Skip to content

OpenVX Samples to use with any conformant implementation of OpenVX

License

Notifications You must be signed in to change notification settings

KhronosGroup/openvx-samples

Repository files navigation

MIT licensed

OpenVX Samples

Khronos OpenVX™ is an open, royalty-free standard for cross-platform acceleration of computer vision applications. OpenVX enables performance and power-optimized computer vision processing, especially important in embedded and real-time use cases such as face, body, and gesture tracking, smart video surveillance, advanced driver assistance systems (ADAS), object and scene reconstruction, augmented reality, visual inspection, robotics and more.

In this project, we provide OpenVX sample applications to use with any conformant implementation of OpenVX.

VX Bubble Pop Sample

In this sample we will create an OpenVX graph to run VX Bubble Pop on a live camera. This sample application uses OpenCV to decode input image, draw bubbles/donuts and display the output.

Prerequisites

Steps to run the Bubble Pop sample

Build OpenVX on Linux

* Git Clone project with a recursive flag to get submodules

      git clone --recursive https://github.com/KhronosGroup/OpenVX-sample-impl.git

* Use Build.py script

      cd OpenVX-sample-impl/
      python Build.py --os=Linux --arch=64 --conf=Debug --conf_vision --enh_vision --conf_nn
  • Step - 2: Export OpenVX Directory Path
export OPENVX_DIR=$(pwd)/install/Linux/x64/Debug
  • Step - 3: Clone the OpenVX Samples project and build the bubble pop application
cd ~/ && mkdir OpenVXSample-pop
cd OpenVXSample-pop/
git clone https://github.com/kiritigowda/openvx-samples.git
  • Step - 4: CMake and Build the pop application
mkdir pop-build && cd pop-build
cmake -DOPENVX_INCLUDES=$OPENVX_DIR/include -DOPENVX_LIBRARIES=$OPENVX_DIR/bin/libopenvx.so ../openvx-samples/bubble-pop/
make
  • Step - 5: Run VX Pop application

    • Bubbles
    ./vxPop --bubble
    
    • Donuts
    ./vxPop --donut
    

Canny Edge Detector Sample

In this sample we will create an OpenVX graph to run canny edge detection on an image or a live camera. This sample application uses OpenCV to decode input image and display the output.

Prerequisites

Steps to run the canny sample

Build OpenVX on Linux

* Git Clone project with a recursive flag to get submodules

      git clone --recursive https://github.com/KhronosGroup/OpenVX-sample-impl.git

* Use Build.py script

      cd OpenVX-sample-impl/
      python Build.py --os=Linux --arch=64 --conf=Debug --conf_vision --enh_vision --conf_nn
  • Step - 2: Export OpenVX Directory Path
export OPENVX_DIR=$(pwd)/install/Linux/x64/Debug
  • Step - 3: Clone the OpenVX Samples project and build the canny application
cd ~/ && mkdir OpenVXSample-canny
cd OpenVXSample-canny/
git clone https://github.com/kiritigowda/openvx-samples.git
  • Step - 4: CMake and Build the canny application
mkdir canny-build && cd canny-build
cmake -DOPENVX_INCLUDES=$OPENVX_DIR/include -DOPENVX_LIBRARIES=$OPENVX_DIR/bin/libopenvx.so ../openvx-samples/canny-edge-detector/
make
  • Step - 5: Run Canny application

    • Live
    ./cannyEdgeDetector --live
    
    • Image
    ./cannyEdgeDetector --image ../openvx-samples/images/face.png
    

Skin Tone Detector Sample

In this sample we will create an OpenVX graph to run skintone detection on an image or a live camera. This sample application uses OpenCV to decode input image and display the output.

Prerequisites

Steps to run the skin tone sample

Build OpenVX on Linux

* Git Clone project with a recursive flag to get submodules

      git clone --recursive https://github.com/KhronosGroup/OpenVX-sample-impl.git

* Use Build.py script

      cd OpenVX-sample-impl/
      python Build.py --os=Linux --arch=64 --conf=Debug --conf_vision --enh_vision --conf_nn
  • Step - 2: Export OpenVX Directory Path
export OPENVX_DIR=$(pwd)/install/Linux/x64/Debug
  • Step - 3: Clone the OpenVX Samples project and build the Skin Tone application
cd ~/ && mkdir OpenVXSample-skintone
cd OpenVXSample-skintone/
git clone https://github.com/kiritigowda/openvx-samples.git
  • Step - 4: CMake and Build the Skin Tone application
mkdir skintone-build && cd skintone-build
cmake -DOPENVX_INCLUDES=$OPENVX_DIR/include -DOPENVX_LIBRARIES=$OPENVX_DIR/bin/libopenvx.so ../openvx-samples/skin-tone-detector/
make
  • Step - 5: Run Skin Tone Detector application

    • Live
    ./skinToneDetector --live
    
    • Image
    ./skinToneDetector --image ../openvx-samples/images/face.png
    

Contribution

The samples VX Bubble Pop, VX Canny Edge Detector, & VX Skin Tone Detector are contributed by AMD from their MIVisionX Toolkit. We welcome contributions to this project from all developers. Please open a pull request with details of your sample application to be accepted into this project.