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 https://docs.nvidia.com/metropolis/deepstream/dev-guide/text/DS_Performance.html
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?
- How inference resolution affect on model performance?
- What’s the maximum performance for YOLOv3 Resnet18 on Jetson Nano in 320x320?
- How to get the maximum performance YOLOv3 Resnet18 on Jetson Nano in 320x320?