@@ -319,11 +319,10 @@ After the extraction is complete, use [ch_PP-OCRv2_rec.yml](../../configs/rec/ch
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### 2.2 Detection Model Configuration File Analysis
The configuration file of the detection model distillation is in the ```PaddleOCR/configs/det/ch_PP-OCRv2/``` directory, which contains three distillation configuration files:
The configuration file of the detection model distillation is in the ```PaddleOCR/configs/det/ch_PP-OCRv3/``` directory, which contains three distillation configuration files:
-```ch_PP-OCRv2_det_cml.yml```, Use one large model to distill two small models, and the two small models learn from each other
-```ch_PP-OCRv2_det_dml.yml```, Method of mutual distillation of two student models
-```ch_PP-OCRv2_det_distill.yml```, The method of using large teacher model to distill small student model
-```ch_PP-OCRv3_det_cml.yml```, Use one large model to distill two small models, and the two small models learn from each other
-```ch_PP-OCRv3_det_dml.yml```, Method of mutual distillation of two student models
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#### 2.2.1 Model Structure
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@@ -341,39 +340,40 @@ Architecture:
model_type: det
algorithm: DB
Backbone:
name: MobileNetV3
scale: 0.5
model_name: large
disable_se: True
name: ResNet
in_channels: 3
layers: 50
Neck:
name: DBFPN
out_channels: 96
name: LKPAN
out_channels: 256
Head:
name: DBHead
kernel_list: [7,2,2]
k: 50
Teacher: # Another sub-network, here is a distillation example of a large model distill a small model
freeze_params: true # The Teacher model is well-trained and does not need to participate in training
return_all_feats: false
model_type: det
algorithm: DB
Transform:
Backbone:
name: ResNet
layers: 18
in_channels: 3
layers: 50
Neck:
name: DBFPN
name: LKPAN
out_channels: 256
Head:
name: DBHead
kernel_list: [7,2,2]
k: 50
```
If DML is used, that is, the method of two small models learning from each other, the Teacher network structure in the above configuration file needs to be set to the same configuration as the Student model.
Refer to the configuration file for details. [ch_PP-OCRv2_det_dml.yml](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.4/configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_dml.yml)
Refer to the configuration file for details. [ch_PP-OCRv3_det_dml.yml](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.4/configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_dml.yml)
The following describes the configuration file parameters [ch_PP-OCRv2_det_cml.yml](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.4/configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml):
The following describes the configuration file parameters [ch_PP-OCRv3_det_cml.yml](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.4/configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_cml.yml):
```
Architecture:
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@@ -390,12 +390,14 @@ Architecture:
Transform:
Backbone:
name: ResNet
layers: 18
in_channels: 3
layers: 50
Neck:
name: DBFPN
name: LKPAN
out_channels: 256
Head:
name: DBHead
kernel_list: [7,2,2]
k: 50
Student: # Student model configuration for CML distillation
@@ -460,34 +464,7 @@ The key contains `backbone_out`, `neck_out`, `head_out`, and `value` is the tens
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#### 2.2.2 Loss Function
In the task of detection knowledge distillation ```ch_PP-OCRv2_det_distill.yml````, the distillation loss function configuration is as follows.
```yaml
Loss:
name: CombinedLoss # Loss function name
loss_config_list: # List of loss function configuration files, mandatory functions for CombinedLoss
- DistillationDilaDBLoss: # DB loss function based on distillation, inherited from standard DBloss
weight: 1.0 # The weight of the loss function. In loss_config_list, each loss function must include this field
model_name_pairs: # Extract the output of these two sub-networks and calculate the loss between them
- ["Student", "Teacher"]
key: maps # In the sub-network output dict, take the corresponding tensor
balance_loss: true # The following parameters are the configuration parameters of standard DBloss
main_loss_type: DiceLoss
alpha: 5
beta: 10
ohem_ratio: 3
- DistillationDBLoss: # Used to calculate the loss between Student and GT
weight: 1.0
model_name_list: ["Student"] # The model name only has Student, which means that the loss between Student and GT is calculated
name: DBLoss
balance_loss: true
main_loss_type: DiceLoss
alpha: 5
beta: 10
ohem_ratio: 3
```
Similarly, distillation loss function configuration(`ch_PP-OCRv2_det_cml.yml`) is shown below. Compared with the loss function configuration of ch_PP-OCRv2_det_distill.yml, there are three changes:
The distillation loss function configuration(`ch_PP-OCRv3_det_cml.yml`) is shown below. Compared with the loss function configuration of ch_PP-OCRv3_det_distill.yml, there are three changes:
```yaml
Loss:
name:CombinedLoss
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@@ -530,7 +507,7 @@ In the task of detecting knowledge distillation, the post-processing configurati
```yaml
PostProcess:
name: DistillationDBPostProcess # The CTC decoding post-processing of the DB detection distillation task, inherited from the standard DBPostProcess class
name:DistillationDBPostProcess# The post-processing of the DB detection distillation task, inherited from the standard DBPostProcess class
model_name:["Student","Student2","Teacher"]# Extract the output of multiple sub-networks and decode them. The network that does not require post-processing is not set in model_name
thresh:0.3
box_thresh:0.6
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@@ -561,9 +538,9 @@ Model Structure
#### 2.2.5 Fine-tuning Distillation Model
There are three ways to fine-tune the detection distillation task:
- `ch_PP-OCRv2_det_distill.yml`, The teacher model is set to the model provided by PaddleOCR or the large model you have trained.
- `ch_PP-OCRv2_det_cml.yml`, Use cml distillation. Similarly, the Teacher model is set to the model provided by PaddleOCR or the large model you have trained.
- `ch_PP-OCRv2_det_dml.yml`, Distillation using DML. The method of mutual distillation of the two Student models has an accuracy improvement of about 1.7% on the data set used by PaddleOCR.
-`ch_PP-OCRv3_det_distill.yml`, The teacher model is set to the model provided by PaddleOCR or the large model you have trained.
-`ch_PP-OCRv3_det_cml.yml`, Use cml distillation. Similarly, the Teacher model is set to the model provided by PaddleOCR or the large model you have trained.
-`ch_PP-OCRv3_det_dml.yml`, Distillation using DML. The method of mutual distillation of the two Student models has an accuracy improvement of about 1.7% on the data set used by PaddleOCR.
In fine-tune, you need to set the pre-trained model to be loaded in the `pretrained` parameter of the network structure.
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@@ -572,13 +549,13 @@ In terms of accuracy improvement, `cml` > `dml` > `distill`. When the amount of
In addition, since the distillation pre-training model provided by PaddleOCR contains multiple model parameters, if you want to extract the parameters of the student model, you can refer to the following code:
```sh
# Download the parameters of the distillation training model
