Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU) A6000
• DeepStream Version N/A
• JetPack Version (valid for Jetson only) N?A
• TensorRT Version 24.01 (Docker container)
• NVIDIA GPU Driver Version (valid for GPU only) 535.154.05
• 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) Run triton on CityScapes models
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)
Hi
I’ve been using the CitySemSeg etlt model (1080x1920) with deepstream using a C++ pipeline. All is working fine. I noticed there are new models called Pre-trained Segformer - CityScapes with onnx models (they appear to be annotated _224). I converted those to TensorRT and served from Triton Inference Server. I’m using the Python client however I need to adjust the input tensors to [3,244,244]. I did have them at [3,1024,1024] as suggested by the model narrative. The reduction in input shape makes the output tensors poor in appearance - are there [3,1024,1024] versions?
It doesn’t make much difference using Deepstream as the input shape is [3,224,224].
Cheers
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