From 30e08573d1c24b93ea01b209917ef91bde392673 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Sun, 06 May 2018 18:31:49 +0000
Subject: [PATCH] Merge pull request #759 from Adesun/log_parser
---
README.md | 4 ++--
1 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index 7634daf..f0549c9 100644
--- a/README.md
+++ b/README.md
@@ -413,12 +413,12 @@
* increase network resolution in your `.cfg`-file (`height=608`, `width=608` or any value multiple of 32) - it will increase precision
* recalculate anchors for your dataset for `width` and `height` from cfg-file:
- `darknet.exe detector calc_anchors data/obj.data -num_of_clusters 9 -width 416 -heigh 416`
+ `darknet.exe detector calc_anchors data/obj.data -num_of_clusters 9 -width 416 -height 416`
then set the same 9 `anchors` in each of 3 `[yolo]`-layers in your cfg-file
* desirable that your training dataset include images with objects at diffrent: scales, rotations, lightings, from different sides, on different backgrounds
- * desirable that your training dataset include images with non-labeled objects that you do not want to detect - negative samples without bounded box
+ * desirable that your training dataset include images with non-labeled objects that you do not want to detect - negative samples without bounded box (empty `.txt` files)
* for training with a large number of objects in each image, add the parameter `max=200` or higher value in the last layer [region] in your cfg-file
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