From 5ae5b2939b29d2894847d313ff8c31aa6fe0d6d3 Mon Sep 17 00:00:00 2001 From: AlexeyAB <alexeyab84@gmail.com> Date: Fri, 02 Dec 2016 18:25:21 +0000 Subject: [PATCH] Merge branch 'master' of github.com:AlexeyAB/darknet --- README.md | 103 +++++++++++++++++++++++++++++++++++++++++++++++++-- 1 files changed, 99 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index d255dab..ff632d5 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,103 @@  -#Darknet# -Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. +# Yolo-Windows v2 +# "You Only Look Once: Unified, Real-Time Object Detection (version 2)" +A yolo windows version (for object detection) -For more information see the [Darknet project website](http://pjreddie.com/darknet). +Contributtors: https://github.com/pjreddie/darknet/graphs/contributors -For questions or issues please use the [Google Group](https://groups.google.com/forum/#!forum/darknet). +This repository is forked from Linux-version: https://github.com/pjreddie/darknet + +More details: http://pjreddie.com/darknet/yolo/ + +##### Requires: +* **MS Visual Studio 2015 (v140)**: https://www.microsoft.com/download/details.aspx?id=48146 +* **CUDA 8.0 for Windows x64**: https://developer.nvidia.com/cuda-downloads +* **OpenCV 2.4.9**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.9/opencv-2.4.9.exe/download + - To compile without OpenCV - remove define OPENCV from: Visual Studio->Project->Properties->C/C++->Preprocessor + - To compile with different OpenCV version - change in file yolo.c each string look like **#pragma comment(lib, "opencv_core249.lib")** from 249 to required version. + - With OpenCV will show image or video detection in window + +##### Pre-trained models for different cfg-files can be downloaded from (smaller -> faster & lower quality): +* `yolo.cfg` (256 MB) - require 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo-voc.weights +* `yolo-tiny.cfg` (60 MB) - require 1 GB GPU-RAM: http://pjreddie.com/media/files/tiny-yolo-voc.weights + +Put it near compiled: darknet.exe + +##### Examples of results: + +[](https://www.youtube.com/watch?v=VOC3huqHrss "Everything Is AWESOME") + +Others: https://www.youtube.com/channel/UC7ev3hNVkx4DzZ3LO19oebg + +### How to use: + +##### Example of usage in cmd-files from `build\darknet\x64\`: + +* `darknet_demo_voc.cmd` - initialization with 256 MB model yolo-voc.weights & yolo-voc.cfg and play your video file which you must rename to: test.mp4 +* `darknet_net_cam_voc.cmd` - initialization with 256 MB model, play video from network video-camera mjpeg-stream (also from you phone) + +How to use from command line with 256 MB model: `darknet.exe yolo demo yolo-voc.cfg yolo-voc.weights test.mp4 -i 0` + +##### For using network video-camera mjpeg-stream with any Android smartphone: + +1. Download for Android phone mjpeg-stream soft: IP Webcam / Smart WebCam + + + Smart WebCam - preferably: https://play.google.com/store/apps/details?id=com.acontech.android.SmartWebCam + IP Webcam: https://play.google.com/store/apps/details?id=com.pas.webcam + +2. Connect your Android phone to computer by WiFi (through a WiFi-router) or USB +3. Start Smart WebCam on your phone +4. Replace the address below, on shown in the phone application (Smart WebCam) and launch: + +``` +darknet.exe yolo demo yolo-voc.cfg yolo-voc.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0 +``` + +##### How to use COCO instead of VOC: + +* Get synset names from `build\darknet\x64\data\coco.names`: https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/data/coco.names +* And change list `char *voc_names[] = ` to COCO-names in file `yolo.c`: https://github.com/AlexeyAB/darknet/blob/master/src/yolo.c#L30 + + +### How to compile: + +1. If you have CUDA 8.0, OpenCV 2.4.9 (C:\opencv_2.4.9) and MSVS 2015 then start MSVS, open `build\darknet\darknet.sln` and do the: Build -> Build darknet + +2. If you have other version of CUDA (not 8.0) then open `build\darknet\darknet.vcxproj` by using Notepad, find 2 places with "CUDA 8.0" and change it to your CUDA-version, then do step 1 + +3. If you have other version of OpenCV 2.4.x (not 2.4.9) then you should change pathes after `\darknet.sln` is opened + + 3.1 (right click on project) -> properties -> C/C++ -> General -> Additional Include Directories + + 3.2 (right click on project) -> properties -> Linker -> General -> Additional Library Directories + +4. If you have other version of OpenCV 3.x (not 2.4.x) then you should change many places in code by yourself. + +### How to compile (custom): + +Also, you can to create your own `darknet.sln` & `darknet.vcxproj`, this example for CUDA 8.0 and OpenCV 2.4.9 + +Then add to your created project: +- (right click on project) -> properties -> C/C++ -> General -> Additional Include Directories, put here: + +`C:\opencv_2.4.9\opencv\build\include;..\..\3rdparty\include;%(AdditionalIncludeDirectories);$(CudaToolkitIncludeDir);$(cudnn)\include` +- right click on project -> Build dependecies -> Build Customizations -> set check on CUDA 8.0 or what version you have - for example as here: http://devblogs.nvidia.com/parallelforall/wp-content/uploads/2015/01/VS2013-R-5.jpg +- add to project all .c & .cu files from yolo-windows\src +- (right click on project) -> properties -> Linker -> General -> Additional Library Directories, put here: + +`C:\opencv_2.4.9\opencv\build\x64\vc12\lib;$(CUDA_PATH)lib\$(PlatformName);$(cudnn)\lib\x64;%(AdditionalLibraryDirectories)` +- (right click on project) -> properties -> Linker -> Input -> Additional dependecies, put here: + +`..\..\3rdparty\lib\x64\pthreadVC2.lib;cublas.lib;curand.lib;cudart.lib;cudnn.lib;%(AdditionalDependencies)` +- (right click on project) -> properties -> C/C++ -> Preprocessor -> Preprocessor Definitions + +`OPENCV;_TIMESPEC_DEFINED;_CRT_SECURE_NO_WARNINGS;GPU;WIN32;NDEBUG;_CONSOLE;_LIB;%(PreprocessorDefinitions)` +- compile to .exe (X64 & Release) and put .dll`s near with .exe: + +`pthreadVC2.dll, pthreadGC2.dll` from yolo-windows\3rdparty\dll\x64 + +`cusolver64_80.dll, curand64_80.dll, cudart64_80.dll, cublas64_80.dll` - 80 for CUDA 8.0 or your version, from C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin + + -- Gitblit v1.10.0