GStreamer-DeckLink

This document is a comprehensive setup guide for integrating GStreamer and the DeckLink SDK with the Blackmagic DeckLink Duo card. It outlines the system requirements, installation steps, and initial configuration instructions for both C/C++ and Python development. It also includes a guide to build OpenCV from source with GPU support (CUDA and cuDNN) with GStreamer for Computer Vision tasks.

For a more detailed overview and summary of this GitHub repository, please follow this link: DeepWiki Index.

• Developing with Blackmagic Design
• GStreamer Application Development Manual

Table of Contents

1. Prerequisites
2. Installation
3. OpenCV from source with GPU and GStreamer
4. Building C++ Applications with Blackmagic Design DeckLink SDK
5. Building C Applications with GStreamer
6. Troubleshooting

Prerequisites

Component	Requirement	Verification Command
Operating System	Ubuntu 22.04.5 LTS	lsb_release -a
Hardware	DeckLink Duo card	BlackmagicFirmwareUpdater status
Hardware	NVIDIA GeForce RTX 5090	nvidia-smi
Build Tools	GCC, CMake, pkg-config	gcc --version && cmake --version
Python	Python 3.10 with gi bindings	python3 -c "import gi"
OpenCV	4.10.0 version	python -c "import cv2; print(cv2.__version__);"

Core Installation Steps

1. System Dependencies and Packages

   • Update package information and install the required packages:

   sudo apt update && upgrade
   sudo apt-get install build-essential pkg-config cmake make unzip yasm dkms git checkinstall libsdl2-dev libgtk2.0-dev libavcodec-dev libavformat-dev libswscale-dev    

   • Image I/O, Video and Audio, and OpenCore for speed codec:

   # Image I/O:
   sudo apt-get install libjpeg-dev libpng-dev libtiff-dev
   
   # Video and Audio:
   sudo apt install libavformat-dev libswscale-dev libavresample-dev
   sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
   sudo apt install libxvidcore-dev x264 libx264-dev libfaac-dev libmp3lame-dev libtheora-dev
   sudo apt install libfaac-dev libmp3lame-dev libvorbis-dev
   
   # OpenCore for Speed Codec:
   sudo apt install libopencore-amrnb-dev libopencore-amrwb-dev

   • GTK for OpenCV Highgui:

   sudo apt-get install libgtk-3-dev

   • Parallelism C++ for CPU:

   sudo apt-get install libtbb2 libtbb-dev 

   • OpenCV Optimization:

   sudo apt-get install libatlas-base-dev gfortran
   sudo apt-get install libprotobuf-dev protobuf-compiler
   sudo apt-get install libgoogle-glog-dev libgflags-dev
   sudo apt-get install libgphoto2-dev libeigen3-dev libhdf5-dev doxygen

2. NVIDIA Drivers

   • Get all the NVIDIA Linux Graphics Driver for Linux-x86_64:

   cd ~/Downloads/
   wget https://download.nvidia.com/XFree86/Linux-x86_64/570.133.07/NVIDIA-Linux-x86_64-570.133.07.run
   chmod +x NVIDIA-Linux-x86_64-570.133.07.run
   sudo ./NVIDIA-Linux-x86_64-570.133.07.run
   sudo reboot

   • Verify NVIDIA Drivers:

   nvidia-smi
   dpkg -l | grep nvidia-driver

3. DeckLink Drivers Installation

   • Download the latest Desktop Video software for Linux from the official Blackmagic Design website: Desktop Video Downloads

   tar -xf Blackmagic_Desktop_Video_Linux_*.tar
   cd Blackmagic_Desktop_Video_Linux_*/deb/x86_64/
   sudo dpkg -i desktopvideo_*.deb
   sudo apt-get install -f

   • Verify DeckLink Hardware/Firmware status and update if necessary:

   lspci | grep Blackmagic
   
   BlackmagicFirmwareUpdater status
   BlackmagicFirmwareUpdater update 0
   
   # Check that libDeckLinkAPI.so is correctly installed
   ls -l /usr/lib | grep libDeckLink
   
   sudo reboot

4. DeckLink SDK Configuration

   • Download and unzip the Desktop Video SDK from the official developer page.

   unzip Blackmagic_DeckLink_SDK_*.zip

   • Update the DECKLINK_SDK_PATH variable in CMakeLists.txt to point to your SDK extraction directory.

5. GStreamer Framework Installation

   • Install GStreamer development packages and plugins:

   sudo apt-get install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libgstreamer-plugins-bad1.0-dev gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa gstreamer1.0-gl gstreamer1.0-gtk3 gstreamer1.0-qt5 gstreamer1.0-pulseaudio

   • Verify that GStreamer is installed correctly

   gst-inspect-1.0 --version
   gst-device-monitor-1.0 Video/Source

6. Python Environment Setup

   • Install the gi bindings for Python applications:

   sudo apt-get install python3-gi gir1.2-gstreamer-1.0 python3-dev python3-numpy python3-pip python3-testresources

   • UV Installation with Python 3.10 version and GStreamer:

   curl -LsSf https://astral.sh/uv/install.sh | sh
   
   uv init
   uv add flask requests
   uv python install 3.10
   uv python pin 3.10 # Updated `.python-version` from `3.13` -> `3.10`
   
   uv run --python 3.10 python -c "import sys; print(sys.version)"
   
   sudo apt install python3-gi python3-gi-cairo gir1.2-glib-2.0 gir1.2-gobject-2.0 gir1.2-gtk-4.0 libgirepository1.0-dev gcc libcairo2-dev pkg-config python3-dev
   
   uv pip install pycairo
   uv pip install PyGObject==3.50.0
   
   python -c "import gi; gi.require_version('GLib', '2.0'); gi.require_version('GObject', '2.0'); print('Success')"

   • Installation for Conda Environments:

   conda install -c conda-forge gcc=12 gxx_linux-64=12 
   conda install -c conda-forge gstreamer gst-plugins-base gst-plugins-good gst-plugins-bad gst-plugins-ugly gst-libav gst-python pygobject

OpenCV from source with GPU and GStreamer

1. Pre-installation Actions:
   • Follow the CUDA Installation Guide for Linux and Uninstall the built OpenCV if there is a built installation of OpenCV already.
   • Check CUDA GPU Compute Capability.
   • Watch this YouTube Tutorial.

   source .venv/bin/activate
   
   sudo apt update
   
   sudo apt install -y build-essential cmake git pkg-config libjpeg-dev libtiff-dev libpng-dev libavcodec-dev libavformat-dev libswscale-dev libv4l-dev libxvidcore-dev libx264-dev libgtk-3-dev libatlas-base-dev gfortran python3-dev python3-numpy libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa gstreamer1.0-gl gstreamer1.0-gtk3 gstreamer1.0-qt5 gstreamer1.0-pulseaudio

2. Download the NVIDIA CUDA Toolkit

   wget https://developer.download.nvidia.com/compute/cuda/12.9.1/local_installers/cuda-repo-ubuntu2204-12-9-local_12.9.1-575.57.08-1_amd64.deb 
   sudo dpkg -i cuda-repo-ubuntu2204-12-9-local_12.9.1-575.57.08-1_amd64.deb
   sudo cp /var/cuda-repo-ubuntu2204-12-9-local/cuda-*-keyring.gpg /usr/share/keyrings/
   sudo apt-get update
   sudo apt-get -y install cuda-toolkit-12-9
   sudo reboot

3. Download cuDNN 9.11.0, Check other cuDNN versions.

   nvcc --version
   wget https://developer.download.nvidia.com/compute/cudnn/9.11.0/local_installers/cudnn-local-repo-ubuntu2204-9.11.0_1.0-1_amd64.deb 
   sudo dpkg -i cudnn-local-repo-ubuntu2204-9.11.0_1.0-1_amd64.deb
   sudo cp /var/cudnn-local-repo-ubuntu2204-9.11.0/cudnn-*-keyring.gpg /usr/share/keyrings/
   sudo apt-get update
   sudo apt-get -y install cudnn
   sudo reboot

4. Purge Conflicting OpenCV Installations:

   uv pip uninstall opencv-python opencv-contrib-python
   sudo apt purge -y *libopencv*

5. Clone OpenCV and OpenCV Contrib Repositories

   # Remove existing clones
   rm -rf ~/opencv ~/opencv_contrib
   
   cd ~
   git clone https://github.com/opencv/opencv.git && cd opencv && git checkout 4.10.0
   cd ~
   git clone https://github.com/opencv/opencv_contrib.git && cd opencv_contrib && git checkout 4.10.0
   
   cd ~/opencv && rm -rf build && mkdir build && cd build

6. Build the project with CMake

   cmake -D CMAKE_BUILD_TYPE=RELEASE \
     -D CMAKE_INSTALL_PREFIX=/usr/local \
     -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \
     -D BUILD_opencv_python3=ON \
     -D PYTHON3_EXECUTABLE=$(which python) \
     -D PYTHON3_INCLUDE_DIR=$(python -c "import sysconfig; print(sysconfig.get_path('include'))") \
     -D PYTHON3_LIBRARY=$(python -c "import sysconfig; print(sysconfig.get_config_var('LIBDIR') + '/' + sysconfig.get_config_var('LDLIBRARY'))") \
     -D PYTHON3_PACKAGES_PATH=$(python -c "import sysconfig; print(sysconfig.get_path('platlib'))") \
     -D WITH_GSTREAMER=ON \
     -D WITH_GSTREAMER_0_10=OFF \
     -D WITH_FFMPEG=ON \
     -D WITH_CUDA=ON \
     -D WITH_CUDNN=ON \
     -D OPENCV_DNN_CUDA=ON \
     -D CUDA_ARCH_BIN=10.0 \
     -D ENABLE_FAST_MATH=ON \
     -D CUDA_FAST_MATH=ON \
     -D WITH_CUFFT=ON \
     -D WITH_CUBLAS=ON \
     -D WITH_V4L=ON \
     -D WITH_OPENCL=ON \
     -D WITH_OPENGL=ON \
     -D BUILD_EXAMPLES=OFF ..

7. Compile, Install, and Verify:

   make -j$(nproc)
   sudo make install && sudo ldconfig
   export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
   
   # Test in UV env
   python -c "import cv2; print(cv2.__version__); print(cv2.getBuildInformation())"
   
   # OpenCV Test with GStreamer
   python -c "import cv2; cap = cv2.VideoCapture('videotestsrc ! video/x-raw, width=640, height=480 ! videoconvert ! appsink', cv2.CAP_GSTREAMER); print('Success' if cap.isOpened() else 'Failure')"

Building C++ Applications with Blackmagic Design DeckLink SDK

Project Structure

• src/: Contains source code files.
• bin/: Houses the compiled executable.
• build/: Temporary build directory (generated during compilation).
• CMakeLists.txt: Defines the build process.

Building the Project

• Path to DeckLink_SDK

  cd /GST-DeckLink/DeckLink_SDK
  mkdir build
  cd build
  cmake .. -DCMAKE_BUILD_TYPE=Debug
  make

• Execute the binary:

  cd ../bin/Linux64/Debug
  ./DeckLink-SDK

• Terminate with Ctrl+C to trigger cleanup, displaying the end time and performance metrics

Building C Applications with GStreamer

• Clone the GStreamer Repository, build and compile the first script tutorial:

  git clone https://gitlab.freedesktop.org/gstreamer/gstreamer
  
  # Change directory to find basic-tutorials-1:
  cd gstreamer/subprojects/gst-docs/examples/tutorials/
  
  # Compile it:
  gcc basic-tutorial-1.c -o basic-tutorial-1 `pkg-config --cflags --libs gstreamer-1.0`
  
  # Execute the binary:
  ./basic-tutorial-1

• Check GST_CMake for the implementation with the BlackMagic DeckLink Duo card.

Troubleshooting

• Device Not Detected: Confirm the card appears in lspci and add your user to the video group if access is denied: sudo usermod -aG video $USER.

• API Failures: Consult HRESULT error codes in the DeckLink SDK Manual for debugging.

• Compilation Issues: Ensure the SDK path is correct and headers like DeckLinkAPI.h are found.

• Runtime Permissions: Elevated privileges may be needed for hardware interaction in some setups.

• Blackmagic Desktop Video Drivers Installation Problems: If you encounter a dependency issue where the Blackmagic Desktop Video drivers need the dkms (Dynamic Kernel Module Support) package, ensure you install the missing dkms package along with its dependencies before proceeding with the installation of the Blackmagic Desktop Video drivers.

  # Step 1: Install DKMS and Dependencies
  sudo apt update
  sudo apt install dkms
  
  # Step 2: Install Build Dependencies (if needed)
  sudo apt install build-essential linux-headers-$(uname -r)
  
  # Step 3: Install the Blackmagic Desktop Video Drivers
  sudo dpkg -i desktopvideo_*.deb
  
  # Step 4: Fix Any Remaining Dependencies
  sudo apt --fix-broken install
  sudo reboot  

External Installations and Configurations

• OpenCV Python with Gstreamer Backend
• Guide to build OpenCV from source with GPU support (CUDA and cuDNN)
• Compiling and installing ffmpeg with Decklink support
• FFmpeg for DekTec
• Compile FFmpeg for Ubuntu
• NVIDIA DeepStream SDK