thebears/deepstream_yolo
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Add benchmarks

Browse Source
This commit is contained in:
Marcos Luciano
2023-05-19 17:22:47 -03:00
parent 07feae9509
commit af20c2f72c
10 changed files with 112 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
docs/YOLOX.md
View File

@@ -32,7 +32,7 @@ Copy the `export_yolox.py` file from `DeepStream-Yolo/utils` directory to the `Y
#### 3. Download the model
Download the `pth` file from [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX/releases/) releases (example for YOLOX-s standard)
Download the `pth` file from [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX/releases/) releases (example for YOLOX-s)
```
wget https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_s.pth
@@ -42,7 +42,7 @@ wget https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yo
#### 4. Convert model
Generate the ONNX model file (example for YOLOX-s standard)
Generate the ONNX model file (example for YOLOX-s)
```
python3 export_yolox.py -w yolox_s.pth -c exps/default/yolox_s.py --simplify
@@ -98,7 +98,7 @@ Open the `DeepStream-Yolo` folder and compile the lib
### Edit the config_infer_primary_yolox file
Edit the `config_infer_primary_yolox.txt` file according to your model (example for YOLOX-s standard with 80 classes)
Edit the `config_infer_primary_yolox.txt` file according to your model (example for YOLOX-s with 80 classes)
```
[property]
@@ -114,10 +114,17 @@ parse-bbox-func-name=NvDsInferParseYolo
**NOTE**: If you use the **legacy** model, you should edit the `config_infer_primary_yolox_legacy.txt` file.
**NOTE**: The **YOLOX standard** uses no normalization on the image preprocess. It is important to change the `net-scale-factor` according to the trained values.
**NOTE**: The **YOLOX and YOLOX legacy** resize the input with left/top padding. To get better accuracy, use
```
net-scale-factor=0
maintain-aspect-ratio=1
symmetric-padding=0
```
**NOTE**: The **YOLOX** uses no normalization on the image preprocess. It is important to change the `net-scale-factor` according to the trained values.
```
net-scale-factor=1
```
**NOTE**: The **YOLOX legacy** uses normalization on the image preprocess. It is important to change the `net-scale-factor` and `offsets` according to the trained values.
@@ -150,4 +157,6 @@ config-file=config_infer_primary_yolox.txt
deepstream-app -c deepstream_app_config.txt
```
**NOTE**: The TensorRT engine file may take a very long time to generate (sometimes more than 10 minutes).
**NOTE**: For more information about custom models configuration (`batch-size`, `network-mode`, etc), please check the [`docs/customModels.md`](customModels.md) file.