blakeblackshear.frigate/docker/tensorrt/detector/build_python_tensorrt.sh
Andrew Reiter a96a951e23
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 05:50:41 -05:00

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#!/bin/bash
set -euxo pipefail
mkdir -p /trt-wheels
if [[ "${TARGETARCH}" == "arm64" ]]; then
# NVIDIA supplies python-tensorrt for python3.8, but frigate uses python3.9,
# so we must build python-tensorrt ourselves.
# Get python-tensorrt source
mkdir /workspace
cd /workspace
git clone -b ${TENSORRT_VER} https://github.com/NVIDIA/TensorRT.git --depth=1
# Collect dependencies
EXT_PATH=/workspace/external && mkdir -p $EXT_PATH
pip3 install pybind11 && ln -s /usr/local/lib/python3.9/dist-packages/pybind11 $EXT_PATH/pybind11
ln -s /usr/include/python3.9 $EXT_PATH/python3.9
ln -s /usr/include/aarch64-linux-gnu/NvOnnxParser.h /workspace/TensorRT/parsers/onnx/
# Build wheel
cd /workspace/TensorRT/python
EXT_PATH=$EXT_PATH PYTHON_MAJOR_VERSION=3 PYTHON_MINOR_VERSION=9 TARGET_ARCHITECTURE=aarch64 /bin/bash ./build.sh
mv build/dist/*.whl /trt-wheels/
fi