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cmake_minimum_required(VERSION 3.18)
project(ImageSimilarityTracker LANGUAGES CXX CUDA)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED True)
# --- vcpkg integration ---
# If vcpkg.json is present in the root, and CMAKE_TOOLCHAIN_FILE is set (by build.sh or environment)
# to point to vcpkg.cmake, dependencies listed in vcpkg.json (like opencv4) will be automatically
# found and linked by CMake. We don't need explicit find_package(OpenCV) here anymore if vcpkg handles it.
# Find LibTorch (should be set by build.sh via Torch_DIR or CMAKE_PREFIX_PATH)
find_package(Torch REQUIRED)
# OpenCV should be provided by vcpkg if vcpkg.json lists it and toolchain is used.
# Remove explicit find_package for OpenCV as vcpkg will provide it.
# find_package(OpenCV REQUIRED)
message(STATUS "Found LibTorch: ${TORCH_LIBRARIES}")
# message(STATUS "Found OpenCV: ${OpenCV_LIBS}") # OpenCV_LIBS will be available if vcpkg succeeds
# Always use CUDA implementation (no CPU fallback)
message(STATUS "Building with CUDA support")
# Define source files for the libraries
set(BB_REGRESSOR_SOURCES
cimp/bb_regressor/bb_regressor.cpp
cimp/bb_regressor/prroi_pooling/prroi_pooling_gpu_impl.cu
)
set(CLASSIFIER_SOURCES
cimp/classifier/classifier.cpp
)
set(RESNET_SOURCES
cimp/resnet/resnet.cpp
)
# Create static libraries
add_library(bb_regressor STATIC ${BB_REGRESSOR_SOURCES})
add_library(classifier STATIC ${CLASSIFIER_SOURCES})
add_library(resnet STATIC ${RESNET_SOURCES})
# Set include directories
target_include_directories(bb_regressor PUBLIC
${CMAKE_CURRENT_SOURCE_DIR}/cimp
${CMAKE_CURRENT_SOURCE_DIR}/cimp/bb_regressor/prroi_pooling
${CMAKE_CURRENT_SOURCE_DIR}/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src
)
target_include_directories(classifier PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}/cimp)
target_include_directories(resnet PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}/cimp)
# Link with LibTorch
target_link_libraries(bb_regressor PRIVATE ${TORCH_LIBRARIES})
target_link_libraries(classifier PRIVATE ${TORCH_LIBRARIES})
target_link_libraries(resnet PRIVATE ${TORCH_LIBRARIES})
# Create the demo executable
add_executable(tracking_demo cimp/demo.cpp)
# Link the demo with the libraries
target_link_libraries(tracking_demo PRIVATE bb_regressor classifier resnet ${TORCH_LIBRARIES})
# Create the test models executable
add_executable(test_models test/test_models.cpp)
# Link the test_models with the libraries
target_link_libraries(test_models PRIVATE bb_regressor classifier resnet ${TORCH_LIBRARIES})
# Create the test sample generator executable (without dependencies on our libraries)
# add_executable(generate_test_samples ${CMAKE_CURRENT_SOURCE_DIR}/test/generate_test_samples.cpp) # COMMENTED OUT
# target_link_libraries(generate_test_samples PRIVATE ${TORCH_LIBRARIES}) # COMMENTED OUT
# Copy the executable to the binary directory
install(TARGETS tracking_demo DESTINATION bin)
install(TARGETS test_models DESTINATION bin)
# install(TARGETS generate_test_samples DESTINATION bin) # COMMENTED OUT
# Print some info during the build
message(STATUS "LibTorch found at: ${TORCH_INCLUDE_DIRS}")
message(STATUS "Using CUDA-enabled build")
# --- Installation ---
# Define where to install the executables and libraries
set(CMAKE_INSTALL_PREFIX ${CMAKE_BINARY_DIR}/install) # Install locally within the build directory
install(TARGETS test_models # generate_test_samples # COMMENTED OUT
RUNTIME DESTINATION bin
LIBRARY DESTINATION lib
ARCHIVE DESTINATION lib
)
install(TARGETS resnet classifier bb_regressor
LIBRARY DESTINATION lib
ARCHIVE DESTINATION lib
)
# Install PyTorch and OpenCV shared libraries that our targets link against.
if(TORCH_LIBRARIES)
if(WIN32)
set(LIBTORCH_DLL_DIR "${Torch_DIR}/../lib")
else()
set(LIBTORCH_DLL_DIR "${Torch_DIR}/../lib") # Usually $HOME/libtorch_version/libtorch/lib
endif()
message(STATUS "Attempting to install Torch shared libs from: ${LIBTORCH_DLL_DIR}")
install(DIRECTORY ${LIBTORCH_DLL_DIR}/
DESTINATION lib
USE_SOURCE_PERMISSIONS
OPTIONAL
FILES_MATCHING PATTERN "*.so*" PATTERN "*.dylib*" PATTERN "*.dll"
PATTERN "c10*.dll" PATTERN "torch_cpu*.dll" PATTERN "torch_cuda*.dll" PATTERN "torch.dll"
PATTERN "cudnn*.dll" # Add cuDNN if it's part of LibTorch distribution
)
else()
message(WARNING "TORCH_LIBRARIES not set, cannot install PyTorch shared libraries.")
endif()
# If using vcpkg, it usually handles its own dependencies' deployment or they are statically linked.
# If OpenCV shared libraries need to be deployed and are not handled by vcpkg install component or not part of LibTorch distribution:
# You might need to explicitly find OpenCV shared library paths and install them if vcpkg doesn't put them in a common place with Torch.
# Example (very dependent on how OpenCV is found/provided):
# if(OpenCV_FOUND AND OpenCV_SHARED_LIBS_DIR) # Assume OpenCV_SHARED_LIBS_DIR is set if needed
# install(DIRECTORY ${OpenCV_SHARED_LIBS_DIR}/
# DESTINATION lib
# FILES_MATCHING PATTERN "*.so*" PATTERN "*.dylib*" PATTERN "*.dll"
# USE_SOURCE_PERMISSIONS
# OPTIONAL)
# endif()
# Enable CTest
enable_testing()
# Define a simple test that runs the test_models executable
# The actual test logic (passing arguments, checking output) is in run_tests.sh
add_test(
NAME RunCppModelTests
COMMAND test_models dummy_arg1 dummy_arg2 dummy_arg3 # Dummy args, real ones from run_tests.sh
WORKING_DIRECTORY ${CMAKE_BINARY_DIR}/bin
)