From 6e0d293aa608d100b9695aee490ff828ec0c90cd Mon Sep 17 00:00:00 2001 From: Edmond Yoo <hj3yoo@uwaterloo.ca> Date: Thu, 06 Sep 2018 16:52:14 +0000 Subject: [PATCH] Resetting README --- README.md | 93 +--------------------------------------------- 1 files changed, 2 insertions(+), 91 deletions(-) diff --git a/README.md b/README.md index 90cecd0..8d0c8a0 100644 --- a/README.md +++ b/README.md @@ -1,93 +1,4 @@ - +# Magic: The Gathering Card Detection Model -# Yolo-Windows v2 -# "You Only Look Once: Unified, Real-Time Object Detection (version 2)" -A yolo windows version (for object detection) - -Contributtors: https://github.com/pjreddie/darknet/graphs/contributors - -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 - -##### Example of usage in cmd-files: - -* `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) - -##### 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.cfg yolo.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0 -``` - -### 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 `yolo-windows\build\darknet\darknet.sln` and do the: Build -> Build darknet - -2. If you have other version of CUDA (not 8.0) then open `darknet\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 - +This is a fork of [Yolo-v3 and Yolo-v2 for Windows and Linux by AlexeyAB](https://github.com/AlexeyAB/darknet#how-to-compile-on-linux) for creating a custom model for [My MTG card detection project](https://github.com/hj3yoo/MTGCardDetector). -- Gitblit v1.10.0