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ultralytics 8.3.72 Fix NVIDIA Jetson DLA core support for DLA inference (#19078)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Lakshantha Dissanayake <lakshanthad@yahoo.com>
Co-authored-by: Lakshantha Dissanayake <lakshantha@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Laughing 2025-02-06 11:10:36 +08:00 • committed by GitHub
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5 changed files with 15 additions and 12 deletions
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docs/en/guides/nvidia-jetson.md
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@ -289,10 +289,13 @@ The YOLO11n model in PyTorch format is converted to TensorRT to run inference wi
The following Jetson devices are equipped with DLA hardware:
- Jetson Orin NX 16GB
- Jetson AGX Orin Series
- Jetson AGX Xavier Series
- Jetson Xavier NX Series
| Jetson Device | DLA Cores | DLA Max Frequency |
| ------------------------ | --------- | ----------------- |
| Jetson AGX Orin Series | 2 | 1.6 GHz |
| Jetson Orin NX 16GB | 2 | 614 MHz |
| Jetson Orin NX 8GB | 1 | 614 MHz |
| Jetson AGX Xavier Series | 2 | 1.4 GHz |
| Jetson Xavier NX Series | 2 | 1.1 GHz |
!!! example
@ -318,6 +321,7 @@ The following Jetson devices are equipped with DLA hardware:
```bash
# Export a YOLO11n PyTorch model to TensorRT format with DLA enabled (only works with FP16 or INT8)
# Once DLA core number is specified at export, it will use the same core at inference
yolo export model=yolo11n.pt format=engine device="dla:0" half=True # dla:0 or dla:1 corresponds to the DLA cores
# Run inference with the exported model on the DLA