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I have followed the YOLOv5-Custom-Training tutorial and trained a model to detect some custom objects.
The object works properly detecting objects.
I then exported the model to onnx using the following command: python export.py --include onnx --weight ./runs/train/exp/weights/best.pt --data {dataset.location}/data.yaml --img 640
The exported onnx model also properly detects objects.
I adjusted the model name and the image size in utils/predict.ts, and I'm getting the following error:
Uncaught (in promise) Error: resize (packed) does not support mode: 'nearest'
at l (ort-web.min.js?f1d4:formatted:18144:282536)
at Object.get (ort-web.min.js?f1d4:formatted:18144:281666)
at t.WebGLInferenceHandler.executeProgram (ort-web.min.js?f1d4:formatted:18144:209391)
at t.WebGLInferenceHandler.run (ort-web.min.js?f1d4:formatted:18144:209690)
at Object.t.resize [as impl] (ort-web.min.js?f1d4:formatted:18144:281598)
at eval (ort-web.min.js?f1d4:formatted:18144:350066)
at t.Profiler.event (ort-web.min.js?f1d4:formatted:18144:365260)
at eval (ort-web.min.js?f1d4:formatted:18144:350026)
Any thing to do to work around this?
The text was updated successfully, but these errors were encountered:
I have followed the
YOLOv5-Custom-Training
tutorial and trained a model to detect some custom objects.The object works properly detecting objects.
I then exported the model to
onnx
using the following command:python export.py --include onnx --weight ./runs/train/exp/weights/best.pt --data {dataset.location}/data.yaml --img 640
The exported
onnx
model also properly detects objects.I then took the
onnxruntime-nextjs-template
and I am trying to adjust it to run my YOLO model.I adjusted the model name and the image size in
utils/predict.ts
, and I'm getting the following error:Any thing to do to work around this?
The text was updated successfully, but these errors were encountered: