Orin AGX run YOLOV5 detect.py,ERROR MSG "RuntimeError: Couldn't load custom C++ ops..."

[JackyChen]

When I clone yolov5 source code in orin agx ubuntu system r35.1, and I install pytorch[Pytorch for Jetson] and torchvision, and then run “pip install -r requirements.txt” to install yolov5 dependencies, “python detect.py” and get an error message like the attach pictures.

[AastaLLL]

Hi,

Based on the document below, you will need to use TorchVision 0.12.0 for PyTorch 1.11.0.
Please downgrade the TorchVision and try it again.

PyTorch

Thanks.

[tnferreira]

I got a another error on AGX Orin r35.1. I’m running inside of the default containers (GitHub - dusty-nv/jetson-containers: Machine Learning Containers for NVIDIA Jetson and JetPack-L4T) r35.1.0-pth1.11-py3. I tried on r35.1.0-pth1.12-py3** but no success.

What’s wrong ? Any tips ?

Fusing layers... 
YOLOv5s summary: 213 layers, 7225885 parameters, 0 gradients
Adding AutoShape... 
Traceback (most recent call last):
  File "test_yolo.py", line 10, in <module>
    results = model(img)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1129, in _call_impl
    return forward_call(*input, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/root/.cache/torch/hub/ultralytics_yolov5_master/models/common.py", line 642, in forward
    y = non_max_suppression(y if self.dmb else y[0],
  File "/root/.cache/torch/hub/ultralytics_yolov5_master/utils/general.py", line 885, in non_max_suppression
    i = torchvision.ops.nms(boxes, scores, iou_thres)  # NMS
  File "/usr/local/lib/python3.8/dist-packages/torchvision-0.13.0a0+da3794e-py3.8-linux-aarch64.egg/torchvision/ops/boxes.py", line 41, in nms
    return torch.ops.torchvision.nms(boxes, scores, iou_threshold)
  File "/usr/local/lib/python3.8/dist-packages/torch/_ops.py", line 142, in __call__
    return self._op(*args, **kwargs or {})
**RuntimeError: CUDA error: no kernel image is available for execution on the device**
**CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.**
**For debugging consider passing CUDA_LAUNCH_BLOCKING=1.**

[dusty_nv]

Hi @tnferreira, please see my reply to your other post here:

CUDA error: no kernel image is available for execution on the device

I got a another error on AGX Orin r35.1. I’m running inside of the default container: l4t-pytorch:r35.1.0-pth1.11-py3. I tried on l4t-pytorch:r35.1.0-pth1.12-py3 too but no success. What’s wrong ? Any tips ? Fusing layers... YOLOv5s summary: 213 layers, 7225885 parameters, 0 gradients Adding AutoShape... Traceback (most recent call last): File "test_yolo.py", line 10, in <module> results = model(img) File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1129,…

[JackyChen]

I deal my probleam with a solution , herer Can I execute yolov5 on the GPU of JETSON AGX XAVIER? - #5 by k-hamada