mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-12 03:50:39 +08:00
[Other] Remove some build options (#1090)
* remove some flags * add gpu check in cmake
This commit is contained in:
Jason
@@ -184,8 +184,10 @@ add_definitions(-DFASTDEPLOY_LIB)
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configure_file(${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/core/config.h.in ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/core/config.h)
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configure_file(${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/pybind/main.cc.in ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/pybind/main.cc)
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file(GLOB_RECURSE ALL_DEPLOY_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/*.cc)
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file(GLOB_RECURSE FDTENSOR_FUNC_CUDA_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/function/*.cu)
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file(GLOB_RECURSE DEPLOY_OP_CUDA_KERNEL_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/runtime/backends/op_cuda_kernels/*.cu)
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if(WITH_GPU)
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file(GLOB_RECURSE DEPLOY_CUDA_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/*.cu)
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list(APPEND ALL_DEPLOY_SRCS ${DEPLOY_CUDA_SRCS})
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endif()
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file(GLOB_RECURSE DEPLOY_ORT_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/runtime/backends/ort/*.cc)
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file(GLOB_RECURSE DEPLOY_PADDLE_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/runtime/backends/paddle/*.cc)
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file(GLOB_RECURSE DEPLOY_POROS_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/runtime/backends/poros/*.cc)
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@@ -197,7 +199,6 @@ file(GLOB_RECURSE DEPLOY_LITE_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastd
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file(GLOB_RECURSE DEPLOY_VISION_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/vision/*.cc)
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file(GLOB_RECURSE DEPLOY_ENCRYPTION_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/encryption/*.cc)
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file(GLOB_RECURSE DEPLOY_PIPELINE_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/pipeline/*.cc)
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file(GLOB_RECURSE DEPLOY_VISION_CUDA_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/vision/*.cu)
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file(GLOB_RECURSE DEPLOY_TEXT_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/text/*.cc)
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file(GLOB_RECURSE DEPLOY_PYBIND_SRCS ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/pybind/*.cc ${PROJECT_SOURCE_DIR}/${CSRCS_DIR_NAME}/fastdeploy/*_pybind.cc)
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list(REMOVE_ITEM ALL_DEPLOY_SRCS ${DEPLOY_ORT_SRCS} ${DEPLOY_PADDLE_SRCS} ${DEPLOY_POROS_SRCS} ${DEPLOY_TRT_SRCS} ${DEPLOY_OPENVINO_SRCS} ${DEPLOY_LITE_SRCS} ${DEPLOY_VISION_SRCS} ${DEPLOY_TEXT_SRCS} ${DEPLOY_PIPELINE_SRCS} ${DEPLOY_RKNPU2_SRCS} ${DEPLOY_SOPHGO_SRCS} ${DEPLOY_ENCRYPTION_SRCS})
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@@ -213,7 +214,8 @@ include_directories(${PROJECT_SOURCE_DIR}/third_party/eigen)
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if(WIN32)
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add_definitions(-DEIGEN_STRONG_INLINE=inline)
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endif()
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# sw not support thread_local semantic
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# sw(sunway) not support thread_local semantic
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if(WITH_SW)
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add_definitions(-DEIGEN_AVOID_THREAD_LOCAL)
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endif()
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@@ -224,9 +226,6 @@ if(ENABLE_ORT_BACKEND)
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list(APPEND ALL_DEPLOY_SRCS ${DEPLOY_ORT_SRCS})
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include(${PROJECT_SOURCE_DIR}/cmake/onnxruntime.cmake)
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list(APPEND DEPEND_LIBS external_onnxruntime)
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if(WITH_GPU)
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list(APPEND ALL_DEPLOY_SRCS ${DEPLOY_OP_CUDA_KERNEL_SRCS})
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endif()
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endif()
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if(ENABLE_LITE_BACKEND)
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@@ -329,20 +328,13 @@ if(WITH_GPU)
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find_library(CUDA_LIB cudart ${CUDA_DIRECTORY}/lib64)
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endif()
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list(APPEND DEPEND_LIBS ${CUDA_LIB})
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endif()
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endif()
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# Whether to build CUDA source files in fastdeploy
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# CUDA source files include CUDA preprocessing, TRT plugins, etc.
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if(WITH_GPU)
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set(BUILD_CUDA_SRC ON)
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enable_language(CUDA)
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message(STATUS "CUDA compiler: ${CMAKE_CUDA_COMPILER}, version: "
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"${CMAKE_CUDA_COMPILER_ID} ${CMAKE_CUDA_COMPILER_VERSION}")
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include(${PROJECT_SOURCE_DIR}/cmake/cuda.cmake)
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list(APPEND ALL_DEPLOY_SRCS ${FDTENSOR_FUNC_CUDA_SRCS})
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else()
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set(BUILD_CUDA_SRC OFF)
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# build CUDA source files in fastdeploy, CUDA source files include CUDA preprocessing, TRT plugins, etc.
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enable_language(CUDA)
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message(STATUS "CUDA compiler: ${CMAKE_CUDA_COMPILER}, version: "
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"${CMAKE_CUDA_COMPILER_ID} ${CMAKE_CUDA_COMPILER_VERSION}")
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include(${PROJECT_SOURCE_DIR}/cmake/cuda.cmake)
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endif()
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endif()
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if(WITH_IPU)
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@@ -383,7 +375,6 @@ if(ENABLE_TRT_BACKEND)
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find_library(TRT_ONNX_LIB nvonnxparser ${TRT_LIB_DIR} NO_DEFAULT_PATH)
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find_library(TRT_PLUGIN_LIB nvinfer_plugin ${TRT_LIB_DIR} NO_DEFAULT_PATH)
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list(APPEND DEPEND_LIBS ${TRT_INFER_LIB} ${TRT_ONNX_LIB} ${TRT_PLUGIN_LIB})
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list(APPEND ALL_DEPLOY_SRCS ${DEPLOY_OP_CUDA_KERNEL_SRCS})
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if(NOT BUILD_ON_JETSON AND TRT_DIRECTORY)
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if(NOT EXISTS "${CMAKE_CURRENT_BINARY_DIR}/third_libs/install/tensorrt")
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@@ -418,10 +409,6 @@ if(ENABLE_VISION)
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add_definitions(-DENABLE_VISION_VISUALIZE)
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add_subdirectory(${PROJECT_SOURCE_DIR}/third_party/yaml-cpp)
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list(APPEND DEPEND_LIBS yaml-cpp)
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if(BUILD_CUDA_SRC)
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add_definitions(-DENABLE_CUDA_PREPROCESS)
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list(APPEND DEPLOY_VISION_SRCS ${DEPLOY_VISION_CUDA_SRCS})
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endif()
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list(APPEND ALL_DEPLOY_SRCS ${DEPLOY_VISION_SRCS})
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list(APPEND ALL_DEPLOY_SRCS ${DEPLOY_PIPELINE_SRCS})
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include_directories(${PROJECT_SOURCE_DIR}/third_party/yaml-cpp/include)
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@@ -483,7 +470,7 @@ elseif(ANDROID)
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set_target_properties(${LIBRARY_NAME} PROPERTIES LINK_FLAGS_MINSIZEREL ${COMMON_LINK_FLAGS_REL})
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elseif(MSVC)
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else()
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if(BUILD_CUDA_SRC)
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if(WITH_GPU)
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set_target_properties(${LIBRARY_NAME} PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
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set_target_properties(${LIBRARY_NAME} PROPERTIES INTERFACE_COMPILE_OPTIONS
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"$<$<BUILD_INTERFACE:$<COMPILE_LANGUAGE:CXX>>:-fvisibility=hidden>$<$<BUILD_INTERFACE:$<COMPILE_LANGUAGE:CUDA>>:-Xcompiler=-fvisibility=hidden>")
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@@ -29,7 +29,6 @@ function(fastdeploy_summary)
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message(STATUS " CMAKE_MODULE_PATH : ${CMAKE_MODULE_PATH}")
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message(STATUS "")
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message(STATUS " FastDeploy version : ${FASTDEPLOY_VERSION}")
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message(STATUS " Paddle2ONNX version : ${PADDLE2ONNX_VERSION}")
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message(STATUS " ENABLE_ORT_BACKEND : ${ENABLE_ORT_BACKEND}")
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message(STATUS " ENABLE_RKNPU2_BACKEND : ${ENABLE_RKNPU2_BACKEND}")
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message(STATUS " ENABLE_SOPHGO_BACKEND : ${ENABLE_SOPHGO_BACKEND}")
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@@ -38,6 +37,7 @@ function(fastdeploy_summary)
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message(STATUS " ENABLE_POROS_BACKEND : ${ENABLE_POROS_BACKEND}")
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message(STATUS " ENABLE_TRT_BACKEND : ${ENABLE_TRT_BACKEND}")
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message(STATUS " ENABLE_OPENVINO_BACKEND : ${ENABLE_OPENVINO_BACKEND}")
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message(STATUS " WITH_GPU : ${WITH_GPU}")
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message(STATUS " WITH_ASCEND : ${WITH_ASCEND}")
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message(STATUS " WITH_TIMVX : ${WITH_TIMVX}")
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message(STATUS " WITH_KUNLUNXIN : ${WITH_KUNLUNXIN}")
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@@ -54,16 +54,12 @@ function(fastdeploy_summary)
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message(STATUS " OpenVINO version : ${OPENVINO_VERSION}")
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endif()
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if(WITH_GPU)
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message(STATUS " WITH_GPU : ${WITH_GPU}")
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message(STATUS " CUDA_DIRECTORY : ${CUDA_DIRECTORY}")
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message(STATUS " TRT_DRECTORY : ${TRT_DIRECTORY}")
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message(STATUS " BUILD_CUDA_SRC : ${BUILD_CUDA_SRC}")
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endif()
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message(STATUS " ENABLE_VISION : ${ENABLE_VISION}")
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message(STATUS " ENABLE_TEXT : ${ENABLE_TEXT}")
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message(STATUS " ENABLE_ENCRYPTION : ${ENABLE_ENCRYPTION}")
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message(STATUS " ENABLE_DEBUG : ${ENABLE_DEBUG}")
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message(STATUS " ENABLE_VISION_VISUALIZE : ${ENABLE_VISION_VISUALIZE}")
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if(ANDROID)
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message(STATUS " ANDROID_ABI : ${ANDROID_ABI}")
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message(STATUS " ANDROID_PLATFORM : ${ANDROID_PLATFORM}")
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@@ -12,8 +12,8 @@
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifdef WITH_GPU
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#include "fastdeploy/function/cuda_cast.h"
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namespace fastdeploy {
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namespace function {
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template <typename T_IN, typename T_OUT>
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@@ -30,13 +30,11 @@ void CudaCast(const FDTensor& in, FDTensor* out, cudaStream_t stream) {
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if (in.dtype == FDDataType::INT64 && out->dtype == FDDataType::INT32) {
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CudaCastKernel<int64_t, int32_t><<<blocks, threads, 0, stream>>>(
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reinterpret_cast<int64_t*>(const_cast<void*>(in.Data())),
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reinterpret_cast<int32_t*>(out->MutableData()),
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jobs);
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reinterpret_cast<int32_t*>(out->MutableData()), jobs);
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} else if (in.dtype == FDDataType::INT32 && out->dtype == FDDataType::INT64) {
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CudaCastKernel<int32_t, int64_t><<<blocks, threads, 0, stream>>>(
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reinterpret_cast<int32_t*>(const_cast<void*>(in.Data())),
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reinterpret_cast<int64_t*>(out->MutableData()),
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jobs);
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reinterpret_cast<int64_t*>(out->MutableData()), jobs);
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} else {
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FDASSERT(false, "CudaCast only support input INT64, output INT32.");
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}
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@@ -44,3 +42,4 @@ void CudaCast(const FDTensor& in, FDTensor* out, cudaStream_t stream) {
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} // namespace function
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} // namespace fastdeploy
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#endif
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@@ -1,3 +1,19 @@
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifdef WITH_GPU
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#include "adaptive_pool2d_kernel.h"
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namespace fastdeploy {
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@@ -54,3 +70,4 @@ void CudaAdaptivePool(const std::vector<int64_t>& input_dims,
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int(input_dims[3]), int(output_dims[2]), int(output_dims[3]), is_avg);
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}
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} // namespace fastdeploy
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#endif
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@@ -12,14 +12,16 @@
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifdef WITH_GPU
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#include "fastdeploy/vision/common/processors/normalize_and_permute.h"
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namespace fastdeploy {
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namespace vision {
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__global__ void NormalizeAndPermuteKernel(
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uint8_t* src, float* dst, const float* alpha, const float* beta,
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int num_channel, bool swap_rb, int edge) {
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__global__ void NormalizeAndPermuteKernel(uint8_t* src, float* dst,
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const float* alpha, const float* beta,
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int num_channel, bool swap_rb,
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int edge) {
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int idx = blockDim.x * blockIdx.x + threadIdx.x;
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if (idx >= edge) return;
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@@ -38,8 +40,8 @@ bool NormalizeAndPermute::ImplByCuda(Mat* mat) {
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cv::Mat* im = mat->GetOpenCVMat();
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std::string buf_name = Name() + "_src";
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std::vector<int64_t> shape = {im->rows, im->cols, im->channels()};
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FDTensor* src = UpdateAndGetReusedBuffer(shape, im->type(), buf_name,
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Device::GPU);
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FDTensor* src =
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UpdateAndGetReusedBuffer(shape, im->type(), buf_name, Device::GPU);
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FDASSERT(cudaMemcpy(src->Data(), im->ptr(), src->Nbytes(),
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cudaMemcpyHostToDevice) == 0,
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"Error occurs while copy memory from CPU to GPU.");
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@@ -58,7 +60,7 @@ bool NormalizeAndPermute::ImplByCuda(Mat* mat) {
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buf_name = Name() + "_beta";
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FDTensor* beta = UpdateAndGetReusedBuffer({(int64_t)beta_.size()}, CV_32FC1,
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buf_name, Device::GPU);
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buf_name, Device::GPU);
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FDASSERT(cudaMemcpy(beta->Data(), beta_.data(), beta->Nbytes(),
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cudaMemcpyHostToDevice) == 0,
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"Error occurs while copy memory from CPU to GPU.");
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@@ -80,3 +82,4 @@ bool NormalizeAndPermute::ImplByCuda(Mat* mat) {
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} // namespace vision
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} // namespace fastdeploy
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#endif
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47
fastdeploy/vision/detection/contrib/yolov5lite.cc
Executable file → Normal file
47
fastdeploy/vision/detection/contrib/yolov5lite.cc
Executable file → Normal file
@@ -13,11 +13,12 @@
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// limitations under the License.
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#include "fastdeploy/vision/detection/contrib/yolov5lite.h"
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#include "fastdeploy/utils/perf.h"
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#include "fastdeploy/vision/utils/utils.h"
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#ifdef ENABLE_CUDA_PREPROCESS
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#ifdef WITH_GPU
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#include "fastdeploy/vision/utils/cuda_utils.h"
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#endif // ENABLE_CUDA_PREPROCESS
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#endif // WITH_GPU
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namespace fastdeploy {
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namespace vision {
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@@ -99,13 +100,13 @@ YOLOv5Lite::YOLOv5Lite(const std::string& model_file,
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runtime_option.model_format = model_format;
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runtime_option.model_file = model_file;
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runtime_option.params_file = params_file;
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#ifdef ENABLE_CUDA_PREPROCESS
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#ifdef WITH_GPU
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cudaSetDevice(runtime_option.device_id);
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cudaStream_t stream;
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CUDA_CHECK(cudaStreamCreate(&stream));
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cuda_stream_ = reinterpret_cast<void*>(stream);
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runtime_option.SetExternalStream(cuda_stream_);
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#endif // ENABLE_CUDA_PREPROCESS
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#endif // WITH_GPU
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initialized = Initialize();
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}
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@@ -148,14 +149,14 @@ bool YOLOv5Lite::Initialize() {
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}
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YOLOv5Lite::~YOLOv5Lite() {
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#ifdef ENABLE_CUDA_PREPROCESS
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#ifdef WITH_GPU
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if (use_cuda_preprocessing_) {
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CUDA_CHECK(cudaFreeHost(input_img_cuda_buffer_host_));
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CUDA_CHECK(cudaFree(input_img_cuda_buffer_device_));
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CUDA_CHECK(cudaFree(input_tensor_cuda_buffer_device_));
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CUDA_CHECK(cudaStreamDestroy(reinterpret_cast<cudaStream_t>(cuda_stream_)));
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}
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#endif // ENABLE_CUDA_PREPROCESS
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#endif // WITH_GPU
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}
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bool YOLOv5Lite::Preprocess(
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@@ -199,28 +200,33 @@ bool YOLOv5Lite::Preprocess(
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}
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void YOLOv5Lite::UseCudaPreprocessing(int max_image_size) {
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#ifdef ENABLE_CUDA_PREPROCESS
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#ifdef WITH_GPU
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use_cuda_preprocessing_ = true;
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is_scale_up = true;
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if (input_img_cuda_buffer_host_ == nullptr) {
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// prepare input data cache in GPU pinned memory
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CUDA_CHECK(cudaMallocHost((void**)&input_img_cuda_buffer_host_, max_image_size * 3));
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CUDA_CHECK(cudaMallocHost((void**)&input_img_cuda_buffer_host_,
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max_image_size * 3));
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// prepare input data cache in GPU device memory
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CUDA_CHECK(cudaMalloc((void**)&input_img_cuda_buffer_device_, max_image_size * 3));
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CUDA_CHECK(cudaMalloc((void**)&input_tensor_cuda_buffer_device_, 3 * size[0] * size[1] * sizeof(float)));
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CUDA_CHECK(
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cudaMalloc((void**)&input_img_cuda_buffer_device_, max_image_size * 3));
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CUDA_CHECK(cudaMalloc((void**)&input_tensor_cuda_buffer_device_,
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3 * size[0] * size[1] * sizeof(float)));
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}
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#else
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FDWARNING << "The FastDeploy didn't compile with BUILD_CUDA_SRC=ON."
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<< std::endl;
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FDWARNING << "The FastDeploy didn't compile with WITH_GPU=ON." << std::endl;
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use_cuda_preprocessing_ = false;
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#endif
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}
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bool YOLOv5Lite::CudaPreprocess(Mat* mat, FDTensor* output,
|
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std::map<std::string, std::array<float, 2>>* im_info) {
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#ifdef ENABLE_CUDA_PREPROCESS
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bool YOLOv5Lite::CudaPreprocess(
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Mat* mat, FDTensor* output,
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std::map<std::string, std::array<float, 2>>* im_info) {
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#ifdef WITH_GPU
|
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if (is_mini_pad != false || is_no_pad != false || is_scale_up != true) {
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FDERROR << "Preprocessing with CUDA is only available when the arguments satisfy (is_mini_pad=false, is_no_pad=false, is_scale_up=true)." << std::endl;
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FDERROR << "Preprocessing with CUDA is only available when the arguments "
|
||||
"satisfy (is_mini_pad=false, is_no_pad=false, is_scale_up=true)."
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<< std::endl;
|
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return false;
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}
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|
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@@ -234,14 +240,15 @@ bool YOLOv5Lite::CudaPreprocess(Mat* mat, FDTensor* output,
|
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int src_img_buf_size = mat->Height() * mat->Width() * mat->Channels();
|
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memcpy(input_img_cuda_buffer_host_, mat->Data(), src_img_buf_size);
|
||||
CUDA_CHECK(cudaMemcpyAsync(input_img_cuda_buffer_device_,
|
||||
input_img_cuda_buffer_host_,
|
||||
src_img_buf_size, cudaMemcpyHostToDevice, stream));
|
||||
input_img_cuda_buffer_host_, src_img_buf_size,
|
||||
cudaMemcpyHostToDevice, stream));
|
||||
utils::CudaYoloPreprocess(input_img_cuda_buffer_device_, mat->Width(),
|
||||
mat->Height(), input_tensor_cuda_buffer_device_,
|
||||
size[0], size[1], padding_value, stream);
|
||||
|
||||
// Record output shape of preprocessed image
|
||||
(*im_info)["output_shape"] = {static_cast<float>(size[0]), static_cast<float>(size[1])};
|
||||
(*im_info)["output_shape"] = {static_cast<float>(size[0]),
|
||||
static_cast<float>(size[1])};
|
||||
|
||||
output->SetExternalData({mat->Channels(), size[0], size[1]}, FDDataType::FP32,
|
||||
input_tensor_cuda_buffer_device_);
|
||||
@@ -251,7 +258,7 @@ bool YOLOv5Lite::CudaPreprocess(Mat* mat, FDTensor* output,
|
||||
#else
|
||||
FDERROR << "CUDA src code was not enabled." << std::endl;
|
||||
return false;
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
}
|
||||
|
||||
bool YOLOv5Lite::PostprocessWithDecode(
|
||||
|
||||
21
fastdeploy/vision/detection/contrib/yolov6.cc
Executable file → Normal file
21
fastdeploy/vision/detection/contrib/yolov6.cc
Executable file → Normal file
@@ -16,9 +16,9 @@
|
||||
|
||||
#include "fastdeploy/utils/perf.h"
|
||||
#include "fastdeploy/vision/utils/utils.h"
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
#include "fastdeploy/vision/utils/cuda_utils.h"
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
|
||||
namespace fastdeploy {
|
||||
|
||||
@@ -79,13 +79,13 @@ YOLOv6::YOLOv6(const std::string& model_file, const std::string& params_file,
|
||||
runtime_option.model_format = model_format;
|
||||
runtime_option.model_file = model_file;
|
||||
runtime_option.params_file = params_file;
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
cudaSetDevice(runtime_option.device_id);
|
||||
cudaStream_t stream;
|
||||
CUDA_CHECK(cudaStreamCreate(&stream));
|
||||
cuda_stream_ = reinterpret_cast<void*>(stream);
|
||||
runtime_option.SetExternalStream(cuda_stream_);
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
initialized = Initialize();
|
||||
}
|
||||
|
||||
@@ -123,14 +123,14 @@ bool YOLOv6::Initialize() {
|
||||
}
|
||||
|
||||
YOLOv6::~YOLOv6() {
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
if (use_cuda_preprocessing_) {
|
||||
CUDA_CHECK(cudaFreeHost(input_img_cuda_buffer_host_));
|
||||
CUDA_CHECK(cudaFree(input_img_cuda_buffer_device_));
|
||||
CUDA_CHECK(cudaFree(input_tensor_cuda_buffer_device_));
|
||||
CUDA_CHECK(cudaStreamDestroy(reinterpret_cast<cudaStream_t>(cuda_stream_)));
|
||||
}
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
}
|
||||
|
||||
bool YOLOv6::Preprocess(Mat* mat, FDTensor* output,
|
||||
@@ -173,7 +173,7 @@ bool YOLOv6::Preprocess(Mat* mat, FDTensor* output,
|
||||
}
|
||||
|
||||
void YOLOv6::UseCudaPreprocessing(int max_image_size) {
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
use_cuda_preprocessing_ = true;
|
||||
is_scale_up = true;
|
||||
if (input_img_cuda_buffer_host_ == nullptr) {
|
||||
@@ -187,8 +187,7 @@ void YOLOv6::UseCudaPreprocessing(int max_image_size) {
|
||||
3 * size[0] * size[1] * sizeof(float)));
|
||||
}
|
||||
#else
|
||||
FDWARNING << "The FastDeploy didn't compile with BUILD_CUDA_SRC=ON."
|
||||
<< std::endl;
|
||||
FDWARNING << "The FastDeploy didn't compile with WITH_GPU=ON." << std::endl;
|
||||
use_cuda_preprocessing_ = false;
|
||||
#endif
|
||||
}
|
||||
@@ -196,7 +195,7 @@ void YOLOv6::UseCudaPreprocessing(int max_image_size) {
|
||||
bool YOLOv6::CudaPreprocess(
|
||||
Mat* mat, FDTensor* output,
|
||||
std::map<std::string, std::array<float, 2>>* im_info) {
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
if (is_mini_pad != false || is_no_pad != false || is_scale_up != true) {
|
||||
FDERROR << "Preprocessing with CUDA is only available when the arguments "
|
||||
"satisfy (is_mini_pad=false, is_no_pad=false, is_scale_up=true)."
|
||||
@@ -232,7 +231,7 @@ bool YOLOv6::CudaPreprocess(
|
||||
#else
|
||||
FDERROR << "CUDA src code was not enabled." << std::endl;
|
||||
return false;
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
}
|
||||
|
||||
bool YOLOv6::Postprocess(
|
||||
|
||||
47
fastdeploy/vision/detection/contrib/yolov7end2end_trt.cc
Executable file → Normal file
47
fastdeploy/vision/detection/contrib/yolov7end2end_trt.cc
Executable file → Normal file
@@ -13,11 +13,12 @@
|
||||
// limitations under the License.
|
||||
|
||||
#include "fastdeploy/vision/detection/contrib/yolov7end2end_trt.h"
|
||||
|
||||
#include "fastdeploy/utils/perf.h"
|
||||
#include "fastdeploy/vision/utils/utils.h"
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
#include "fastdeploy/vision/utils/cuda_utils.h"
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
|
||||
namespace fastdeploy {
|
||||
namespace vision {
|
||||
@@ -88,13 +89,13 @@ YOLOv7End2EndTRT::YOLOv7End2EndTRT(const std::string& model_file,
|
||||
runtime_option.backend = Backend::TRT;
|
||||
}
|
||||
}
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
cudaSetDevice(runtime_option.device_id);
|
||||
cudaStream_t stream;
|
||||
CUDA_CHECK(cudaStreamCreate(&stream));
|
||||
cuda_stream_ = reinterpret_cast<void*>(stream);
|
||||
runtime_option.SetExternalStream(cuda_stream_);
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
initialized = Initialize();
|
||||
}
|
||||
|
||||
@@ -131,14 +132,14 @@ bool YOLOv7End2EndTRT::Initialize() {
|
||||
}
|
||||
|
||||
YOLOv7End2EndTRT::~YOLOv7End2EndTRT() {
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
if (use_cuda_preprocessing_) {
|
||||
CUDA_CHECK(cudaFreeHost(input_img_cuda_buffer_host_));
|
||||
CUDA_CHECK(cudaFree(input_img_cuda_buffer_device_));
|
||||
CUDA_CHECK(cudaFree(input_tensor_cuda_buffer_device_));
|
||||
CUDA_CHECK(cudaStreamDestroy(reinterpret_cast<cudaStream_t>(cuda_stream_)));
|
||||
}
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
}
|
||||
|
||||
bool YOLOv7End2EndTRT::Preprocess(
|
||||
@@ -173,28 +174,33 @@ bool YOLOv7End2EndTRT::Preprocess(
|
||||
}
|
||||
|
||||
void YOLOv7End2EndTRT::UseCudaPreprocessing(int max_image_size) {
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
#ifdef WITH_GPU
|
||||
use_cuda_preprocessing_ = true;
|
||||
is_scale_up = true;
|
||||
if (input_img_cuda_buffer_host_ == nullptr) {
|
||||
// prepare input data cache in GPU pinned memory
|
||||
CUDA_CHECK(cudaMallocHost((void**)&input_img_cuda_buffer_host_, max_image_size * 3));
|
||||
CUDA_CHECK(cudaMallocHost((void**)&input_img_cuda_buffer_host_,
|
||||
max_image_size * 3));
|
||||
// prepare input data cache in GPU device memory
|
||||
CUDA_CHECK(cudaMalloc((void**)&input_img_cuda_buffer_device_, max_image_size * 3));
|
||||
CUDA_CHECK(cudaMalloc((void**)&input_tensor_cuda_buffer_device_, 3 * size[0] * size[1] * sizeof(float)));
|
||||
CUDA_CHECK(
|
||||
cudaMalloc((void**)&input_img_cuda_buffer_device_, max_image_size * 3));
|
||||
CUDA_CHECK(cudaMalloc((void**)&input_tensor_cuda_buffer_device_,
|
||||
3 * size[0] * size[1] * sizeof(float)));
|
||||
}
|
||||
#else
|
||||
FDWARNING << "The FastDeploy didn't compile with BUILD_CUDA_SRC=ON."
|
||||
<< std::endl;
|
||||
FDWARNING << "The FastDeploy didn't compile with WITH_GPU=ON." << std::endl;
|
||||
use_cuda_preprocessing_ = false;
|
||||
#endif
|
||||
}
|
||||
|
||||
bool YOLOv7End2EndTRT::CudaPreprocess(Mat* mat, FDTensor* output,
|
||||
std::map<std::string, std::array<float, 2>>* im_info) {
|
||||
#ifdef ENABLE_CUDA_PREPROCESS
|
||||
bool YOLOv7End2EndTRT::CudaPreprocess(
|
||||
Mat* mat, FDTensor* output,
|
||||
std::map<std::string, std::array<float, 2>>* im_info) {
|
||||
#ifdef WITH_GPU
|
||||
if (is_mini_pad != false || is_no_pad != false || is_scale_up != true) {
|
||||
FDERROR << "Preprocessing with CUDA is only available when the arguments satisfy (is_mini_pad=false, is_no_pad=false, is_scale_up=true)." << std::endl;
|
||||
FDERROR << "Preprocessing with CUDA is only available when the arguments "
|
||||
"satisfy (is_mini_pad=false, is_no_pad=false, is_scale_up=true)."
|
||||
<< std::endl;
|
||||
return false;
|
||||
}
|
||||
|
||||
@@ -208,14 +214,15 @@ bool YOLOv7End2EndTRT::CudaPreprocess(Mat* mat, FDTensor* output,
|
||||
int src_img_buf_size = mat->Height() * mat->Width() * mat->Channels();
|
||||
memcpy(input_img_cuda_buffer_host_, mat->Data(), src_img_buf_size);
|
||||
CUDA_CHECK(cudaMemcpyAsync(input_img_cuda_buffer_device_,
|
||||
input_img_cuda_buffer_host_,
|
||||
src_img_buf_size, cudaMemcpyHostToDevice, stream));
|
||||
input_img_cuda_buffer_host_, src_img_buf_size,
|
||||
cudaMemcpyHostToDevice, stream));
|
||||
utils::CudaYoloPreprocess(input_img_cuda_buffer_device_, mat->Width(),
|
||||
mat->Height(), input_tensor_cuda_buffer_device_,
|
||||
size[0], size[1], padding_value, stream);
|
||||
|
||||
// Record output shape of preprocessed image
|
||||
(*im_info)["output_shape"] = {static_cast<float>(size[0]), static_cast<float>(size[1])};
|
||||
(*im_info)["output_shape"] = {static_cast<float>(size[0]),
|
||||
static_cast<float>(size[1])};
|
||||
|
||||
output->SetExternalData({mat->Channels(), size[0], size[1]}, FDDataType::FP32,
|
||||
input_tensor_cuda_buffer_device_);
|
||||
@@ -225,7 +232,7 @@ bool YOLOv7End2EndTRT::CudaPreprocess(Mat* mat, FDTensor* output,
|
||||
#else
|
||||
FDERROR << "CUDA src code was not enabled." << std::endl;
|
||||
return false;
|
||||
#endif // ENABLE_CUDA_PREPROCESS
|
||||
#endif // WITH_GPU
|
||||
}
|
||||
|
||||
bool YOLOv7End2EndTRT::Postprocess(
|
||||
|
||||
@@ -21,9 +21,11 @@
|
||||
// \brief
|
||||
// \author Qi Liu, Xinyu Wang
|
||||
|
||||
#include "fastdeploy/vision/utils/cuda_utils.h"
|
||||
#ifdef WITH_GPU
|
||||
#include <opencv2/opencv.hpp>
|
||||
|
||||
#include "fastdeploy/vision/utils/cuda_utils.h"
|
||||
|
||||
namespace fastdeploy {
|
||||
namespace vision {
|
||||
namespace utils {
|
||||
@@ -33,11 +35,10 @@ struct AffineMatrix {
|
||||
};
|
||||
|
||||
__global__ void YoloPreprocessCudaKernel(
|
||||
uint8_t* src, int src_line_size, int src_width,
|
||||
int src_height, float* dst, int dst_width,
|
||||
int dst_height, uint8_t padding_color_b,
|
||||
uint8_t padding_color_g, uint8_t padding_color_r,
|
||||
AffineMatrix d2s, int edge) {
|
||||
uint8_t* src, int src_line_size, int src_width, int src_height, float* dst,
|
||||
int dst_width, int dst_height, uint8_t padding_color_b,
|
||||
uint8_t padding_color_g, uint8_t padding_color_r, AffineMatrix d2s,
|
||||
int edge) {
|
||||
int position = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
if (position >= edge) return;
|
||||
|
||||
@@ -111,16 +112,17 @@ __global__ void YoloPreprocessCudaKernel(
|
||||
*pdst_c2 = c2;
|
||||
}
|
||||
|
||||
void CudaYoloPreprocess(
|
||||
uint8_t* src, int src_width, int src_height,
|
||||
float* dst, int dst_width, int dst_height,
|
||||
const std::vector<float> padding_value, cudaStream_t stream) {
|
||||
void CudaYoloPreprocess(uint8_t* src, int src_width, int src_height, float* dst,
|
||||
int dst_width, int dst_height,
|
||||
const std::vector<float> padding_value,
|
||||
cudaStream_t stream) {
|
||||
AffineMatrix s2d, d2s;
|
||||
float scale = std::min(dst_height / (float)src_height, dst_width / (float)src_width);
|
||||
float scale =
|
||||
std::min(dst_height / (float)src_height, dst_width / (float)src_width);
|
||||
|
||||
s2d.value[0] = scale;
|
||||
s2d.value[1] = 0;
|
||||
s2d.value[2] = -scale * src_width * 0.5 + dst_width * 0.5;
|
||||
s2d.value[2] = -scale * src_width * 0.5 + dst_width * 0.5;
|
||||
s2d.value[3] = 0;
|
||||
s2d.value[4] = scale;
|
||||
s2d.value[5] = -scale * src_height * 0.5 + dst_height * 0.5;
|
||||
@@ -135,12 +137,11 @@ void CudaYoloPreprocess(
|
||||
int threads = 256;
|
||||
int blocks = ceil(jobs / (float)threads);
|
||||
YoloPreprocessCudaKernel<<<blocks, threads, 0, stream>>>(
|
||||
src, src_width * 3, src_width,
|
||||
src_height, dst, dst_width,
|
||||
dst_height, padding_value[0], padding_value[1], padding_value[2], d2s, jobs);
|
||||
|
||||
src, src_width * 3, src_width, src_height, dst, dst_width, dst_height,
|
||||
padding_value[0], padding_value[1], padding_value[2], d2s, jobs);
|
||||
}
|
||||
|
||||
} // namespace utils
|
||||
} // namespace vision
|
||||
} // namespace fastdeploy
|
||||
#endif
|
||||
|
||||
Reference in New Issue
Block a user