2122 lines
57 KiB
Plaintext
2122 lines
57 KiB
Plaintext
node {
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node {
|
|
name: "BoxPredictor_2/BoxEncodingPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
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"
|
|
attr {
|
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node {
|
|
name: "BoxPredictor_2/ClassPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
input: "BoxPredictor_2/ClassPredictor/convolution"
|
|
input: "BoxPredictor_2/ClassPredictor/biases"
|
|
}
|
|
node {
|
|
name: "paddings"
|
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op: "Const"
|
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attr {
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key: "value"
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value {
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tensor {
|
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dtype: DT_INT32
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tensor_shape {
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node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6/padding"
|
|
op: "Pad"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6"
|
|
input: "paddings"
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_3_1x1_128/Relu6/padding"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/weights"
|
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attr {
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key: "padding"
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}
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}
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}
|
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}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm"
|
|
op: "FusedBatchNorm"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/convolution"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/gamma"
|
|
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"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm/moving_variance"
|
|
attr { key: "epsilon" value { f: 0.001 } }
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
|
|
op: "Relu6"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/BatchNorm"
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/convolution"
|
|
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"
|
|
attr {
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key: "padding"
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value {
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s: "SAME"
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}
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}
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attr {
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key: "strides"
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value {
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}
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}
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}
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm"
|
|
op: "FusedBatchNorm"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/convolution"
|
|
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"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm/moving_variance"
|
|
attr { key: "epsilon" value { f: 0.001 } }
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6"
|
|
op: "Relu6"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/BatchNorm"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_3/BoxEncodingPredictor/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_3_3x3_s2_256/Relu6"
|
|
input: "BoxPredictor_3/BoxEncodingPredictor/weights"
|
|
attr {
|
|
key: "padding"
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value {
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s: "SAME"
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}
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}
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attr {
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key: "strides"
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value {
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}
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}
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}
|
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}
|
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node {
|
|
name: "BoxPredictor_3/BoxEncodingPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
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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attr {
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key: "padding"
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value {
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s: "SAME"
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}
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}
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attr {
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key: "strides"
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value {
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}
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}
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}
|
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}
|
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node {
|
|
name: "BoxPredictor_3/ClassPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
input: "BoxPredictor_3/ClassPredictor/convolution"
|
|
input: "BoxPredictor_3/ClassPredictor/biases"
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6/padding"
|
|
op: "Pad"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6"
|
|
input: "paddings"
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_4_1x1_128/Relu6/padding"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/weights"
|
|
attr {
|
|
key: "padding"
|
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value {
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s: "SAME"
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}
|
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}
|
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attr {
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key: "strides"
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value {
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list {
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i: 1
|
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i: 2
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i: 2
|
|
i: 1
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
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"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/gamma"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/beta"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/moving_mean"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm/moving_variance"
|
|
attr { key: "epsilon" value { f: 0.001 } }
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
|
|
op: "Relu6"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/BatchNorm"
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/weights"
|
|
attr {
|
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key: "padding"
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value {
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s: "SAME"
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}
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}
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attr {
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key: "strides"
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value {
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list {
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}
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}
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}
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm"
|
|
op: "FusedBatchNorm"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/convolution"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/gamma"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/beta"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/moving_mean"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm/moving_variance"
|
|
attr { key: "epsilon" value { f: 0.001 } }
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/Relu6"
|
|
op: "Relu6"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/BatchNorm"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_4/BoxEncodingPredictor/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
|
|
input: "BoxPredictor_4/BoxEncodingPredictor/weights"
|
|
attr {
|
|
key: "padding"
|
|
value {
|
|
s: "SAME"
|
|
}
|
|
}
|
|
attr {
|
|
key: "strides"
|
|
value {
|
|
list {
|
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i: 1
|
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i: 1
|
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i: 1
|
|
i: 1
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
input: "BoxPredictor_4/BoxEncodingPredictor/convolution"
|
|
input: "BoxPredictor_4/BoxEncodingPredictor/biases"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_4/ClassPredictor/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_4_3x3_s2_256/Relu6"
|
|
input: "BoxPredictor_4/ClassPredictor/weights"
|
|
attr {
|
|
key: "padding"
|
|
value {
|
|
s: "SAME"
|
|
}
|
|
}
|
|
attr {
|
|
key: "strides"
|
|
value {
|
|
list {
|
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i: 1
|
|
i: 1
|
|
i: 1
|
|
i: 1
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "BoxPredictor_4/ClassPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
input: "BoxPredictor_4/ClassPredictor/convolution"
|
|
input: "BoxPredictor_4/ClassPredictor/biases"
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_1_Conv2d_5_1x1_64/Relu6"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/weights"
|
|
attr {
|
|
key: "padding"
|
|
value {
|
|
s: "SAME"
|
|
}
|
|
}
|
|
attr {
|
|
key: "strides"
|
|
value {
|
|
list {
|
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i: 1
|
|
i: 2
|
|
i: 2
|
|
i: 1
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm"
|
|
op: "FusedBatchNorm"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/convolution"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/gamma"
|
|
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"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm/moving_variance"
|
|
attr { key: "epsilon" value { f: 0.001 } }
|
|
}
|
|
node {
|
|
name: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
|
|
op: "Relu6"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/BatchNorm"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_5/BoxEncodingPredictor/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
|
|
input: "BoxPredictor_5/BoxEncodingPredictor/weights"
|
|
attr {
|
|
key: "padding"
|
|
value {
|
|
s: "SAME"
|
|
}
|
|
}
|
|
attr {
|
|
key: "strides"
|
|
value {
|
|
list {
|
|
i: 1
|
|
i: 1
|
|
i: 1
|
|
i: 1
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
input: "BoxPredictor_5/BoxEncodingPredictor/convolution"
|
|
input: "BoxPredictor_5/BoxEncodingPredictor/biases"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_5/ClassPredictor/convolution"
|
|
op: "Conv2D"
|
|
input: "FeatureExtractor/MobilenetV1/Conv2d_13_pointwise_2_Conv2d_5_3x3_s2_128/Relu6"
|
|
input: "BoxPredictor_5/ClassPredictor/weights"
|
|
attr {
|
|
key: "padding"
|
|
value {
|
|
s: "SAME"
|
|
}
|
|
}
|
|
attr {
|
|
key: "strides"
|
|
value {
|
|
list {
|
|
i: 1
|
|
i: 1
|
|
i: 1
|
|
i: 1
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "BoxPredictor_5/ClassPredictor/BiasAdd"
|
|
op: "BiasAdd"
|
|
input: "BoxPredictor_5/ClassPredictor/convolution"
|
|
input: "BoxPredictor_5/ClassPredictor/biases"
|
|
}
|
|
### Locations ##################################################################
|
|
node {
|
|
name: "BoxPredictor_0/Flatten"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_0/BoxEncodingPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_1/Flatten"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_1/BoxEncodingPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_2/Flatten"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_2/BoxEncodingPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_3/Flatten"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_3/BoxEncodingPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_4/Flatten"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_5/Flatten"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "concat/axis_flatten"
|
|
op: "Const"
|
|
attr {
|
|
key: "value"
|
|
value {
|
|
tensor {
|
|
dtype: DT_INT32
|
|
tensor_shape {
|
|
}
|
|
int_val: -1
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "concat"
|
|
op: "ConcatV2"
|
|
input: "BoxPredictor_0/Flatten"
|
|
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 ############################################################
|
|
node {
|
|
name: "BoxPredictor_0/Flatten_1"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_0/ClassPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_1/Flatten_1"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_1/ClassPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_2/Flatten_1"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_2/ClassPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_3/Flatten_1"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_3/ClassPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_4/Flatten_1"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_4/ClassPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "BoxPredictor_5/Flatten_1"
|
|
op: "Flatten"
|
|
input: "BoxPredictor_5/ClassPredictor/BiasAdd"
|
|
}
|
|
node {
|
|
name: "concat_1"
|
|
op: "ConcatV2"
|
|
input: "BoxPredictor_0/Flatten_1"
|
|
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"
|
|
}
|
|
################################################################################
|
|
node {
|
|
name: "PriorBox"
|
|
op: "PriorBox"
|
|
input: "BoxPredictor_0/BoxEncodingPredictor/BiasAdd"
|
|
input: "image_tensor"
|
|
attr { key: "min_size" value { i: 60 } }
|
|
attr { key: "flip" value { b: true } }
|
|
attr { key: "clip" value { b: false } }
|
|
attr {
|
|
key: "aspect_ratio"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 1
|
|
}
|
|
}
|
|
float_val: 2.0
|
|
}
|
|
}
|
|
}
|
|
attr {
|
|
key: "scales"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 3
|
|
}
|
|
}
|
|
float_val: 0.5
|
|
float_val: 1.0
|
|
float_val: 1.0
|
|
}
|
|
}
|
|
}
|
|
attr {
|
|
key: "variance"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 4
|
|
}
|
|
}
|
|
float_val: 0.1
|
|
float_val: 0.1
|
|
float_val: 0.2
|
|
float_val: 0.2
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "PriorBox_1"
|
|
op: "PriorBox"
|
|
input: "BoxPredictor_1/BoxEncodingPredictor/BiasAdd"
|
|
input: "image_tensor"
|
|
attr { key: "min_size" value { i: 105 } }
|
|
attr { key: "max_size" value { i: 150 } }
|
|
attr { key: "flip" value { b: true } }
|
|
attr { key: "clip" value { b: false } }
|
|
attr {
|
|
key: "aspect_ratio"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 2
|
|
}
|
|
}
|
|
float_val: 2.0
|
|
float_val: 3.0
|
|
}
|
|
}
|
|
}
|
|
attr {
|
|
key: "variance"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 4
|
|
}
|
|
}
|
|
float_val: 0.1
|
|
float_val: 0.1
|
|
float_val: 0.2
|
|
float_val: 0.2
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "PriorBox_2"
|
|
op: "PriorBox"
|
|
input: "BoxPredictor_2/BoxEncodingPredictor/BiasAdd"
|
|
input: "image_tensor"
|
|
attr { key: "min_size" value { i: 150 } }
|
|
attr { key: "max_size" value { i: 195 } }
|
|
attr { key: "flip" value { b: true } }
|
|
attr { key: "clip" value { b: false } }
|
|
attr {
|
|
key: "aspect_ratio"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 2
|
|
}
|
|
}
|
|
float_val: 2.0
|
|
float_val: 3.0
|
|
}
|
|
}
|
|
}
|
|
attr {
|
|
key: "variance"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 4
|
|
}
|
|
}
|
|
float_val: 0.1
|
|
float_val: 0.1
|
|
float_val: 0.2
|
|
float_val: 0.2
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "PriorBox_3"
|
|
op: "PriorBox"
|
|
input: "BoxPredictor_3/BoxEncodingPredictor/BiasAdd"
|
|
input: "image_tensor"
|
|
attr { key: "min_size" value { i: 195 } }
|
|
attr { key: "max_size" value { i: 240 } }
|
|
attr { key: "flip" value { b: true } }
|
|
attr { key: "clip" value { b: false } }
|
|
attr {
|
|
key: "aspect_ratio"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 2
|
|
}
|
|
}
|
|
float_val: 2.0
|
|
float_val: 3.0
|
|
}
|
|
}
|
|
}
|
|
attr {
|
|
key: "variance"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 4
|
|
}
|
|
}
|
|
float_val: 0.1
|
|
float_val: 0.1
|
|
float_val: 0.2
|
|
float_val: 0.2
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "PriorBox_4"
|
|
op: "PriorBox"
|
|
input: "BoxPredictor_4/BoxEncodingPredictor/BiasAdd"
|
|
input: "image_tensor"
|
|
attr { key: "min_size" value { i: 240 } }
|
|
attr { key: "max_size" value { i: 285 } }
|
|
attr { key: "flip" value { b: true } }
|
|
attr { key: "clip" value { b: false } }
|
|
attr {
|
|
key: "aspect_ratio"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 2
|
|
}
|
|
}
|
|
float_val: 2.0
|
|
float_val: 3.0
|
|
}
|
|
}
|
|
}
|
|
attr {
|
|
key: "variance"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 4
|
|
}
|
|
}
|
|
float_val: 0.1
|
|
float_val: 0.1
|
|
float_val: 0.2
|
|
float_val: 0.2
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "PriorBox_5"
|
|
op: "PriorBox"
|
|
input: "BoxPredictor_5/BoxEncodingPredictor/BiasAdd"
|
|
input: "image_tensor"
|
|
attr { key: "min_size" value { i: 285 } }
|
|
attr { key: "max_size" value { i: 300 } }
|
|
attr { key: "flip" value { b: true } }
|
|
attr { key: "clip" value { b: false } }
|
|
attr {
|
|
key: "aspect_ratio"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 2
|
|
}
|
|
}
|
|
float_val: 2.0
|
|
float_val: 3.0
|
|
}
|
|
}
|
|
}
|
|
attr {
|
|
key: "variance"
|
|
value {
|
|
tensor {
|
|
dtype: DT_FLOAT
|
|
tensor_shape {
|
|
dim {
|
|
size: 4
|
|
}
|
|
}
|
|
float_val: 0.1
|
|
float_val: 0.1
|
|
float_val: 0.2
|
|
float_val: 0.2
|
|
}
|
|
}
|
|
}
|
|
}
|
|
node {
|
|
name: "concat_2"
|
|
op: "ConcatV2"
|
|
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: 1 } }
|
|
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 } }
|
|
}
|