-[6.2 Test layout analysis results](#62-Test-layout-analysis-results)
-[6.2 Test layout analysis results](#62-Test-layout-analysis-results)
-[7 Model export and inference](#7-Model-export-and-inference)
-[7. Model export and inference](#7-Model-export-and-inference)
-[7.1 Model export](#71-Model-export)
-[7.1 Model export](#71-Model-export)
-[7.2 Model inference](#72-Model-inference)
-[7.2 Model inference](#72-Model-inference)
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@@ -249,7 +249,7 @@ After starting training normally, you will see the following log output:
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@@ -249,7 +249,7 @@ After starting training normally, you will see the following log output:
**Note that the configuration file for prediction / evaluation must be consistent with the training.**
**Note that the configuration file for prediction / evaluation must be consistent with the training.**
### 5.2. FGD Distillation Training
### 5.2. FGD Distillation Training
PaddleDetection supports FGD-based [Focal and Global Knowledge Distillation for Detectors](https://arxiv.org/abs/2111.11837v1) The training process of the target detection model of distillation, FGD distillation is divided into two parts `Focal` and `Global`. `Focal` Distillation separates the foreground and background of the image, allowing the student model to focus on the key pixels of the foreground and background features of the teacher model respectively;` Global`Distillation section reconstructs the relationships between different pixels and transfers them from the teacher to the student to compensate for the global information lost in `Focal`Distillation.
PaddleDetection supports FGD-based [Focal and Global Knowledge Distillation for Detectors](https://arxiv.org/abs/2111.11837v1) The training process of the target detection model of distillation, FGD distillation is divided into two parts `Focal` and `Global`. `Focal` Distillation separates the foreground and background of the image, allowing the student model to focus on the key pixels of the foreground and background features of the teacher model respectively;` Global`Distillation section reconstructs the relationships between different pixels and transfers them from the teacher to the student to compensate for the global information lost in `Focal`Distillation.
