nvImageCodec Samples

Description

These are some sample applications showcasing various nvImageCodec APIs. Sample applications are available in C++ and Python.

Pre-requisites

• Recommended linux distros:
  • Ubuntu >= 20.04 (tested with 20.04 and 22.04)
  • WSL2 with Ubuntu >= 20.04 (tested with 20.04)
• NVIIDA driver:
  • Linux: version 520.56.06 or higher
• NVIDIA CUDA Toolkit >= 11.8
• CMake >= 3.18
• gcc >= 9.4
• Python Packages:
  • jupyter >= 1.0.0
  • matplotlib >= 3.5.2
  • numpy >= 1.23.1
  • cupy >= 11.2.0
  • cucim >= 22.6.0
  • cv-cuda == 0.3.0 Beta
  • opencv-python >= 4.6.0.66
  • torch == 1.13.0
  • torchvision == 0.14.0
  • torchnvjpeg (https://github.com/itsliupeng/torchnvjpeg)

Build C++ samples

mkdir build
cd build
export CUDACXX=nvcc
cmake .. -DCMAKE_BUILD_TYPE=Release
make

Build C++ CVCUDA samples

To build CV-CUDA samples, additionally CV-CUDA has to be installed and CVCUDA_DIR and NVCV_TYPES_DIR need to point folders with *-config.cmake files. Apart of that, BUILD_CVCUDA_SAMPLES variable must be set to ON.

Open Python Jupyter notebooks samples

Change directory to nvimgcodec/samples/python and start the notebook server from the command line:

cd samples/python
jupyter notebook

This will print some information about the notebook server in your terminal, including the URL of the web application (by default, http://localhost:8888):

...
[I 2023-07-28 11:06:53.944 ServerApp] Jupyter Server 2.7.0 is running at:
[I 2023-07-28 11:06:53.944 ServerApp] http://localhost:8888/tree?token=599f185ea12dce78b606ab103ad82510c749ca4c551e0713
[I 2023-07-28 11:06:53.944 ServerApp]     http://127.0.0.1:8888/tree?token=599f185ea12dce78b606ab103ad82510c749ca4c551e0713
[I 2023-07-28 11:06:53.944 ServerApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
...

Open your web browser to this given URL.

When the notebook opens in your browser, you will see the Notebook Dashboard, which will show a list of the notebooks with samples.