ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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AttributeError: 'tuple' object has no attribute 'to' #13213

Open stillbetter opened 3 months ago

stillbetter commented 3 months ago

https://github.com/ultralytics/yolov5/blob/d6112173f5b2b809ec7f3ff1f8048ac0e465092c/models/experimental.py#L99

I got an error like:

  File "export.py", line 1346, in run
    model = attempt_load(weights, device=device, inplace=True, fuse=True)  # load FP32 model
  File "/home/mi/PycharmProjects/yolov5/models/experimental.py", line 99, in attempt_load
    ckpt = (ckpt.get("ema") or ckpt["model"]).to(device).float()  # FP32 model
AttributeError: 'tuple' object has no attribute 'to'

Should I just remove ckpt.get("ema") or ckpt["model"] in the code?

glenn-jocher commented 3 months ago

@stillbetter hi there,

Thank you for reaching out and providing detailed information about the issue you're encountering. The error you're seeing, AttributeError: 'tuple' object has no attribute 'to', suggests that the ckpt variable is being assigned a tuple instead of the expected dictionary.

This issue can sometimes occur if the attempt_load function is not handling the weights file correctly. Here are a few steps you can take to troubleshoot and resolve this:

  1. Verify the Weights File: Ensure that the weights file you are using is correctly formatted and not corrupted. You can try downloading the weights file again from the official YOLOv5 release page.

  2. Update to the Latest Version: Make sure you are using the latest version of YOLOv5. The issue might have been fixed in a more recent update. You can update your local repository with:

    git pull
  3. Check the attempt_load Function: The attempt_load function should return a model object, not a tuple. Ensure that the function is correctly implemented. Here is a snippet of how it should look:

    def attempt_load(weights, map_location=None, inplace=False, fuse=True):
        # Load model
        ckpt = torch.load(weights, map_location=map_location)  # load checkpoint
        model = ckpt['model'].float()  # FP32 model
        if fuse:
            model.fuse()
        return model
  4. Debugging: Add print statements to check the type and content of ckpt before the line causing the error:

    print(type(ckpt))
    print(ckpt)

If the issue persists after these steps, please provide additional details such as the version of YOLOv5 you are using and the exact command you ran. This will help us further diagnose the problem.

Feel free to reach out with any more questions or updates on your progress. The YOLO community and the Ultralytics team are here to help! 😊