From b7a6dffd3e213541ac9ac654dfa0b6395f326a47 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Fri, 06 Jul 2018 18:58:35 +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 a52aafa..f980b9d 100644
--- a/README.md
+++ b/README.md
@@ -128,7 +128,7 @@
 * `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. Or you can try to run so `LD_LIBRARY_PATH=./:$LD_LIBRARY_PATH ./uselib test.mp4` How to use this SO-library from your own code - you can look at C++ example: https://github.com/AlexeyAB/darknet/blob/master/src/yolo_console_dll.cpp
-
+    or use in such a way: `LD_LIBRARY_PATH=./:$LD_LIBRARY_PATH ./uselib data/coco.names cfg/yolov3.cfg yolov3.weights test.mp4`
 
 ### How to compile on Windows:
 
@@ -324,6 +324,8 @@
  
  **Note:** After training use such command for detection: `darknet.exe detector test data/obj.data yolo-obj.cfg yolo-obj_8000.weights`
  
+  **Note:** if error `Out of memory` occurs then in `.cfg`-file you should increase `subdivisions=16`, 32 or 64: [link](https://github.com/AlexeyAB/darknet/blob/0039fd26786ab5f71d5af725fc18b3f521e7acfd/cfg/yolov3.cfg#L4)
+ 
 ### How to train tiny-yolo (to detect your custom objects):
 
 Do all the same steps as for the full yolo model as described above. With the exception of:

--
Gitblit v1.10.0