From 198b4287f722a7dc7894b2ba5e96312ee6d81e35 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Sun, 08 Apr 2018 21:54:41 +0000
Subject: [PATCH] Update Readme.md

---
 README.md |    4 +++-
 1 files changed, 3 insertions(+), 1 deletions(-)

diff --git a/README.md b/README.md
index 55c36a5..0e81cfd 100644
--- a/README.md
+++ b/README.md
@@ -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`, `.cpp` & `.cu` files 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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