Comments (1)
use the provided convertPytorchToONNX.py
script for the conversion as I adopted the same output format as the other YOLO versions, You can refer to the following log :
[INFO ] Name [0]: outputs
[INFO ] Shape [0]: (1, 8400, 85, )
[INFO ] Class num: 80
from yolo-nas-onnxruntime.
Related Issues (9)
- Is compatible with latest onnxruntime (1.15.0) ? HOT 3
- Can this run in Jetson Nano ? if yes please help me tutorial setting env HOT 3
- doesnt work on custom dataset HOT 9
- Help me with implementing this project. HOT 8
- About model chooses HOT 1
- No instance of overloaded function "std::vector<_Ty, _Alloc>::push_back [with _Ty=Ort::Float16_t, _Alloc=std::allocator<Ort::Float16_t>]" matches the argument list HOT 2
- C# version HOT 6
- How to run inference with ONNX uint8 model?
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from yolo-nas-onnxruntime.