pyproject.toml

[project]
name = "tensorrt-practice"
version = "0.1.0"
description = "TensorRT learning workspace with CMake modules and model export helpers."
readme = "models/README.md"
requires-python = ">=3.10"
dependencies = [
	"numpy>=1.24,<2",
	"onnx>=1.14,<2",
	"opencv-python>=4.11.0.86",
	"protobuf>=4.25,<6",
]

[project.optional-dependencies]
# Shared Python utilities for model export scripts.
export = [
	"pillow>=10,<12",
]

# Non-Jetson convenience group. On x86_64/dev machines this can be installed directly.
cpu-dev = [
	"torch>=2.2,<2.6; platform_machine != 'aarch64'",
	"torchvision>=0.17,<0.21; platform_machine != 'aarch64'",
]

# Jetson note:
# Do NOT install torch/torchvision from PyPI on aarch64 blindly.
# Install JetPack-matched NVIDIA wheels first, then install this project extras.
jetson = [
	"jetson-stats>=4.2; platform_machine == 'aarch64' and sys_platform == 'linux'",
]

[tool.tensorrt_practice]
jetson_torch_install = "Install JetPack-matched NVIDIA torch/torchvision wheels first, then install this project with: pip install -e .[export,jetson]"
jetson_torch_install_uv = "Install JetPack-matched NVIDIA torch/torchvision wheels first, then run: uv sync --extra export --extra jetson"

[tool.uv]
# This repository uses uv for environment/dependency management only.
# Do not build/install this repository itself as a package.
package = false