Scaled-YOLOv4 in Deepstream

Accelerated Computing Intelligent Video Analytics DeepStream SDK
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Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) GPU
• DeepStream Version 5.0.1
• JetPack Version (valid for Jetson only)
• TensorRT Version 7.0
• NVIDIA GPU Driver Version (valid for GPU only) 440
• Issue Type( questions, new requirements, bugs) questions

Hi I have previously run yolov4 on deepstream using yolov4_deepstream/README.md at master · NVIDIA-AI-IOT/yolov4_deepstream · GitHub and it works well.

I see that recently there is a vastly improved Yolov4 https://github.com/AlexeyAB/darknet/issues/7087 Scaled-Yolov4. I tried to use the new cfg file and weights for this version with the above nvidia deepstream github but while it builds the results are worse than normal yolov4.

Is there something I need to change to be able to use this new model? Thanks

1 Like
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Does the Scaled-YoloV4 require different pre-processing, e.g. maintain-aspect-ratio ?

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Not sure, reading the paper now https://arxiv.org/pdf/2011.08036.pdf

If it does can I try and set maintain-aspect-ratio=0? I note in yolov4 config its =1

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yes, you could take a quick try.

And, you can use yolov4_deepstream/tensorrt_yolov4 at master · NVIDIA-AI-IOT/yolov4_deepstream · GitHub to evaluate the accuracy with Coco dataset.

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Hi,

I am also very interested in this topic. Did you finally get the chanve to try it in Deepstream and if so, what was the performance?

I was very surprised as they stated that with Jetson Nano it was possible to get up to 39 FPS, which is a very promising performance.

Best regards,
Alberto