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Marcos Luciano
2023-05-19 03:05:43 -03:00
parent 68f762d5bd
commit 07feae9509
86 changed files with 1523 additions and 5223 deletions
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docs/YOLOX.md
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@@ -1,5 +1,7 @@
# YOLOX usage
**NOTE**: You can use the main branch of the YOLOX repo to convert all model versions.
**NOTE**: The yaml file is not required.
* [Convert model](#convert-model)
@@ -18,13 +20,15 @@
git clone https://github.com/Megvii-BaseDetection/YOLOX.git
cd YOLOX
pip3 install -r requirements.txt
python3 setup.py develop
pip3 install onnx onnxsim onnxruntime
```
**NOTE**: It is recommended to use Python virtualenv.
#### 2. Copy conversor
Copy the `gen_wts_yolox.py` file from `DeepStream-Yolo/utils` directory to the `YOLOX` folder.
Copy the `export_yolox.py` file from `DeepStream-Yolo/utils` directory to the `YOLOX` folder.
#### 3. Download the model
@@ -34,19 +38,19 @@ Download the `pth` file from [YOLOX](https://github.com/Megvii-BaseDetection/YOL
wget https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_s.pth
```
**NOTE**: You can use your custom model, but it is important to keep the YOLO model reference (`yolox_`) in you `cfg` and `weights`/`wts` filenames to generate the engine correctly.
**NOTE**: You can use your custom model.
#### 4. Convert model
Generate the `cfg` and `wts` files (example for YOLOX-s standard)
Generate the ONNX model file (example for YOLOX-s standard)
```
python3 gen_wts_yolox.py -w yolox_s.pth -e exps/default/yolox_s.py
python3 export_yolox.py -w yolox_s.pth -c exps/default/yolox_s.py --simplify
```
#### 5. Copy generated files
Copy the generated `cfg` and `wts` files to the `DeepStream-Yolo` folder.
Copy the generated ONNX model file to the `DeepStream-Yolo` folder.
##
@@ -99,11 +103,13 @@ Edit the `config_infer_primary_yolox.txt` file according to your model (example
```
[property]
...
custom-network-config=yolox_s.cfg
model-file=yolox_s.wts
onnx-file=yolox_s.onnx
model-engine-file=yolox_s.onnx_b1_gpu0_fp32.engine
...
num-detected-classes=80
...
parse-bbox-func-name=NvDsInferParseYolo
...
```
**NOTE**: If you use the **legacy** model, you should edit the `config_infer_primary_yolox_legacy.txt` file.