how to inference on torchscript

[nobody-cheng]

how inference torchscript

[zhiqwang]

Hi @nobody-cheng ,

Are you interested in the python side or the cpp side?

If you want to use python, you could check this notebook, and if you are interested in the Cpp backend, you could check the unit-test, and we provided an C++ example of how to infer with the transformed torchscript model, but this example is a little outdated.

BTW the upstream PyTorch have refactored their interfaces of torchscript recently, I've only updated the unit-test to PyTorch 1.8. The example in deployment only works in PyTorch 1.7.x. I will update the example in deployment to PyTorch 1.8 soon.

[nobody-cheng]

Hi @nobody-cheng ,

Are you interested in the python side or the cpp side?

If you want to use python, you could check this notebook, and if you are interested in the Cpp backend, you could check the unit-test, and we provided an C++ example of how to infer with the transformed torchscript model, but this example is a little outdated.

BTW the upstream PyTorch have refactored their interfaces of torchscript recently, I've only updated the unit-test to PyTorch 1.8. The example in deployment only works in PyTorch 1.7.x. I will update the example in deployment to PyTorch 1.8 soon.

# TorchScript export
print(f'Starting TorchScript export with torch {torch.__version__}...')
export_script_name = './checkpoints/yolov5/yolov5s.torchscript.pt'  # >>>>>>> ** Variable is not called **

model_script = torch.jit.script(model)
model_script.eval()
model_script = model_script.to(device)

x = img[None]
out = model(x)
out_script = model_script(x)

export_script_name Variable is not called

[zhiqwang]

Hi @nobody-cheng ,

This is reserved for the target torchscript model to be generated. Fell free to delete this line! If you want to save the generated model, you can do something as following:

model_script.save(export_script_name)

[nobody-cheng]

This is reserved for the target torchscript model to be generated. Fell free to delete this line! If you want to save the generated model, you can do something as following:

model_script.save(export_script_name)

ths
ultralytics/yolov5 code

model.model[-1].export = False  # set

python models/export.py --weights ./runs/train/exp5/weights/best.pt --img 640 --batch 1

it work