Why I can't get 40 FPS for TLT YOLOv3 ResNet18 FP16 in 320x320?

Accelerated Computing Intelligent Video Analytics DeepStream SDK
,
1

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) Jetson Nano B01
• DeepStream Version 5.0.1
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)
• Issue Type( questions, new requirements, bugs) question
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)

Hi, I’m refer to this doc Performance — DeepStream 6.1.1 Release documentation

YoloV3 – ResNet18 in FP16 on Jetson Nano has 11 FPS in 960x544 resolution. I’ve checked it in Jetson Nano, convert provided models and really get ~11 FPS.

So when I train YoloV3 ResNet18 with Transfer Learning Toolkit in 320x320 and convert it to FP16 in Jetson Nano I get only 20 FPS and 11FPS in FP32 - why?

  1. How inference resolution affect on model performance?
  2. What’s the maximum performance for YOLOv3 Resnet18 on Jetson Nano in 320x320?
  3. How to get the maximum performance YOLOv3 Resnet18 on Jetson Nano in 320x320?