Cannot create Interpolate layer /model.10... Error on Bloblconverter

keggy

Hello Members,

i want to convert a costum OpenVino Model. The .xml and. bin Files converted with Ultralytix.
The OpenVino Model is running (original its a Yolov8n PyTorch model)
But when I start the Converter on: http://blobconverter.luxonis.com

Error:Cannot create Interpolate layer /model.10/Resize id:164 from unsupported opset: opset11

jakaskerl

Hi keggy
Could you try using a different OpenVINO version; maybe a 2021.4? Changing to different opset might also help.

Hope it works.

Thanks,
Jaka

keggy

I was able to convert it to blob by converting PyTorch to Onnx and then to .blob

import torch

from ultralytics import YOLO

# Load your YOLO model

model = YOLO('yolov8n.pt')

# Convert PyTorch model to ONNX

dummy_input = torch.randn(1, 3, 640, 640)

torch.onnx.export(model.model, dummy_input, "yolov8n.onnx", verbose=True, opset_version=10) #Changed the #Opset to 10

keggy

But as I see I need a .json file for the Yolov8 to run on the camera?

Is there any smallest example just to run the .blob file on the camera with color image?

jakaskerl

Hi keggy
Not needed as far as I know. If you already have the blob, there is no need to use the json. Depends on whether you are using SDK or API.
For api:
detectionNetwork.setBlobPath(<blob path>)

For sdk:
nn = oak.create_nn('path_to_blob', color)

According to the definition, both .json and .blob can be passed.

def _parse_model(self, model):
        """
        Called when NNComponent is initialized. Parses "model" argument passed by user.
        """
        if isinstance(model, Dict):
            self._parse_config(model)
            return
        # Parse the input config/model
        elif isinstance(model, str):
            # Download from the web, or convert to Path
            model = getBlob(model) if isUrl(model) else Path(model)

        if model.suffix in ['.blob', '.json']:
            if model.suffix == '.blob':
                self._blob = dai.OpenVINO.Blob(model.resolve())
                self._forced_version = self._blob.version
            elif model.suffix == '.json':  # json config file was passed
                self._parse_config(model)

Thanks,
Jaka

keggy

Hey @jakaskerl thanks for the reply. I think my error is that I don't know the Anchormasks:
Mask is not defined for output layer with width '8400'. Define at pipeline build time using: 'setAnchorMasks' for 'side8400'

But I think I will get them today so I will try out with it.

best regards

David