https://github.com/DanaHan/Yolov5-in-Deepstream-5.0

Describe how to use yolov5 in Deepstream 5.0
https://github.com/DanaHan/Yolov5-in-Deepstream-5.0

Last synced: 12 days ago
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Describe how to use yolov5 in Deepstream 5.0

• Host: GitHub
• URL: https://github.com/DanaHan/Yolov5-in-Deepstream-5.0
• Owner: DanaHan
• Created: 2020-09-01T13:03:35.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2023-10-17T22:27:46.000Z (8 months ago)
• Last Synced: 2024-02-29T09:31:37.045Z (4 months ago)
• Language: C++
• Size: 125 KB
• Stars: 209
• Watchers: 5
• Forks: 58
• Open Issues: 25
• Metadata Files:
  • Readme: README.md

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• awesome-yolo-object-detection - DanaHan/Yolov5-in-Deepstream-5.0 - in-Deepstream-5.0?style=social"/> : Describe how to use yolov5 in Deepstream 5.0. (Lighter and Deployment Frameworks)

README

        
# 0.Instruction

This Repos contains how to run yolov5 model in DeepStream 5.0

# 1.Geneate yolov5 engine model 

We can use https://github.com/wang-xinyu/tensorrtx yolov5 to generate engine model

### Important Note:

   You should replace yololayer.cu and hardswish.cu file in tensorrtx/yolov5

### How to Run, yolov5s as example

-- a). generate yolov5s.wts from pytorch with yolov5s.pt

```

git clone https://github.com/wang-xinyu/tensorrtx.git

git clone https://github.com/ultralytics/yolov5.git

// download its weights 'yolov5s.pt'

// copy tensorrtx/yolov5/gen_wts.py into ultralytics/yolov5

// ensure the file name is yolov5s.pt and yolov5s.wts in gen_wts.py

// go to ultralytics/yolov5

python gen_wts.py

// a file 'yolov5s.wts' will be generated.

```

-- b). build tensorrtx/yolov5 and run

```

// put yolov5s.wts into tensorrtx/yolov5

// go to tensorrtx/yolov5

// ensure the macro NET in yolov5.cpp is s

mkdir build

cd build

cmake ..

make

sudo ./yolov5 -s             // serialize model to plan file i.e. 'yolov5s.engine'

```

We can get 'yolov5s.engine' and 'libmyplugin.so' here for the future use.

# 2.Build DeepStream 5.0 nvdsinfer_custom_impl_yolo plugin

In Deepstream 5.0/nvdsinfer_custom_impl_Yolo Directory, exec 'make' command.

We can get libnvdsinfer_custom_impl_Yolo.so here.

# 3.Modify configure file

After build yolov5 plugin, modify 'config_infer_primary_yoloV5.txt' in Deepstream 5.0 Directory.

-- a).In Line 58. "parse-bbox-func-name=NvDsInferParseCustomYoloV5"   // This is the bbox parse function name.

-- b).In Line 59. "custom-lib-path"   // This is DeepStream plugin path.

-- c).In Line 56. Comment "#cluster-mode=2". Becase we use custom NMS function.

# 4. How to run it

Running the application as

```

LD_PRELOAD=./libcustomOp.so deepstream-app -c 

```