Is it possible to use yolov11 or v8 on k730 board?
Hello, I am trying to convert the yolov11 model to nef, following the instructions on the document center.
the optimized onnx model of yolov11 works fine on ktc.kneron_inference
the problem is, when i quantize & compile the model to nef,
the resulting nef model does not work properly (it outputs 0 probablilities for all classes or has no detection at all)
but so far no errors
Im wondering if there is a way to compile the v11 model safely
or it is unsupported for now?
Comments
Hello,
Regarding the YOLOv11 and YOLOv8 models, if you can modify them to a structure consisting only of supported operators, they will be able to run on KL730. Please refer to the table to check the supported list
https://doc.kneron.com/docs/#toolchain/appendix/operators/
About the model accuracy of the ONNX and NEF models, please run inference on these two types of models using ktc.kneron_inference() under the exact same conditions (e.g., input image, preprocess function, postprocess function). Any difference in the inference flow would cause a different output result.
To ensure the model's accuracy, it is recommended not to run model inference on the board before all the verification on the toolchain simulator ktc.kneron_inference() is complete.
Thanks for the reply,
this is the output list of model operators after running optimize.py
after comparing with the resource you provided
I see all the operators except 'Constant' are on the list and supported on 730, have I got it right?
or are operators like Softmax still not supported on 730?
if there is a need for model modification, may I ask how can I modify it? does kneron support apis for modification
or should it be done using other resources?
Hello,
The operator "Softmax" is supported on KL730, and you can check the compatibility of other operators using our support table: https://doc.kneron.com/docs/#toolchain/appendix/operators/
You can modify your ONNX model using many open tools, like:
https://onnx.ai/onnx/api/index.html or https://github.com/ZhangGe6/onnx-modifier
These are both tools for ONNX models. You can find many details for them on the internet, or you can find other tools yourself. But to edit the model, it requires some knowledge of the model.
If all the operators are supported, there is no need to modify the model. If you still encounter any issue, please feel free to let us know.