From d8bafc728478e5cba9cf41eca01d66a38800eddd Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Fri, 28 Apr 2017 11:04:56 +0000
Subject: [PATCH] Update Readme.md

---
 README.md |    6 +++---
 1 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 99495d1..85b25d5 100644
--- a/README.md
+++ b/README.md
@@ -187,7 +187,7 @@
 
 ## How to train (to detect your custom objects):
 
-1. Create file `yolo-obj.cfg` with the same content as in `yolo-voc.cfg` (or copy `yolo-voc.cfg` to `yolo-obj.cfg)` and:
+1. Create file `yolo-obj.cfg` with the same content as in `yolo-voc.2.0.cfg` (or copy `yolo-voc.2.0.cfg` to `yolo-obj.cfg)` and:
 
   * change line batch to [`batch=64`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.cfg#L3)
   * change line subdivisions to [`subdivisions=8`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.cfg#L4)
@@ -267,7 +267,7 @@
   * **9002** - iteration number (number of batch)
   * **0.060730 avg** - average loss (error) - **the lower, the better**
 
-  When you see that average loss **0.060730 avg** enough low at many iterations and no longer decreases then you should stop training.
+  When you see that average loss **0.xxxxxx avg** no longer decreases at many iterations then you should stop training.
 
 2. Once training is stopped, you should take some of last `.weights`-files from `darknet\build\darknet\x64\backup` and choose the best of them:
 
@@ -288,7 +288,7 @@
 > 7586 7612 7689 RPs/Img: 68.23 **IOU: 77.86%** Recall:99.00%
 
 * **IOU** - the bigger, the better (says about accuracy) - **better to use**
-* **Recall** - the bigger, the better (says about accuracy)
+* **Recall** - the bigger, the better (says about accuracy) - actually Yolo calculates true positives, so it shouldn't be used
 
 For example, **bigger IUO** gives weights `yolo-obj_8000.weights` - then **use this weights for detection**.
 

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