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@ -121,7 +121,7 @@ class Yolov3LossOpMaker : public framework::OpProtoAndCheckerMaker {
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"mask for calculate objectness loss in gradient kernel.")
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.AsIntermediate();
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AddOutput("GTMatchMask",
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"This is an intermediate tensor with shape if [N, B], "
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"This is an intermediate tensor with shape of [N, B], "
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"B is the max box number of GT boxes. This parameter caches "
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"matched mask index of each GT boxes for gradient calculate.")
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.AsIntermediate();
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@ -175,7 +175,7 @@ class Yolov3LossOpMaker : public framework::OpProtoAndCheckerMaker {
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thresh, the confidence score loss of this anchor box will be ignored.
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Therefore, the yolov3 loss consist of three major parts, box location loss,
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confidence score loss, and classification loss. The L1 loss is used for
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confidence score loss, and classification loss. The L2 loss is used for
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box coordinates (w, h), and sigmoid cross entropy loss is used for box
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coordinates (x, y), confidence score loss and classification loss.
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