From 82f630cac763a168b67d3d51e60eb860e2aa26de Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Sat, 17 Feb 2018 23:31:56 +0000
Subject: [PATCH] Added param -http_port 8090 to show MJPEG-stream in the WebBrowser (Chrome/Firefox)

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

diff --git a/README.md b/README.md
index 692fb44..ebe9a1a 100644
--- a/README.md
+++ b/README.md
@@ -272,7 +272,7 @@
 
 8. Start training by using the command line: `darknet.exe detector train data/obj.data yolo-obj.cfg darknet19_448.conv.23`
 
-    (file `yolo-obj_xxx.weights` will be saved to the `build\darknet\x64\backup\` for each 100 iterations until 1000 iterations has been reached, and after for each 1000 iterations)
+    (file `yolo-obj_xxx.weights` will be saved to the `build\darknet\x64\backup\` for each 100 iterations)
 
 9. After training is complete - get result `yolo-obj_final.weights` from path `build\darknet\x64\backup\`
 
@@ -341,6 +341,8 @@
   
   * desirable that your training dataset include images with objects at diffrent: scales, rotations, lightings, from different sides
 
+  * for training on small objects, add the parameter `small_object=1` in the last layer [region] in your cfg-file
+
 2. After training - for detection:
 
   * Increase network-resolution by set in your `.cfg`-file (`height=608` and `width=608`) or (`height=832` and `width=832`) or (any value multiple of 32) - this increases the precision and makes it possible to detect small objects: [link](https://github.com/AlexeyAB/darknet/blob/master/cfg/yolo-voc.2.0.cfg#L4)

--
Gitblit v1.10.0