Script uitleg erbij gezet en uitleg hoe ons filemap systeem moet werken voor (nja mijne in elk geval, weet niet welke nog meer) enzo.

docs/report.tex

@@ -351,7 +351,25 @@ it as good as possible because all occurrences are in the learning set.
 \subsection{Supporting Scripts}
 
 To be able to use the code efficiently, we wrote a number of scripts. This
-section describes the purpose and usage of each script.
+section describes the purpose and usage of each script. For each script it is
+essential that you use the correct folder and subfolder naming scheme. The scheme
+is as follows:
+
+\begin{enumerate}
+
+\item A main folder called 'images' placed in the current directory as the src folder.
+\item In the images folder there have to be three folders. Images, Infos and LearningSet.
+\item The Images and Infos folder contain subfolders which are numbered ($0001$ to possibly $9999$).
+\item In each of the subfolders the data (i.e the images or xml files) can be placed.
+And have to be named $00991_XXXXX.ext$, where XXXXX can be $00000 to 99999$.
+\item For loops in the script currently only go up to 9 subfolders, with a maximum
+of containing 100 images or xml files. These numbers have to be adjusted if the scripts 
+are being used, but with a bigger dataset.
+\end{enumerate}
+
+It is ofcourse possible to use your own naming scheme. A search for the $filename$ variable will most
+likely find the occurences where the naming scheme is implemented.
+
 
 \subsection*{\texttt{create\_characters.py}}
 
@@ -367,8 +385,16 @@ section describes the purpose and usage of each script.
 
 \subsection*{\texttt{generate\_learning\_set.py}}
 
-
-
+Usage of this script could be minimal, since you only need to extract the letters carefully
+and succesfully once. Then other scripts in this list can use the extracted images. Most
+likely the other scripts will use caching to speed up the system to. But in short, the script will create images of a single character based on a given dataset
+of license plate images and corresponding xml files. If the xml files give correct
+locations of the characters they can be extracted. The workhorse of this script is
+$plate = xml_to_LicensePlate(filename, save_character=1)$. Where save_character is
+an optional variable. If set it will save the image in the LearningSet folder and
+pick the correct subfolder based on the character value. So if the XML says a character
+is an 'A' it will be placed in the 'A' folder. These folders will be created automatically
+if they do not exist yet.
 \subsection*{\texttt{load\_learning\_set.py}}