Comments (1)
Since the YoloV5 repository https://github.com/ultralytics/yolov5/ provides a export to ONNX, you should be able to run it using Triton Inference Server under this DeepStream-app example. That said, you'll most probably have to write your own parser for the network output.
Some references to help you get started:
The custom parser section from: https://developer.nvidia.com/blog/deploying-models-from-tensorflow-model-zoo-using-deepstream-and-triton-inference-server/
YOLOv5 to ONNX: ultralytics/yolov5#251
^ this link also provides a way to turn the model into a TRT Engine, but YMMV for the Tensorrtx translation.
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Related Issues (16)
- Unexpected platform and fail to load model (Solved onnx with triton not suported on Jetson) HOT 6
- an error about loading model by using triton HOT 2
- is there any example with python? HOT 1
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- Jetpack 4.5 triton 2.10 - deepstream 5.1 on Jetson Xavier NX HOT 4
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- Problem with running centerface model. HOT 10
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- Using Centernet model with batching in Deepstream HOT 3
- Does nvcr.io/nvidia/deepstream:5.0.1-20.09-triton support TensorRT 7.2.2? HOT 1
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