- Load dataset containing jpgs and their xmls,
- Create dataset mirrored copy,
- Translate xml files to txt files which are understanded by darknet
- Use
labelImg
software to create labels for dataset - Use
Vi Tools
App ->Mirror IMGs
function to create mirror of your dataset - Use
Vi Tools
App ->Create TXT files
function to translate xmls to txt for darknet
App supports:
- Asynchronus programming
Colorful
status presentation- Mvvm
<annotation>
<folder>folder</folder>
<filename>file name</filename>
<path>jpg path</path>
<source>
<database>Unknown</database>
</source>
<size>
<width>864</width>
<height>1159</height>
<depth>1</depth>
</size>
<segmented>0</segmented>
<object>
<name>class name</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>intiger</xmin>
<ymin>intiger</ymin>
<xmax>intiger</xmax>
<ymax>intiger</ymax>
</bndbox>
</object>
</annotation>
[class numer] [Left] [Top] [Width] [Height]
Class numbers are intigers, first one has number '0'. All values are independent from resolution and are given in percents. 0.52502 means that obiect is located in 52,502% of images height.
1 0.52502 0.46065 0.09259 0.68766
Worth mentioning that next labels will apear in next rows. Their amount is corresponding to 'object' elements in xml file. Like so:
1 0.52502 0.46065 0.09259 0.68766
1 0.52502 0.46065 0.09259 0.68766
1 0.52502 0.46065 0.09259 0.68766
And so on.