# video-codec-sdk **Repository Path**: gcyai/video-codec-sdk ## Basic Information - **Project Name**: video-codec-sdk - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-12-06 - **Last Updated**: 2025-12-06 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Container Images for Video Codec SDK This repo includes the source for building base container images for the [NVIDIA Video Codec SDK](https://developer.nvidia.com/nvidia-video-codec-sdk). ## Versions Supported The build recipes include the following versions: - Video Codec SDK: 11.0.10 - CUDA: 11.2.2 ## Getting Started Build files are provided for the following Linux distributions: - Ubuntu 18.04: [(*ubuntu18.04/Dockerfile*)](https://gitlab.com/nvidia/videosdk/blob/master/ubuntu18.04/Dockerfile) ### Building Images First, clone the repo: ```bash $ git clone https://gitlab.com/nvidia/container-images/video-codec-sdk.git ``` Download the Video Codec SDK (`11.0.10`) archive from the NVIDIA Video Codec SDK [page](https://developer.nvidia.com/nvidia-video-codec-sdk/download) and place it in the image directory. Build the Docker container: ```bash $ docker build --pull \ -t nvcr.io/nvidia/video-codec-sdk:11.0.10 \ --build-arg repository=nvcr.io/nvidia/cuda \ --build-arg flavor=devel \ --file Dockerfile . ``` Once the image is built, you can run the Docker container: ```bash $ docker run --gpus all -it \ nvcr.io/nvidia/video-codec-sdk:11.0.10 \ bash ``` ### Running Samples After launching the container in the previous step, you can build and run the samples from the container. First, install the FFMpeg headers and libraries to allow the samples to build cleanly. ```bash apt-get install -y \ libavutil-dev libavcodec-dev \ libavformat-dev libswresample-dev \ pkg-config ``` Now, we proceed to build the `AppDec` sample and run it with a sample input video file.