From 408bde78ffd5c9512ee09adcd2faba21c875d676 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Fri, 13 Apr 2018 14:32:10 +0000
Subject: [PATCH] Fixed darknet.py for Linux

---
 README.md |    6 ++++--
 1 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 55c36a5..fa2809b 100644
--- a/README.md
+++ b/README.md
@@ -46,7 +46,7 @@
 * **OpenCV 3.4.0**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.4.0/opencv-3.4.0-vc14_vc15.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
+* **GPU with CC >= 3.0**: https://en.wikipedia.org/wiki/CUDA#GPUs_supported
 
 ##### Pre-trained models for different cfg-files can be downloaded from (smaller -> faster & lower quality):
 * `yolov3.cfg` (236 MB COCO **Yolo v3**) - require 4 GB GPU-RAM: https://pjreddie.com/media/files/yolov3.weights
@@ -167,7 +167,7 @@
 
 `C:\opencv_3.0\opencv\build\include;..\..\3rdparty\include;%(AdditionalIncludeDirectories);$(CudaToolkitIncludeDir);$(cudnn)\include`
 - (right click on project) -> Build dependecies -> Build Customizations -> set check on CUDA 9.1 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 `\src`
+- add to project all `.c` & `.cu` files and file `http_stream.cpp` from `\src`
 - (right click on project) -> properties  -> Linker -> General -> Additional Library Directories, put here: 
 
 `C:\opencv_3.0\opencv\build\x64\vc14\lib;$(CUDA_PATH)lib\$(PlatformName);$(cudnn)\lib\x64;%(AdditionalLibraryDirectories)`
@@ -216,6 +216,8 @@
 
 More information about training by the link: http://pjreddie.com/darknet/yolo/#train-voc
 
+ **Note:** If during training you see `nan` values in some lines then training goes well, but if `nan` are in all lines then training goes wrong.
+
 ## How to train with multi-GPU:
 
 1. Train it first on 1 GPU for like 1000 iterations: `darknet.exe detector train data/voc.data cfg/yolov3-voc.cfg darknet53.conv.74`

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