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January 24, 2018 10:58
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise/BatchNorm/moving_mean" | |
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| node { | |
| name: "BoxPredictor_1/ClassPredictor/convolution" | |
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| input: "BoxPredictor_1/ClassPredictor/weights" | |
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| name: "BoxPredictor_0/BoxEncodingPredictor/convolution" | |
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| node { | |
| name: "BoxPredictor_0/ClassPredictor/convolution" | |
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| input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_11_pointwise/Relu6" | |
| input: "BoxPredictor_0/ClassPredictor/weights" | |
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| input: "BoxPredictor_0/ClassPredictor/convolution" | |
| input: "BoxPredictor_0/ClassPredictor/biases" | |
| } | |
| node { | |
| name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/convolution" | |
| op: "Conv2D" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_2_1x1_256/Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/weights" | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/convolution" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/gamma" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/beta" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/moving_mean" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm/moving_variance" | |
| attr { key: "epsilon" value { f: 0.001 } } | |
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| node { | |
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| op: "Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/BatchNorm" | |
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| op: "Conv2D" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6" | |
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| op: "FusedBatchNorm" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/convolution" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/gamma" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/beta" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm/moving_mean" | |
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| attr { key: "epsilon" value { f: 0.001 } } | |
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| op: "Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/BatchNorm" | |
| } | |
| node { | |
| name: "BoxPredictor_2/BoxEncodingPredictor/convolution" | |
| op: "Conv2D" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6" | |
| input: "BoxPredictor_2/BoxEncodingPredictor/weights" | |
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| input: "BoxPredictor_2/BoxEncodingPredictor/convolution" | |
| input: "BoxPredictor_2/BoxEncodingPredictor/biases" | |
| } | |
| node { | |
| name: "BoxPredictor_2/ClassPredictor/convolution" | |
| op: "Conv2D" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_2_3x3_s2_512/Relu6" | |
| input: "BoxPredictor_2/ClassPredictor/weights" | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/weights" | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/beta" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/moving_mean" | |
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| attr { key: "epsilon" value { f: 0.001 } } | |
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| op: "Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm" | |
| } | |
| node { | |
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| op: "Conv2D" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/weights" | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/gamma" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/beta" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/moving_mean" | |
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| attr { key: "epsilon" value { f: 0.001 } } | |
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| node { | |
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| op: "Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm" | |
| } | |
| node { | |
| name: "BoxPredictor_3/BoxEncodingPredictor/convolution" | |
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| input: "BoxPredictor_3/BoxEncodingPredictor/convolution" | |
| input: "BoxPredictor_3/BoxEncodingPredictor/biases" | |
| } | |
| node { | |
| name: "BoxPredictor_3/ClassPredictor/convolution" | |
| op: "Conv2D" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6" | |
| input: "BoxPredictor_3/ClassPredictor/weights" | |
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| op: "BiasAdd" | |
| input: "BoxPredictor_3/ClassPredictor/convolution" | |
| input: "BoxPredictor_3/ClassPredictor/biases" | |
| } | |
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| # input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6" | |
| # input: "paddings" | |
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| op: "Conv2D" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/weights" | |
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| name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm" | |
| op: "FusedBatchNorm" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/convolution" | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/beta" | |
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| node { | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/Relu6" | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/convolution" | |
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| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/beta" | |
| input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/moving_mean" | |
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| input: "BoxPredictor_5/ClassPredictor/weights" | |
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| input: "BoxPredictor_5/ClassPredictor/convolution" | |
| input: "BoxPredictor_5/ClassPredictor/biases" | |
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| ### Locations ################################################################## | |
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| input: "BoxPredictor_0/BoxEncodingPredictor/BiasAdd" | |
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| input: "BoxPredictor_2/BoxEncodingPredictor/BiasAdd" | |
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| node { | |
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| op: "Flatten" | |
| input: "BoxPredictor_3/BoxEncodingPredictor/BiasAdd" | |
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| node { | |
| name: "BoxPredictor_4/Flatten" | |
| op: "Flatten" | |
| input: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd" | |
| } | |
| node { | |
| name: "BoxPredictor_5/Flatten" | |
| op: "Flatten" | |
| input: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd" | |
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| input: "BoxPredictor_1/Flatten" | |
| input: "BoxPredictor_2/Flatten" | |
| input: "BoxPredictor_3/Flatten" | |
| input: "BoxPredictor_4/Flatten" | |
| input: "BoxPredictor_5/Flatten" | |
| input: "concat/axis_flatten" | |
| } | |
| ### Classifications ############################################################ | |
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| op: "Flatten" | |
| input: "BoxPredictor_0/ClassPredictor/BiasAdd" | |
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| input: "BoxPredictor_1/Flatten_1" | |
| input: "BoxPredictor_2/Flatten_1" | |
| input: "BoxPredictor_3/Flatten_1" | |
| input: "BoxPredictor_4/Flatten_1" | |
| input: "BoxPredictor_5/Flatten_1" | |
| input: "concat/axis_flatten" | |
| } | |
| ################################################################################ | |
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| input: "PriorBox" | |
| input: "PriorBox_1" | |
| input: "PriorBox_2" | |
| input: "PriorBox_3" | |
| input: "PriorBox_4" | |
| input: "PriorBox_5" | |
| input: "concat/axis_flatten" | |
| } | |
| ################################################################################ | |
| node { | |
| name: "concat_1_sigmoid" | |
| op: "Sigmoid" | |
| input: "concat_1" | |
| } | |
| node { | |
| name: "detection_out" | |
| op: "DetectionOutput" | |
| input: "concat" | |
| input: "concat_1_sigmoid" | |
| input: "concat_2" | |
| attr { key: "num_classes" value { i: 2 } } | |
| attr { key: "share_location" value { b: true } } | |
| attr { key: "background_label_id" value { i: 0 } } | |
| attr { key: "nms_threshold" value { f: 0.6 } } | |
| attr { key: "top_k" value { i: 100 } } | |
| attr { key: "code_type" value { s: "CENTER_SIZE" } } | |
| attr { key: "keep_top_k" value { i: 100 } } | |
| attr { key: "confidence_threshold" value { f: 0.01 } } | |
| attr { key: "loc_pred_transposed" value { b: true } } | |
| } |
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