | |
| bottom: 'bbox-list-label-class1' | |
| bottom: 'bbox-list-class1' | |
| top: 'bbox-list-scored-class1' | |
| python_param { | |
| module: 'caffe.layers.detectnet.mean_ap' | |
| layer: 'ScoreDetections' | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| type: 'Python' | |
| name: 'mAP-class1' | |
| bottom: 'bbox-list-scored-class1' | |
| top: 'mAP-class1' | |
| top: 'precision-class1' | |
| top: 'recall-class1' | |
| python_param { | |
| module: 'caffe.layers.detectnet.mean_ap' | |
| layer: 'mAP' | |
| param_str : '320, 240, 4' | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| type: 'Python' | |
| name: 'score-class2' | |
| bottom: 'bbox-list-label-class2' | |
| bottom: 'bbox-list-class2' | |
| top: 'bbox-list-scored-class2' | |
| python_param { | |
| module: 'caffe.layers.detectnet.mean_ap' | |
| layer: 'ScoreDetections' | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } | |
| layer { | |
| type: 'Python' | |
| name: 'mAP-class2' | |
| bottom: 'bbox-list-scored-class2' | |
| top: 'mAP-class2' | |
| top: 'precision-class2' | |
| top: 'recall-class2' | |
| python_param { | |
| module: 'caffe.layers.detectnet.mean_ap' | |
| layer: 'mAP' | |
| param_str : '320, 240, 4' | |
| } | |
| include: { phase: TEST stage: "val" } | |
| } |
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