From dd01b3ca0bb37e04550ed6a6d9e01aee6299197d Mon Sep 17 00:00:00 2001 From: Zheng-Bicheng <58363586+Zheng-Bicheng@users.noreply.github.com> Date: Wed, 11 Jan 2023 13:56:17 +0800 Subject: [PATCH] =?UTF-8?q?[Model]=20=E6=9B=B4=E6=96=B0SCRFD=E6=A8=A1?= =?UTF-8?q?=E5=9E=8Bdemo=E4=BB=A5=E5=8F=8A=E6=96=87=E6=A1=A3=20(#1108)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * 更新scrfd * 更新scrfd --- .../vision/facedet/scrfd/rknpu2/README_CN.md | 2 +- .../facedet/scrfd/rknpu2/cpp/CMakeLists.txt | 39 +++--------- .../facedet/scrfd/rknpu2/cpp/README_CN.md | 59 +++++-------------- .../vision/facedet/scrfd/rknpu2/cpp/infer.cc | 38 ++++++------ .../{scrfd.yaml => scrfd_quantized.yaml} | 4 +- tools/rknpu2/config/scrfd_unquantized.yaml | 15 +++++ tools/rknpu2/export.py | 21 +++++-- 7 files changed, 78 insertions(+), 100 deletions(-) rename tools/rknpu2/config/{scrfd.yaml => scrfd_quantized.yaml} (79%) create mode 100644 tools/rknpu2/config/scrfd_unquantized.yaml diff --git a/examples/vision/facedet/scrfd/rknpu2/README_CN.md b/examples/vision/facedet/scrfd/rknpu2/README_CN.md index 00a8c0844..dd5e9e1c8 100644 --- a/examples/vision/facedet/scrfd/rknpu2/README_CN.md +++ b/examples/vision/facedet/scrfd/rknpu2/README_CN.md @@ -10,7 +10,7 @@ wget https://bj.bcebos.com/paddlehub/fastdeploy/rknpu2/scrfd_500m_bnkps_shape640x640.zip unzip scrfd_500m_bnkps_shape640x640.zip python /Path/To/FastDeploy/tools/rknpu2/export.py \ - --config_path tools/rknpu2/config/scrfd.yaml \ + --config_path tools/rknpu2/config/scrfd_quantized.yaml \ --target_platform rk3588 ``` diff --git a/examples/vision/facedet/scrfd/rknpu2/cpp/CMakeLists.txt b/examples/vision/facedet/scrfd/rknpu2/cpp/CMakeLists.txt index 7e207d8e4..7853ccb1a 100644 --- a/examples/vision/facedet/scrfd/rknpu2/cpp/CMakeLists.txt +++ b/examples/vision/facedet/scrfd/rknpu2/cpp/CMakeLists.txt @@ -1,36 +1,15 @@ -CMAKE_MINIMUM_REQUIRED(VERSION 3.10) -project(rknpu_test) - -set(CMAKE_CXX_STANDARD 14) +PROJECT(infer_demo C CXX) +CMAKE_MINIMUM_REQUIRED (VERSION 3.10) # 指定下载解压后的fastdeploy库路径 -set(FASTDEPLOY_INSTALL_DIR "thirdpartys/fastdeploy-0.7.0") +option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.") -include(${FASTDEPLOY_INSTALL_DIR}/FastDeployConfig.cmake) -include_directories(${FastDeploy_INCLUDE_DIRS}) -add_executable(rknpu_test infer.cc) -target_link_libraries(rknpu_test - ${FastDeploy_LIBS} - ) +include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake) -set(CMAKE_INSTALL_PREFIX ${CMAKE_SOURCE_DIR}/build/install) +# 添加FastDeploy依赖头文件 +include_directories(${FASTDEPLOY_INCS}) -install(TARGETS rknpu_test DESTINATION ./) +add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.cc) -install(DIRECTORY model DESTINATION ./) -install(DIRECTORY images DESTINATION ./) - -file(GLOB FASTDEPLOY_LIBS ${FASTDEPLOY_INSTALL_DIR}/lib/*) -message("${FASTDEPLOY_LIBS}") -install(PROGRAMS ${FASTDEPLOY_LIBS} DESTINATION lib) - -file(GLOB ONNXRUNTIME_LIBS ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/onnxruntime/lib/*) -install(PROGRAMS ${ONNXRUNTIME_LIBS} DESTINATION lib) - -install(DIRECTORY ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/opencv/lib DESTINATION ./) - -file(GLOB PADDLETOONNX_LIBS ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/paddle2onnx/lib/*) -install(PROGRAMS ${PADDLETOONNX_LIBS} DESTINATION lib) - -file(GLOB RKNPU2_LIBS ${FASTDEPLOY_INSTALL_DIR}/third_libs/install/rknpu2_runtime/RK3588/lib/*) -install(PROGRAMS ${RKNPU2_LIBS} DESTINATION lib) +# 添加FastDeploy库依赖 +target_link_libraries(infer_demo ${FASTDEPLOY_LIBS}) diff --git a/examples/vision/facedet/scrfd/rknpu2/cpp/README_CN.md b/examples/vision/facedet/scrfd/rknpu2/cpp/README_CN.md index f32433fd4..dda3f0b3b 100644 --- a/examples/vision/facedet/scrfd/rknpu2/cpp/README_CN.md +++ b/examples/vision/facedet/scrfd/rknpu2/cpp/README_CN.md @@ -1,66 +1,37 @@ [English](README.md) | 简体中文 # SCRFD C++部署示例 -本目录下提供`infer.cc`快速完成SCRFD在NPU加速部署的示例。 +本目录下提供`infer.cc`在RK356X上，快速完成SCRFD在NPU加速部署的示例。 在部署前，需确认以下两个步骤: 1. 软硬件环境满足要求 2. 根据开发环境，下载预编译部署库或者从头编译FastDeploy仓库 -以上步骤请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)实现 - -## 生成基本目录文件 - -该例程由以下几个部分组成 -```text -. -├── CMakeLists.txt -├── build # 编译文件夹 -├── image # 存放图片的文件夹 -├── infer.cc -├── model # 存放模型文件的文件夹 -└── thirdpartys # 存放sdk的文件夹 -``` - -首先需要先生成目录结构 -```bash -mkdir build -mkdir images -mkdir model -mkdir thirdpartys -``` +以上步骤请参考[RK2代NPU文档导航](../../../../../../docs/cn/build_and_install/rknpu2.md)实现 ## 编译 -### 编译并拷贝SDK到thirdpartys文件夹 - -请参考[RK2代NPU部署库编译](../../../../../../docs/cn/build_and_install/rknpu2.md)仓库编译SDK，编译完成后，将在build目录下生成 -fastdeploy-0.7.0目录，请移动它至thirdpartys目录下. - -### 拷贝模型文件至model文件夹 -请参考[SCRFD模型转换文档](../README.md)转换SCRFD ONNX模型到RKNN模型,再将RKNN模型移动到model文件夹。 - -### 准备测试图片至image文件夹 -```bash -wget https://raw.githubusercontent.com/DefTruth/lite.ai.toolkit/main/examples/lite/resources/test_lite_face_detector_3.jpg -cp test_lite_face_detector_3.jpg ./images -``` - -### 编译example - ```bash +mkdir build cd build -cmake .. +# 下载FastDeploy预编译库，用户可在上文提到的`FastDeploy预编译库`中自行选择合适的版本使用 +wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-aarch64-rk356X-x.x.x.tgz +tar -xzvf fastdeploy-linux-aarch64-rk356X-x.x.x.tgz +cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-aarch64-rk356X make -j8 -make install ``` + ## 运行例程 ```bash -cd ./build/install -export LD_LIBRARY_PATH=${PWD}/lib:${LD_LIBRARY_PATH} -./rknpu_test +#下载官方转换好的SCRFD模型文件和测试图片 +wget https://bj.bcebos.com/paddlehub/fastdeploy/rknpu2/scrfd_500m_bnkps_shape640x640_rknpu2.zip +unzip scrfd_500m_bnkps_shape640x640_rknpu2.zip +wget https://raw.githubusercontent.com/DefTruth/lite.ai.toolkit/main/examples/lite/resources/test_lite_face_detector_3.jpg +./infer_demo scrfd_500m_bnkps_shape640x640_rknpu2/scrfd_500m_bnkps_shape640x640_rk3568_quantized.rknn \ + test_lite_face_detector_3.jpg \ + 1 ``` 运行完成可视化结果如下图所示 diff --git a/examples/vision/facedet/scrfd/rknpu2/cpp/infer.cc b/examples/vision/facedet/scrfd/rknpu2/cpp/infer.cc index 6ae869fe4..36e961e9a 100644 --- a/examples/vision/facedet/scrfd/rknpu2/cpp/infer.cc +++ b/examples/vision/facedet/scrfd/rknpu2/cpp/infer.cc @@ -1,16 +1,16 @@ #include #include + #include "fastdeploy/vision.h" -void ONNXInfer(const std::string& model_dir, const std::string& image_file) { - std::string model_file = model_dir + "/scrfd_500m_bnkps_shape640x640.onnx"; +void ONNXInfer(const std::string& model_file, const std::string& image_file) { std::string params_file; auto option = fastdeploy::RuntimeOption(); option.UseCpu(); auto format = fastdeploy::ModelFormat::ONNX; - auto model = fastdeploy::vision::facedet::SCRFD( - model_file, params_file, option, format); + auto model = fastdeploy::vision::facedet::SCRFD(model_file, params_file, + option, format); if (!model.Initialized()) { std::cerr << "Failed to initialize." << std::endl; @@ -31,19 +31,17 @@ void ONNXInfer(const std::string& model_dir, const std::string& image_file) { std::cout << res.Str() << std::endl; cv::imwrite("infer_onnx.jpg", vis_im); - std::cout - << "Visualized result saved in ./infer_onnx.jpg" - << std::endl; + std::cout << "Visualized result saved in ./infer_onnx.jpg" << std::endl; } -void RKNPU2Infer(const std::string& model_dir, const std::string& image_file) { - std::string model_file = model_dir + "/scrfd_500m_bnkps_shape640x640_rk3588.rknn"; +void RKNPU2Infer(const std::string& model_file, const std::string& image_file) { std::string params_file; auto option = fastdeploy::RuntimeOption(); option.UseRKNPU2(); auto format = fastdeploy::ModelFormat::RKNN; - auto model = fastdeploy::vision::facedet::SCRFD(model_file, params_file, option, format); + auto model = fastdeploy::vision::facedet::SCRFD(model_file, params_file, + option, format); if (!model.Initialized()) { std::cerr << "Failed to initialize." << std::endl; @@ -66,21 +64,25 @@ void RKNPU2Infer(const std::string& model_dir, const std::string& image_file) { std::cout << res.Str() << std::endl; cv::imwrite("infer_rknn.jpg", vis_im); - std::cout - << "Visualized result saved in ./infer_rknn.jpg" - << std::endl; + std::cout << "Visualized result saved in ./infer_rknn.jpg" << std::endl; } int main(int argc, char* argv[]) { - if (argc < 3) { + if (argc < 4) { std::cout - << "Usage: infer_demo path/to/model_dir path/to/image run_option, " - "e.g ./infer_model ./picodet_model_dir ./test.jpeg" + << "Usage: infer_demo path/to/model path/to/image run_option, " + "e.g ./infer_model scrfd_500m_bnkps_shape640x640.onnx ./test.jpeg 0" << std::endl; + std::cout << "The data type of run_option is int, " + "0: run with cpu; 1: run with rknpu2." + << std::endl; return -1; } - RKNPU2Infer(argv[1], argv[2]); - ONNXInfer(argv[1], argv[2]); + if (std::atoi(argv[3]) == 0) { + ONNXInfer(argv[1], argv[2]); + } else if (std::atoi(argv[3]) == 1) { + RKNPU2Infer(argv[1], argv[2]); + } return 0; } \ No newline at end of file diff --git a/tools/rknpu2/config/scrfd.yaml b/tools/rknpu2/config/scrfd_quantized.yaml similarity index 79% rename from tools/rknpu2/config/scrfd.yaml rename to tools/rknpu2/config/scrfd_quantized.yaml index 454d762ab..58b6f0b09 100644 --- a/tools/rknpu2/config/scrfd.yaml +++ b/tools/rknpu2/config/scrfd_quantized.yaml @@ -11,5 +11,5 @@ std: model_path: ./scrfd_500m_bnkps_shape640x640.onnx outputs_nodes: do_quantization: True -dataset: "./datasets.txt" -output_folder: "./" \ No newline at end of file +dataset: "./dataset.txt" +output_folder: "./" diff --git a/tools/rknpu2/config/scrfd_unquantized.yaml b/tools/rknpu2/config/scrfd_unquantized.yaml new file mode 100644 index 000000000..11a434eca --- /dev/null +++ b/tools/rknpu2/config/scrfd_unquantized.yaml @@ -0,0 +1,15 @@ +mean: + - + - 128.5 + - 128.5 + - 128.5 +std: + - + - 128.5 + - 128.5 + - 128.5 +model_path: ./scrfd_500m_bnkps_shape640x640.onnx +outputs_nodes: +do_quantization: False +dataset: "./dataset.txt" +output_folder: "./" diff --git a/tools/rknpu2/export.py b/tools/rknpu2/export.py index 062f4fd82..c42a1eade 100644 --- a/tools/rknpu2/export.py +++ b/tools/rknpu2/export.py @@ -37,17 +37,24 @@ if __name__ == "__main__": # Config mean_values = yaml_config["mean"] std_values = yaml_config["std"] - model.config(mean_values=mean_values, std_values=std_values, target_platform=config.target_platform) + model.config( + mean_values=mean_values, + std_values=std_values, + target_platform=config.target_platform) # Load ONNX model if yaml_config["outputs_nodes"] is None: ret = model.load_onnx(model=yaml_config["model_path"]) else: - ret = model.load_onnx(model=yaml_config["model_path"], outputs=yaml_config["outputs_nodes"]) + ret = model.load_onnx( + model=yaml_config["model_path"], + outputs=yaml_config["outputs_nodes"]) assert ret == 0, "Load model failed!" # Build model - ret = model.build(do_quantization=yaml_config["do_quantization"], dataset=yaml_config["dataset"]) + ret = model.build( + do_quantization=yaml_config["do_quantization"], + dataset=yaml_config["dataset"]) assert ret == 0, "Build model failed!" # Init Runtime @@ -60,7 +67,11 @@ if __name__ == "__main__": model_base_name = os.path.basename(yaml_config["model_path"]).split(".")[0] model_device_name = config.target_platform.lower() - model_save_name = model_base_name + "_" + model_device_name + ".rknn" - ret = model.export_rknn(os.path.join(yaml_config["output_folder"], model_save_name)) + if yaml_config["do_quantization"]: + model_save_name = model_base_name + "_" + model_device_name + "_quantized" + ".rknn" + else: + model_save_name = model_base_name + "_" + model_device_name + "_unquantized" + ".rknn" + ret = model.export_rknn( + os.path.join(yaml_config["output_folder"], model_save_name)) assert ret == 0, "Export rknn model failed!" print("Export OK!")