From ab9ea76ad28c47fee6ff55b9680485ab2271136c Mon Sep 17 00:00:00 2001 From: Erik Smistad Date: Tue, 12 Jan 2021 16:56:46 +0100 Subject: [PATCH 1/2] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 131c15ade..d7af0127e 100644 --- a/README.md +++ b/README.md @@ -20,8 +20,9 @@ Need help? Use the gitter chat: [![Join the chat on Gitter](https://img.shields. ### Main features * **Data streaming** – Processing pipelines in FAST can handle both static and dynamic/temporal data without any change to the code. FAST can stream data from movie files, your webcamera, an Intel RealSense camera, a sequence of images and even directly from ultrasound scanners such as Clarius. -* **Deep learning** – FAST supports several inference engines, such as Google’s TensorFlow, NVIDIA's TensorRT and Intel's OpenVINO, making it possible to create real-time neural network pipelines. +* **Deep learning** – FAST provides a common interface for neural networks supporting different model formats (ONNX, protobuf, SavedModel, OpenVINO, UFF) and backends (Google TensorFlow, NVIDIA TensorRT, Intel OpenVINO), making it possible to create real-time neural network pipelines. * **High-level data management** – Data objects in FAST represent data, such as an image, on all processors. FAST keeps data coherent across the different storage areas thereby removing the burden of explicit memory handling from the developer. +* **Wide data format support** - FAST supports several data formats (DICOM, metaimage (MHD), regular jpg/png/bmp images, videos, HDF5, VTK polydata, whole slide images, ultrasound file format) and data types (images 2D and 3D, grayscale and color, image pyramids, surface mesh, vertices, lines, text ++). * **High performance algorithms** – FAST has several high performance parallel OpenCL implementations of common algorithms, such as marching cubes surface extraction, Gaussian smoothing, non-local means, block matching tracking and seeded region growing. * **Fast concurrent visualization** – Rendering and computation are done in separate threads to ensure smooth responsive visualizations. Several types of visualizations are supported both 3D (mesh, point, line, image slice and volume rendering) and 2D (2D image, image slice and segmentation/label rendering, whole slide image (WSI) pyramids). * **Interoperability** – FAST can be used with Python and can also be easily integrated into existing Qt applications. From 5249fecdabd7a94628ce03a8df934236f8bcc88f Mon Sep 17 00:00:00 2001 From: Erik Smistad Date: Wed, 13 Jan 2021 13:05:44 +0100 Subject: [PATCH 2/2] Fixed OpenVINO build issue on windows needing ngraph.lib for linking --- cmake/ExternalOpenVINO.cmake | 1 + .../Algorithms/NeuralNetwork/InferenceEngines/CMakeLists.txt | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/cmake/ExternalOpenVINO.cmake b/cmake/ExternalOpenVINO.cmake index 50467babf..45ad1f9cc 100644 --- a/cmake/ExternalOpenVINO.cmake +++ b/cmake/ExternalOpenVINO.cmake @@ -50,6 +50,7 @@ ExternalProject_Add(OpenVINO ${CMAKE_COMMAND} -E copy ${FAST_EXTERNAL_BUILD_DIR}/OpenVINO/src/OpenVINO/bin/intel64/Release/MKLDNNPlugin.dll ${FAST_EXTERNAL_INSTALL_DIR}/bin/ COMMAND ${CMAKE_COMMAND} -E copy ${FAST_EXTERNAL_BUILD_DIR}/OpenVINO/src/OpenVINO/bin/intel64/Release/myriadPlugin.dll ${FAST_EXTERNAL_INSTALL_DIR}/bin/ COMMAND ${CMAKE_COMMAND} -E copy ${FAST_EXTERNAL_BUILD_DIR}/OpenVINO/src/OpenVINO/bin/intel64/Release/ngraph.dll ${FAST_EXTERNAL_INSTALL_DIR}/bin/ COMMAND + ${CMAKE_COMMAND} -E copy ${FAST_EXTERNAL_BUILD_DIR}/OpenVINO/src/OpenVINO/bin/intel64/Release/ngraph.lib ${FAST_EXTERNAL_INSTALL_DIR}/lib/ COMMAND ${CMAKE_COMMAND} -E copy ${FAST_EXTERNAL_BUILD_DIR}/OpenVINO/src/OpenVINO/bin/intel64/Release/plugins.xml ${FAST_EXTERNAL_INSTALL_DIR}/bin/ COMMAND ${CMAKE_COMMAND} -E copy ${FAST_EXTERNAL_BUILD_DIR}/OpenVINO/src/OpenVINO/inference-engine/temp/tbb/bin/tbb.dll ${FAST_EXTERNAL_INSTALL_DIR}/bin/ COMMAND ${CMAKE_COMMAND} -E copy_directory ${FAST_EXTERNAL_BUILD_DIR}/OpenVINO/src/OpenVINO/inference-engine/include/ ${FAST_EXTERNAL_INSTALL_DIR}/include/openvino/ COMMAND diff --git a/source/FAST/Algorithms/NeuralNetwork/InferenceEngines/CMakeLists.txt b/source/FAST/Algorithms/NeuralNetwork/InferenceEngines/CMakeLists.txt index 8fc9c3371..d07496d39 100644 --- a/source/FAST/Algorithms/NeuralNetwork/InferenceEngines/CMakeLists.txt +++ b/source/FAST/Algorithms/NeuralNetwork/InferenceEngines/CMakeLists.txt @@ -34,7 +34,7 @@ if(FAST_MODULE_OpenVINO) add_dependencies(InferenceEngineOpenVINO OpenVINO) target_include_directories(InferenceEngineOpenVINO PRIVATE ${FAST_INCLUDE_DIRS} ${FAST_INCLUDE_DIRS}/openvino/) if(WIN32) - target_link_libraries(InferenceEngineOpenVINO FAST inference_engine.lib inference_engine_legacy.lib inference_engine_transformations.lib inference_engine_lp_transformations.lib) + target_link_libraries(InferenceEngineOpenVINO FAST inference_engine.lib inference_engine_legacy.lib inference_engine_transformations.lib inference_engine_lp_transformations.lib ngraph.lib) else() target_link_libraries(InferenceEngineOpenVINO FAST libinference_engine.so libinference_engine_legacy.so libinference_engine_transformations.so libinference_engine_lp_transformations.so) endif()