blakeblackshear.frigate/docker/tensorrt/requirements-arm64.txt

cuda-python == 11.7; platform_machine == 'aarch64'
onnxruntime @ https://nvidia.box.com/shared/static/9aemm4grzbbkfaesg5l7fplgjtmswhj8.whl; platform_machine == 'aarch64'
Nvidia Jetson ffmpeg + TensorRT support (#6458) * Non-Jetson changes Required for later commits: - Allow base image to be overridden (and don't assume its WORKDIR) - Ensure python3.9 - Map hwaccel decode presets as strings instead of lists Not required: - Fix existing documentation - Simplify hwaccel scale logic * Prepare for multi-arch tensorrt build * Add tensorrt images for Jetson boards * Add Jetson ffmpeg hwaccel * Update docs * Add CODEOWNERS * CI * Change default model from yolov7-tiny-416 to yolov7-320 In my experience the tiny models perform markedly worse without being much faster * fixup! Update docs 2023-07-26 12:50:41 +02:00			`cuda-python == 11.7; platform_machine == 'aarch64'`
Jetson onnxruntime (#14688) * Add support for using onnx runtime with jetson * Update docs * Clarify 2024-10-30 15:22:28 +01:00			`onnxruntime @ https://nvidia.box.com/shared/static/9aemm4grzbbkfaesg5l7fplgjtmswhj8.whl; platform_machine == 'aarch64'`