description update

README.md

@@ -1,5 +1,9 @@
+##Description
+
 The goal of this project is to estimate air polution in the city by utilising machine learning technique. It uses images from public surveillence cameras as an input, learns to identify the cars and counts the number of cars in a given image.
 
+##How to use it
+
 img/collect.sh script stores images from surveillence cameras. I use crontab to call this script every minute.
 
 test directory is used to train algorithm to recognize the cars. First of all, copy a set of images from img directory into test directory and run a script test/slide.sh This script will select all jpg images in test directory, it will create test/out directory, where it will save converted jpg images. In the next step, the script will select image by image from test/out directory and it will slice into 100x100 images each. 
@@ -10,4 +14,5 @@ To have cross validation data, copy unseen images from img directory to crossval
 
 Now you are ready to run carRecognition.R script
 
-If you have problems or questions - please contact me at twitter @dzidorius
+##Contact
+If you have problems or questions - please contact me at twitter [@dzidorius](twitter.com/dzidorius) or by [mail](https://github.com/kafka399)

carRecognition.R

@@ -46,4 +46,4 @@ pred=predict(forest,cross,decision.values=TRUE)
 
 ###############copy positives into result directory###############
 dir.create('result')
-file.copy(paste('crossval/out/slide/',files[which(as.double(pred)>0.6)],sep=''),'result/')
+file.copy(paste('crossval/out/slide/',files[which(as.double(pred)>0.75)],sep=''),'result/')