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fastRT refactor 

fix cmake bug and model.h refacotr
pull/408/head
Xingyu Liao 2021-02-01 10:12:22 +08:00 committed by GitHub
parent 1666c82db4 5f7d3d586e
commit a8ae0fd1e9
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 11 additions and 8 deletions
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4
projects/FastRT/CMakeLists.txt
View File

@ -4,7 +4,7 @@ set(LIBARARY_NAME "FastRT" CACHE STRING "The Fastreid-tensorrt library name")
set(LIBARARY_VERSION_MAJOR "0")
set(LIBARARY_VERSION_MINOR "0")
set(LIBARARY_VERSION_SINOR "1")
set(LIBARARY_VERSION_SINOR "2")
set(LIBARARY_SOVERSION "0")
set(LIBARARY_VERSION "${LIBARARY_VERSION_MAJOR}.${LIBARARY_VERSION_MINOR}.${LIBARARY_VERSION_SINOR}")
project(${LIBARARY_NAME}${LIBARARY_VERSION})
@ -54,4 +54,4 @@ if(BUILD_DEMO)
message(STATUS "BUILD_DEMO: ON")
else()
message(STATUS "BUILD_DEMO: OFF")
endif()
endif()

2
projects/FastRT/demo/CMakeLists.txt
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@ -16,7 +16,7 @@ add_executable(${APP_PROJECT_NAME} inference.cpp)
find_package(OpenCV)
target_include_directories(${APP_PROJECT_NAME}
PUBLIC
OpenCV_INCLUDE_DIRS
${OpenCV_INCLUDE_DIRS}
)
target_link_libraries(${APP_PROJECT_NAME}
PUBLIC

2
projects/FastRT/fastrt/CMakeLists.txt
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@ -24,7 +24,7 @@ PUBLIC
find_package(OpenCV)
target_include_directories(${PROJECT_NAME}
PUBLIC
OpenCV_INCLUDE_DIRS
${OpenCV_INCLUDE_DIRS}
)
target_link_libraries(${PROJECT_NAME}

11
projects/FastRT/include/fastrt/model.h
View File

@ -31,9 +31,9 @@ namespace fastrt {
/* Create builder */
auto builder = make_holder(createInferBuilder(gLogger));
auto config = make_holder(builder->createBuilderConfig());
/* Create model to populate the network, then set the outputs and create an engine */
auto engine = createEngine<B, H>(builder.get(), config.get(), backbone, head);
auto engine = createEngine<B, H>(builder.get(), backbone, head);
TRTASSERT(engine.get());
/* Serialize the engine */
@ -74,15 +74,16 @@ namespace fastrt {
private:
template <typename B, typename H>
TensorRTHolder<ICudaEngine> createEngine(IBuilder* builder, IBuilderConfig* config,
TensorRTHolder<ICudaEngine> createEngine(IBuilder* builder,
std::function<B*(INetworkDefinition*, std::map<std::string, Weights>&, ITensor&, const FastreidConfig&)> backbone,
std::function<H*(INetworkDefinition*, std::map<std::string, Weights>&, ITensor&, const FastreidConfig&)> head) {
auto network = make_holder(builder->createNetworkV2(0U));
auto config = make_holder(builder->createBuilderConfig());
auto data = network->addInput(_engineCfg.input_name.c_str(), _dt, Dims3{3, _engineCfg.input_h, _engineCfg.input_w});
TRTASSERT(data);
std::map<std::string, Weights> weightMap = loadWeights(_engineCfg.weights_path);
auto weightMap = loadWeights(_engineCfg.weights_path);
/* Preprocessing */
auto pre_input = preprocessing_gpu(network.get(), weightMap, data);
@ -90,7 +91,9 @@ namespace fastrt {
/* Modeling */
auto feat_map = backbone(network.get(), weightMap, *pre_input, _reidcfg);
TRTASSERT(feat_map);
auto embedding = head(network.get(), weightMap, *feat_map->getOutput(0), _reidcfg);
TRTASSERT(embedding);
/* Set output */
embedding->getOutput(0)->setName(_engineCfg.output_name.c_str());