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Add PP-YOLOE+ support

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Marcos Luciano
2023-01-31 02:59:56 -03:00
parent 825d6bfda8
commit 69f29f8934
4 changed files with 61 additions and 24 deletions
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docs/PPYOLOE.md
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@@ -1,8 +1,8 @@
# PP-YOLOE usage
# PP-YOLOE / PP-YOLOE+ usage
* [Convert model](#convert-model)
* [Compile the lib](#compile-the-lib)
* [Edit the config_infer_primary_ppyoloe file](#edit-the-config_infer_primary_ppyoloe-file)
* [Edit the config_infer_primary_ppyoloe_plus file](#edit-the-config_infer_primary_ppyoloe_plus-file)
* [Edit the deepstream_app_config file](#edit-the-deepstream_app_config-file)
* [Testing the model](#testing-the-model)
@@ -12,7 +12,7 @@
#### 1. Download the PaddleDetection repo and install the requirements
https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.4/docs/tutorials/INSTALL.md
https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/tutorials/INSTALL.md
**NOTE**: It is recommended to use Python virtualenv.
@@ -22,20 +22,20 @@ Copy the `gen_wts_ppyoloe.py` file from `DeepStream-Yolo/utils` directory to the
#### 3. Download the model
Download the `pdparams` file from [PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/ppyoloe) releases (example for PP-YOLOE-s)
Download the `pdparams` file from [PP-YOLOE](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/ppyoloe) releases (example for PP-YOLOE+_s)
```
wget https://paddledet.bj.bcebos.com/models/ppyoloe_crn_s_400e_coco.pdparams
wget https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_80e_coco.pdparams
```
**NOTE**: You can use your custom model, but it is important to keep the YOLO model reference (`ppyoloe_`) in you `cfg` and `weights`/`wts` filenames to generate the engine correctly.
#### 4. Convert model
Generate the `cfg` and `wts` files (example for PP-YOLOE-s)
Generate the `cfg` and `wts` files (example for PP-YOLOE+_s)
```
python3 gen_wts_ppyoloe.py -w ppyoloe_crn_s_400e_coco.pdparams -c configs/ppyoloe/ppyoloe_crn_s_400e_coco.yml
python3 gen_wts_ppyoloe.py -w ppyoloe_plus_crn_s_80e_coco.pdparams -c configs/ppyoloe/ppyoloe_plus_crn_s_80e_coco.yml
```
#### 5. Copy generated files
@@ -80,19 +80,27 @@ Open the `DeepStream-Yolo` folder and compile the lib
##
### Edit the config_infer_primary_ppyoloe file
### Edit the config_infer_primary_ppyoloe_plus file
Edit the `config_infer_primary_ppyoloe.txt` file according to your model (example for PP-YOLOE-s)
Edit the `config_infer_primary_ppyoloe_plus.txt` file according to your model (example for PP-YOLOE+_s)
```
[property]
...
custom-network-config=ppyoloe_crn_s_400e_coco.cfg
model-file=ppyoloe_crn_s_400e_coco.wts
custom-network-config=ppyoloe_plus_crn_s_80e_coco.cfg
model-file=ppyoloe_plus_crn_s_80e_coco.wts
...
```
**NOTE**: The PP-YOLOE uses normalization on the image preprocess. It is important to change the `net-scale-factor` and `offsets` according to the trained values.
**NOTE**: If you use the **legacy** model, you should edit the `config_infer_primary_ppyoloe.txt` file.
**NOTE**: The **PP-YOLOE+** uses zero mean normalization on the image preprocess. It is important to change the `net-scale-factor` according to the trained values.
```
net-scale-factor=0.0039215697906911373
```
**NOTE**: The **PP-YOLOE (legacy)** uses normalization on the image preprocess. It is important to change the `net-scale-factor` and `offsets` according to the trained values.
Default: `mean = 0.485, 0.456, 0.406` and `std = 0.229, 0.224, 0.225`
@@ -109,9 +117,11 @@ offsets=123.675;116.28;103.53
...
[primary-gie]
...
config-file=config_infer_primary_ppyoloe.txt
config-file=config_infer_primary_ppyoloe_plus.txt
```
**NOTE**: If you use the **legacy** model, you should edit it to `config_infer_primary_ppyoloe.txt`.
##
### Testing the model