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@ -22,36 +22,39 @@ class Detection_output_OpMaker : public framework::OpProtoAndCheckerMaker {
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framework::OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("Loc",
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"(Tensor) The input tensor of detection_output operator. "
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"(Tensor) The input tensor of detection_output operator."
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"The input predict locations"
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"The format of input tensor is kNCHW. Where K is priorbox point "
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"numbers,"
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"N is How many boxes are there on each point, "
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"C is 4, H and W both are 1.");
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AddInput("Conf",
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"(Tensor) The input tensor of detection_output operator. "
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"(Tensor) The input tensor of detection_output operator."
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"The input priorbox confidence."
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"The format of input tensor is kNCHW. Where K is priorbox point "
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"numbers,"
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"N is How many boxes are there on each point, "
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"C is the number of classes, H and W both are 1.");
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AddInput("PriorBox",
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"(Tensor) The input tensor of detection_output operator. "
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"(Tensor) The input tensor of detection_output operator."
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"The format of input tensor is the position and variance "
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"of the boxes");
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AddOutput("Out",
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"(Tensor) The output tensor of detection_output operator.");
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AddAttr<int>("background_label_id",
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"(int), the attr of detection_output operator");
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AddAttr<int>("num_classes",
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"(int), the attr of detection_output operator");
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AddAttr<int>("background_label_id", "(int), The background class index.");
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AddAttr<int>("num_classes", "(int), The number of the classification.");
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AddAttr<float>("nms_threshold",
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"(float), the attr of detection_output operator");
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"(float), The Non-maximum suppression threshold.");
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AddAttr<float>("confidence_threshold",
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"(float), the attr of detection_output operator");
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AddAttr<int>("top_k", "(int), the attr of detection_output operator");
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AddAttr<int>("nms_top_k", "(int), the attr of detection_output operator");
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"(float), The classification confidence threshold.");
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AddAttr<int>("top_k", "(int), The bbox number kept of the layer’s output.");
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AddAttr<int>("nms_top_k",
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"(int), The bbox number kept of the NMS’s output.");
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AddComment(R"DOC(
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detection output for SSD(single shot multibox detector)
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Apply the NMS to the output of network and compute the predict
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bounding box location. The output’s shape of this layer could
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be zero if there is no valid bounding box.
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)DOC");
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}
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};
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