Code cleanup and readme fixes
This commit is contained in:
perseusdg
+3
-3
@@ -3,11 +3,11 @@ cmake_minimum_required(VERSION 3.5)
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project (tkDNN)
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set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} ${CMAKE_CURRENT_SOURCE_DIR}/cmake)
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if(UNIX)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14 -fPIC -Wno-deprecated-declarations -Wno-unused-variable")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -fPIC -Wno-deprecated-declarations -Wno-unused-variable -g ")
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endif()
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if(WIN32)
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set(CMAKE_CXX_STANDARD 14)
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set(CMAKE_CXX_FLAGS "/O1 /FS /EHsc")
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set(CMAKE_CXX_STANDARD 11)
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set(CMAKE_CXX_FLAGS "/O2 /FS /EHsc")
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set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
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endif(WIN32)
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include_directories(${CMAKE_CURRENT_SOURCE_DIR}/include/tkDNN)
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@@ -80,12 +80,13 @@ Results for COCO val 2017 (5k images), on RTX 2080Ti, with conf threshold=0.001
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- [mAP demo](#map-demo)
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- [Existing tests and supported networks](#existing-tests-and-supported-networks)
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- [References](#references)
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- [tkDNN on Windows 10 (experimental)](#tkdnn-on-windows)
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- [tkDNN on Windows 10 (experimental)](#tkdnn-on-windows-10-experimental)
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- [Dependencies-Windows](#dependencies-windows)
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- [Compiling tkDNN on Windows](#tkdnn-windows-compile)
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- [Compiling tkDNN on Windows](#compiling-tkdnn-on-windows)
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- [Run the demo on Windows](#run-the-demo-on-windows)
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- [FP16 interference windows](#fp16-windows)
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- [INT8 interference windows](#int8-windows)
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- [FP16 inference windows](#fp16-inference-windows)
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- [INT8 inference windows](#int8-inference-windows)
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- [Known issues with tkDNN on Windows](#known-issues-with-tkdnn-on-windows)
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@@ -362,26 +363,31 @@ This demo also creates a json file named ```net_name_COCO_res.json``` containing
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| yolo4tiny | Yolov4 tiny <sup>9</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 416x416 | [weights](https://cloud.hipert.unimore.it/s/iRnc4pSqmx78gJs/download) |
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| yolo4x | Yolov4x-mish <sup>9</sup> | [COCO 2017](http://cocodataset.org/) | 80 | 672x672 | [weights](https://cloud.hipert.unimore.it/s/BLPpiAigZJLorQD/download) |
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##tkDNN on Windows 10 (experimental)
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### tkDNN on Windows 10 (experimental)
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### Dependencies-Windows
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This branch should work on every NVIDIA GPU supported in windows with the following dependencies:
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* WINDOWS 10 1803 or HIGHER
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* CUDA 10.0 (Recommended CUDA 11.0 +)
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* CUDNN 7.6 (Recommended CUDNN 8.0.0 +)
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* TENSORRT 6.0.1 (Recommended TENSORRT 7.1 +)
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* OPENCV 3.4 (Recommended OPENCV 4.2.0 +)
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* MSVC 16.7 (Recommended MSVC 16.8/16.9)
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* YAML-CPP 0.5.2
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* CUDA 10.0 (Recommended CUDA 11.2 )
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* CUDNN 7.6 (Recommended CUDNN 8.1.1 )
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* TENSORRT 6.0.1 (Recommended TENSORRT 7.2.3.4 )
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* OPENCV 3.4 (Recommended OPENCV 4.2.0 )
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* MSVC 16.7
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* YAML-CPP
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* EIGEN3
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* 7ZIP (ADD TO PATH)
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* NINJA 1.10
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All the above mentioned dependencies except 7ZIP can be installed using Microsoft's [VCPKG](https://github.com/microsoft/vcpkg.git) .
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After bootstrapping VCPKG the dependencies can be built and installed using the following command :
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```vcpkg.exe install opencv4[tbb,jpeg,tiff,opengl,openmp,png,ffmpeg]:x64-windows yaml-cpp:x64-windows eigen3:x64-windows --x-install-root=C:\opt --x-buildtrees-root=C:\temp_vcpkg_build```
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```
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opencv4(normal) - vcpkg.exe install opencv4[tbb,jpeg,tiff,opengl,openmp,png,ffmpeg,eigen]:x64-windows yaml-cpp:x64-windows eigen3:x64-windows --x-install-root=C:\opt --x-buildtrees-root=C:\temp_vcpkg_build
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opencv4(cuda) - vcpkg.exe install opencv4[cuda,nonfree,contrib,eigen,tbb,jpeg,tiff,opengl,openmp,png,ffmpeg]:x64-windows yaml-cpp:x64-windows eigen3:x64-windows --x-install-root=C:\opt --x-buildtrees-root=C:\temp_vcpkg_build
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```
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After VCPKG finishes building and installing all the packages delete C:\temp_vcpkg_build and add C:\opt\x64-windows\bin and C:\opt\x64-windows\debug\bin to path
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@@ -411,7 +417,7 @@ Once the rt file has been successfully create,run the demo using the following c
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```
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For general info on more demo paramters,check Run the demo section on top
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### FP16 interference windows
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### FP16 inference windows
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This is an untested feature on windows.To run the object detection demo with FP16 interference follow the below steps(example with yolo4tiny):
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```
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@@ -421,7 +427,7 @@ del /f yolo4tiny_fp16.rt
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.\demo.exe yolo4tiny_fp16.rt ..\demo\yolo_test.mp4
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```
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### INT8 interference windows
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### INT8 inference windows
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To run object detection demo with INT8 (example with yolo4tiny):
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```
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set TKDNN_MODE=INT8
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@@ -433,10 +439,13 @@ del /f yolo4tiny_int8.rt # be sure to delete(or move) old tensorRT files
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```
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### Known issues with tkDNN on Windows
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Mobilenet and Centernet demos work properly only when built with msvc 16.7 in Release Mode,when built in debug mode for the mentioned networks one might encounter opencv assert errors
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All Darknet models work properly with demo using MSVC version(16.7-16.9)
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It is recommended to use Nvidia Driver(465+),Cuda unknown errors have been observed when using older drivers on pascal(SM 61) devices.
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+6
-1
@@ -25,7 +25,12 @@ int main(int argc, char *argv[]) {
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std::string net = "yolo4tiny_fp32.rt";
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if(argc > 1)
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net = argv[1];
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std::string input = "..\..\..\demo\yolo_test.mp4";
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#ifdef __linux__
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std::string input = "../demo/yolo_test.mp4";
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#elif _WIN32
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std::string input = "..\\..\\..\\demo\\yolo_test.mp4";
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#endif
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if(argc > 2)
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input = argv[2];
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char ntype = 'y';
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@@ -17,7 +17,7 @@
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#include "tkdnn.h"
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#define OPENCV_CUDACONTRIB //if OPENCV has been compiled with CUDA and contrib.
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//#define OPENCV_CUDACONTRIB //if OPENCV has been compiled with CUDA and contrib.
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#ifdef OPENCV_CUDACONTRIB
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#include <opencv2/cudawarping.hpp>
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@@ -59,8 +59,6 @@ public:
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tk::dnn::writeBUF(buf, c);
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tk::dnn::writeBUF(buf, h);
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tk::dnn::writeBUF(buf, w);
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std::cout << "Upsample Serialization SIze" << getSerializationSize() << std::endl;
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assert(buf == a + getSerializationSize());
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}
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@@ -120,7 +120,6 @@ public:
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tk::dnn::writeBUF(buf, tmp[j]);
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}
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}
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std::cout << getSerializationSize() << std::endl;
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assert(buf == a + getSerializationSize());
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}
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@@ -24,7 +24,7 @@ file1 = open(".\\..\\demo\\all_labels.txt","a")
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path1 = os.path.realpath(labelFolder)
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for file in os.listdir(labelFolder):
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valTemp = path1 + "\\" + file
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valTemp = valTemp + " \n"
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valTemp = valTemp + '\n'
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file1.write(valTemp)
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file1.close()
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@@ -32,7 +32,7 @@ file2 = open(".\\..\\demo\\all_images.txt","a")
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path2 = os.path.realpath(imageFolder)
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for file in os.listdir(imageFolder):
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pathtemp = path2 + "\\" + file
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pathtemp = pathtemp + " \n"
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pathtemp = pathtemp + '\n'
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file2.write(pathtemp)
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file2.close()
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+1
-1
@@ -648,7 +648,7 @@ IPlugin* PluginFactory::createPlugin(const char* layerName, const void* serialDa
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const char * buf = reinterpret_cast<const char*>(serialData),*bufCheck = buf;
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std::string name(layerName);
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std::cout<<name<<std::endl;
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//std::cout<<name<<std::endl;
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if(name.find("ActivationLeaky") == 0) {
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ActivationLeakyRT *a = new ActivationLeakyRT();
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