From 84cdbaa1f14b4f2ca73b370c6db6a4dc9571fd07 Mon Sep 17 00:00:00 2001 From: AlexeyAB <alexeyab84@gmail.com> Date: Sun, 29 Oct 2017 15:34:55 +0000 Subject: [PATCH] Fixed for Linux: detection for batch > 1 and 0x0d at command line --- README.md | 7 +++++-- 1 files changed, 5 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index ac789be..11d8565 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ # Yolo-v2 Windows and Linux version +[](https://circleci.com/gh/AlexeyAB/darknet) + 1. [How to use](#how-to-use) 2. [How to compile on Linux](#how-to-compile-on-linux) 3. [How to compile on Windows](#how-to-compile-on-windows) @@ -38,6 +40,7 @@ * **OpenCV 3.x**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.2.0/opencv-3.2.0-vc14.exe/download * **or OpenCV 2.4.13**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.13/opencv-2.4.13.2-vc14.exe/download - OpenCV allows to show image or video detection in the window and store result to file that specified in command line `-out_filename res.avi` +* **GPU with CC >= 2.0** if you use CUDA, or **GPU CC >= 3.0** if you use cuDNN + CUDA: https://en.wikipedia.org/wiki/CUDA#GPUs_supported ##### Pre-trained models for different cfg-files can be downloaded from (smaller -> faster & lower quality): * `yolo.cfg` (194 MB COCO-model) - require 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo.weights @@ -112,7 +115,7 @@ * `OPENCV=1` to build with OpenCV 3.x/2.4.x - allows to detect on video files and video streams from network cameras or web-cams * `DEBUG=1` to bould debug version of Yolo * `OPENMP=1` to build with OpenMP support to accelerate Yolo by using multi-core CPU -* `LIBSO=1` to build a library `darknet.so` and binary runable file `uselib` that uses this library. How to use this SO-library from your own code - you can look at C++ example: https://github.com/AlexeyAB/darknet/blob/master/src/yolo_console_dll.cpp +* `LIBSO=1` to build a library `darknet.so` and binary runable file `uselib` that uses this library. Or you can try to run so `LD_LIBRARY_PATH=./:$LD_LIBRARY_PATH ./uselib test.mp4` How to use this SO-library from your own code - you can look at C++ example: https://github.com/AlexeyAB/darknet/blob/master/src/yolo_console_dll.cpp ### How to compile on Windows: @@ -201,7 +204,7 @@ 1. Train it first on 1 GPU for like 1000 iterations: `darknet.exe detector train data/voc.data yolo-voc.2.0.cfg darknet19_448.conv.23` -2. Then stop and by using partially-trained model `/backup/yolo-voc_1000.weights` run training with multigpu (up to 4 GPUs): `darknet.exe detector train data/voc.data yolo-voc.2.0.cfg yolo-voc_1000.weights -gpus 0,1,2,3` +2. Then stop and by using partially-trained model `/backup/yolo-voc_1000.weights` run training with multigpu (up to 4 GPUs): `darknet.exe detector train data/voc.data yolo-voc.2.0.cfg /backup/yolo-voc_1000.weights -gpus 0,1,2,3` https://groups.google.com/d/msg/darknet/NbJqonJBTSY/Te5PfIpuCAAJ -- Gitblit v1.10.0