mirror of https://github.com/AlexeyAB/darknet.git
added cmake build instructions and reorganized some install instructions
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README.md
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README.md
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@ -18,9 +18,12 @@ More details: http://pjreddie.com/darknet/yolo/
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0. [Improvements in this repository](#improvements-in-this-repository)
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1. [How to use](#how-to-use-on-the-command-line)
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2. [How to compile on Linux](#how-to-compile-on-linux)
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2. How to compile on Linux
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* [Using cmake](#how-to-compile-on-linux-using-cmake)
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* [Using make](#how-to-compile-on-linux-using-make)
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3. How to compile on Windows
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* [Using vcpkg](#how-to-compile-on-windows-using-vcpkg)
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* [Using Cmake-GUI](#how-to-compile-on-windows-using-Cmake-GUI)
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* [Legacy way](#how-to-compile-on-windows-legacy-way)
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4. [How to train (Pascal VOC Data)](#how-to-train-pascal-voc-data)
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5. [How to train with multi-GPU:](#how-to-train-with-multi-gpu)
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@ -50,10 +53,6 @@ More details: http://pjreddie.com/darknet/yolo/
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* **GPU with CC >= 3.0**: https://en.wikipedia.org/wiki/CUDA#GPUs_supported
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* on Linux **GCC or Clang**, on Windows **MSVC 2015/2017/2019** https://visualstudio.microsoft.com/thank-you-downloading-visual-studio/?sku=Community
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Compiling on **Windows** by using `Cmake-GUI` as on this [**IMAGE**](https://user-images.githubusercontent.com/4096485/55107892-6becf380-50e3-11e9-9a0a-556a943c429a.png): Configure -> Optional platform for generator (Set: x64) -> Finish -> Generate -> Open Project -> x64 & Release -> Build -> Build solution
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Compiling on **Linux** by using command `make` (or alternative way by using command: `cmake . && make` )
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#### Pre-trained models
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There are weights-file for different cfg-files (smaller size -> faster speed & lower accuracy:
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@ -154,7 +153,23 @@ On Linux find executable file `./darknet` in the root directory, while on Window
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* Yolo v3 COCO-model: `darknet.exe detector demo data/coco.data yolov3.cfg yolov3.weights http://192.168.0.80:8080/video?dummy=param.mjpg -i 0`
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### How to compile on Linux
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### How to compile on Linux (using `cmake`)
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The `CMakeLists.txt` will attempt to find installed optional dependencies like
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CUDA, cudnn, ZED and build against those. It will also create a shared object
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library file to use `darknet` for code development.
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Inside the cloned repository:
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```
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mkdir build-release
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cd build-release
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cmake ..
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make
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make install
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```
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### How to compile on Linux (using `make`)
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Just do `make` in the darknet directory.
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Before make, you can set such options in the `Makefile`: [link](https://github.com/AlexeyAB/darknet/blob/9c1b9a2cf6363546c152251be578a21f3c3caec6/Makefile#L1)
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@ -201,6 +216,19 @@ PS Code\vcpkg> .\vcpkg install pthreads opencv[ffmpeg] #replace with ope
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9. Open Powershell, go to the `darknet` folder and build with the command `.\build.ps1`. If you want to use Visual Studio, you will find two custom solutions created for you by CMake after the build, one in `build_win_debug` and the other in `build_win_release`, containing all the appropriate config flags for your system.
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### How to compile on Windows (using `Cmake-GUI`)
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Using `Cmake-GUI` as shown here on this [**IMAGE**](https://user-images.githubusercontent.com/4096485/55107892-6becf380-50e3-11e9-9a0a-556a943c429a.png):
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1. Configure
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2. Optional platform for generator (Set: x64)
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3. Finish
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4. Generate
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5. Open Project
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6. x64 & Release
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7. Build
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8. Build solution
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### How to compile on Windows (legacy way)
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1. If you have **CUDA 10.0, cuDNN 7.4 and OpenCV 3.x** (with paths: `C:\opencv_3.0\opencv\build\include` & `C:\opencv_3.0\opencv\build\x64\vc14\lib`), then open `build\darknet\darknet.sln`, set **x64** and **Release** https://hsto.org/webt/uh/fk/-e/uhfk-eb0q-hwd9hsxhrikbokd6u.jpeg and do the: Build -> Build darknet. Also add Windows system variable `CUDNN` with path to CUDNN: https://user-images.githubusercontent.com/4096485/53249764-019ef880-36ca-11e9-8ffe-d9cf47e7e462.jpg
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@ -596,8 +624,12 @@ With example of: `train.txt`, `obj.names`, `obj.data`, `yolo-obj.cfg`, `air`1-6`
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## How to use Yolo as DLL and SO libraries
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* on Linux - set `LIBSO=1` in the `Makefile` and do `make`
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* on Windows - compile `build\darknet\yolo_cpp_dll.sln` or `build\darknet\yolo_cpp_dll_no_gpu.sln` solution
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* on Linux
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* build `darknet` using `cmake` or
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* set `LIBSO=1` in the `Makefile` and do `make`
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* on Windows
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* compile `build\darknet\yolo_cpp_dll.sln` solution or
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* compile `build\darknet\yolo_cpp_dll_no_gpu.sln` solution
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There are 2 APIs:
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* C API: https://github.com/AlexeyAB/darknet/blob/master/include/darknet.h
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