Docs

YoloOneTouch/README.md

@@ -3,24 +3,24 @@
 
 Tested on Ubuntu 16.04LTS, Python3  - @Bitsoko
 
-1.Data preparation to yolo format
-2.Yolo config files auto editing and generation (yolo cfg, obj.data , obj.names)
-3.Automatic training launch
-4.Automatic classes determination
-5.Automatoc pre-trained weights download if not present
-6.Yolo installation check
+1.Data preparation to yolo format <br>
+2.Yolo config files auto editing and generation (yolo cfg, obj.data , obj.names) <br>
+3.Automatic training launch<br>
+4.Automatic classes determination<br>
+5.Automatoc pre-trained weights download if not present<br>
+6.Yolo installation check<br>
 
-YoloOneTouch, lets you focus on the data ONLY using labelImg! It does the rest!
+YoloOneTouch, lets you focus on the data ONLY using labelImg! It does the rest!<br>
 
 #DEPENDS ON:
 
--yolo cfg starter file - will be modified automatically - already provided in this repo
--Data set folder as generated by labelimg - https://github.com/tzutalin/labelImg
--require darknet yolo model installation
-		-$git clone https://github.com/pjreddie/darknet
-		-$cd darknet
-		-$make
-		$pwd
+-yolo cfg starter file - will be modified automatically - already provided in this repo<br>
+-Data set folder as generated by labelimg - https://github.com/tzutalin/labelImg<br>
+-require darknet yolo model installation<br>
+		-$git clone https://github.com/pjreddie/darknet<br>
+		-$cd darknet<br>
+		-$make<br>
+		$pwd<br>
 
 Getting started with yolo model can be a painful experience
 Especially in data preparation as yolo expects data in a certain format