NVIDIA/PVA-Solutions

NVIDIA/PVA-Solutions

Description: Optimized computer-vision and signal-processing operators, samples and pipelines for the NVIDIA Programmable Vision Accelerator (PVA)

Language: C

License: Apache-2.0

Stars: 0

Forks: 0

Open issues: 0

Created: 2026-10-02T18:28:06Z

Pushed: 2026-10-21T17:40:27Z

Default branch: main

Fork: no

Archived: no

README: .. SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. SPDX-License-Identifier: Apache-2.0 .. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at .. http://www.apache.org/licenses/LICENSE-2.0 .. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

############## PVA Solutions ##############

PVA Solutions is an open-source collection of computer-vision and signal-processing operators, samples, and pipelines optimized for the NVIDIA Programmable Vision Accelerator (PVA). Refer to the PVA Solutions documentation __ for more information.

Getting Started ===============

Set up your local PVA Solutions project ------------------------------------------

Install the dependencies needed to set up the project:

• git

On Ubuntu >= 22.04, install the following packages using apt:

.. code-block:: shell

sudo apt install -y git

Initialize CV-CUDA explicitly after cloning the repository:

.. code-block:: shell

git submodule update --init

Build PVA Solutions -------------------

Prerequisites +++++++++++++

• NVIDIA PVA SDK version 2.5.4 or later is required, with version 2.10.0 set as the default recommended version. Please follow the PVA SDK documentation __ for installing the SDK and its prerequisites.

If multiple versions of PVA SDK are installed, the `FORCE_PVA_SDK_VERSION CMake flag can be set to select between them, e.g. -DFORCE_PVA_SDK_VERSION=2.5.4`.

• CUDA Toolkit 12.5 (or later) and cross-platform packages
• CMake 3.20 (or later)
• To build the DLInference samples:
• Python >= 3.10.12 and = 22.0.2 are required.
• LLVM 16.0.6 or later and Clang 16.0.6 or later are required.
• Install the Python packages listed in `samples/assets/onnx/requirements.txt`.
• Download the network models listed in `samples/assets/onnx/networks.txt`.

• To build the YOLOv5 pipelines: the same prerequisites as the DLInference

samples, plus TensorRT 10 (10.3 or later) AArch64 cross-development packages. TensorRT 11 is not supported.

• The YOLOv5 pipelines build for DRIVE OS Linux and Jetson Linux (L4T) targets only.
• The PVA+GPU pipeline requires PVA SDK 2.7.0 or later for CUDA-stream submission; when built with an older SDK, it reports an error and exits.
• Set the `TENSORRT_ROOT CMake variable to select a TensorRT installation. By default, /usr` is used when it contains the AArch64 TensorRT headers.
• If TensorRT 10 is not found, the YOLOv5 pipelines are skipped. Set `-DPVA_SOLUTIONS_REQUIRE_TENSORRT=ON` to make a missing TensorRT 10 a configuration error instead.
• The YOLOv5 pipelines need the TensorRT 10 runtime on the target.

For a consistent development environment, we recommend creating a development container (devcontainer). This allows you to install all required dependencies in an isolated environment, helping to avoid version conflicts and platform-specific issues.

Building for DRIVE OS Linux or Jetson Linux (L4T) +++++++++++++++++++++++++++++++++++++++++++++++++

To build PVA Solutions for DRIVE OS Linux or Jetson Linux (L4T), you need to set some environment variables. Refer to the PVA SDK documentation __ for detailed instructions. Below is an example of how to build for Linux platforms:

.. code-block:: shell

mkdir build_l4t && cd build_l4t cmake -DPVA_BUILD_MODE=L4T .. make package -j16

pva_dl_lib static libraries are downloaded automatically at configure time. Set IMPORT_DEVICE_TARGETS=ON` to use pre-compiled device binaries; they are downloaded at configure time.

To build NvSci interop examples, set the `NVSCI_INCLUDE_PATH and NVSCI_LIBRARY_PATH` CMake flags to the paths to the NvSci include and library directories, respectively.

.. code-block:: shell

cmake -DPVA_BUILD_MODE=L4T -DNVSCI_INCLUDE_PATH=/path/to/nvsci/include -DNVSCI_LIBRARY_PATH=/path/to/nvsci/lib ..

Building for DRIVE OS QNX +++++++++++++++++++++++++

The procedure is similar to building for Linux platforms; however some QNX toolchain environment variables are also required. Refer to the PVA SDK documentation __ for detailed instructions. QNX CUDA Toolkit and cross-compile packages are required to build for QNX. Path to the QNX CUDA Toolkit should be set using the `CUDA_TOOLKIT_DIR` CMake flag, similar to the example below.

.. code-block:: shell

mkdir build_qnx && cd build_qnx cmake -DPVA_BUILD_MODE=QNX -DCUDA_TOOLKIT_DIR=/usr/local/cuda-safe-12.5 .. make package -j16

Building for EMU ++++++++++++++++

PVA SDK 2.10 and later include EMU, an x86 emulator that runs NVVPU-compiled VPU programs on the development host. EMU lets you build and test PVA Solutions and samples without deploying to target hardware. Below is an example of how to build for EMU:

.. code-block:: shell

mkdir build_emu && cd build_emu cmake -DPVA_BUILD_MODE=EMU .. make -j16

.. note::

EMU requires PVA SDK 2.10 or later. With older PVA SDK versions, use `-DPVA_BUILD_MODE=NATIVE` instead.

Deploying PVA Solutions -----------------------

On Linux Platforms ++++++++++++++++++

PVA Operator sample applications require pva_operator and nvcv_types dynamic libraries on the target device, in addition to cuPVA runtime libraries. Ensure that cuPVA host runtime libraries (and compatible BSP) are installed on the target device.

PVA Solutions debian packages can be used to conveniently install dynamic libraries, sample application binaries, and asset files.

Copy Debian Packages to Target ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Copy the runtime library and sample Debian packages from the root build directory (build_l4t) to the target system.

.. code-block:: shell

pva-solutions--l4t.deb pva-solutions--l4t-samples.deb pva-solutions--sample-assets.deb

Install Debian Packages on Target ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. code-block:: shell...