Expecting torch and torchvision for JP6.1

lakshanthad · December 20, 2024, 5:44pm

It should be numpy 1.23.5.

We are already handling that here when you do pip install ultralytics[export] on the Jetson:

ultralytics/ultralytics/blob/main/pyproject.toml#L108


      
          export = [
              "onnx>=1.12.0", # ONNX export
              "coremltools>=7.0; platform_system != 'Windows' and python_version <= '3.11'", # CoreML supported on macOS and Linux
              "scikit-learn>=1.3.2; platform_system != 'Windows' and python_version <= '3.11'", # CoreML k-means quantization
              "openvino>=2024.0.0", # OpenVINO export
              "tensorflow>=2.0.0", # TF bug https://github.com/ultralytics/ultralytics/issues/5161
              "tensorflowjs>=3.9.0", # TF.js export, automatically installs tensorflow
              "tensorstore>=0.1.63; platform_machine == 'aarch64' and python_version >= '3.9'", # for TF Raspberry Pi exports
              "keras", # not installed automatically by tensorflow>=2.16
              "flatbuffers>=23.5.26,<100; platform_machine == 'aarch64'", # update old 'flatbuffers' included inside tensorflow package
              "numpy==1.23.5; platform_machine == 'aarch64'", # fix error: `np.bool` was a deprecated alias for the builtin `bool` when using TensorRT models on NVIDIA Jetson
              "h5py!=3.11.0; platform_machine == 'aarch64'", # fix h5py build issues due to missing aarch64 wheels in 3.11 release
          ]
          solutions = [
              "shapely>=2.0.0",    # shapely for point and polygon data matching
              "streamlit",    # for live inference on web browser i.e `yolo streamlit-predict`
          ]
          logging = [
              "comet", # https://docs.ultralytics.com/integrations/comet/
              "tensorboard>=2.13.0",
              "dvclive>=2.12.0",

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Expecting torch and torchvision for JP6.1

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