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* [cudnn] add port and enable it in darknet
* [OpenCV4] fix ffmpeg feature on uwp
* [darknet] enable integration with cuda/cudnn also with opencv3
* [darknet] update to latest revision
string(REGEX MATCH "V([0-9]+)\\.([0-9]+)\\.([0-9]+)" CUDA_VERSION ${NVCC_OUTPUT})
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message(STATUS"Found CUDA ${CUDA_VERSION}")
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set(CUDA_VERSION_MAJOR ${CMAKE_MATCH_1})
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#set(CUDA_VERSION_MINOR ${CMAKE_MATCH_2})
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#set(CUDA_VERSION_PATCH ${CMAKE_MATCH_3})
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set(CUDA_VERSION_MINOR ${CMAKE_MATCH_2})
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set(CUDA_VERSION_PATCH ${CMAKE_MATCH_3})
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if (CUDA_VERSION_MAJOR LESS9)
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message(FATAL_ERROR "CUDA ${CUDA_VERSION} but ${CUDA_REQUIRED_VERSION} is required. Please download and install a more recent version of CUDA from:"
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if (CUDA_VERSION_MAJOR LESS10 AND CUDA_VERSION_MINOR LESS 1)
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message(FATAL_ERROR "CUDA ${CUDA_VERSION}found, but ${CUDA_REQUIRED_VERSION} is required. Please download and install a more recent version of CUDA from:"
Description: Darknet is an open source neural network framework written in C and CUDA. You only look once (YOLO) is a state-of-the-art, real-time object detection system, best example of darknet functionalities.
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Build-Depends: pthreads (windows), stb
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Default-Features: weights
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Feature: opencv
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Build-Depends: opencv[ffmpeg]
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Description: Build darknet with support for OpenCV
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Feature: cuda
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Build-Depends: cuda
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Description: Build darknet with support for CUDA
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Feature: cudnn
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Build-Depends: darknet[cuda]
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Description: Build darknet with support for CUDNN
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Feature: opencv-base
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Build-Depends: opencv[ffmpeg]
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Description: Build darknet with support for OpenCV
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Feature: opencv-cuda
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Build-Depends: opencv[ffmpeg], opencv[cuda]
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Description: Build darknet with support for a CUDA-enabled OpenCV
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Feature: opencv3-base
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Build-Depends: opencv3[ffmpeg]
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Description: Build darknet with support for OpenCV3
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Feature: opencv3-cuda
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Build-Depends: opencv3[ffmpeg], opencv3[cuda]
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Description: Build darknet with support for a CUDA-enabled OpenCV3
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Feature: weights
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Description: Download pre-built weights for test
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Feature: weights-train
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Description: Download pre-built weights for training
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Feature: opencv-cuda
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Build-Depends: darknet[opencv], darknet[cuda]
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Description: Build darknet with support for a CUDA-enabled OpenCV
# enable OPENCV (with its own CUDA feature enabled) inside DARKNET
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# (note: this does not mean that DARKNET itself will have CUDA support since by design it is independent, to have it you must require both opencv-cuda and cuda features!)
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# DARKNET will be automatically able to distinguish an OpenCV that is built with or without CUDA support.
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if("opencv-cuda"IN_LIST FEATURES)
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set(ENABLE_OPENCV ON)
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endif()
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if("opencv3-cuda"IN_LIST FEATURES)
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set(ENABLE_OPENCV ON)
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endif()
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# enable CUDNN inside DARKNET (which depends on the "cuda" feature by design)
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set(ENABLE_CUDNN OFF)
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if("cudnn"IN_LIST FEATURES)
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set(ENABLE_CUDNN ON)
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endif()
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if ("cuda"IN_LIST FEATURES)
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if (NOT VCPKG_CMAKE_SYSTEM_NAME ANDNOT ENV{CUDACXX})
@@ -67,15 +93,18 @@ endif()
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#make sure we don't use any integrated pre-built library nor any unnecessary CMake module
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