minor adjustments

Report_Klaudia_Przybylska.md

@@ -7,6 +7,8 @@ The program uses Random Forest Classifier to recognize five types of rubbish:
 * metal
 * paper
 * plastic
+
+
 Before running the program it is obligatory to unpack "Garbage classifier.rar" and "ClassificationGarbage.rar".
 ## Extracting information from images
 In order to use Random Forest Classifier to classify pictures, I used three global feature descriptors:
@@ -38,14 +40,14 @@ def haralick(image):
 ```
 allFeatures = np.hstack([histo, hara, huMoments])
 ```
-##Creating test and training sets
+## Creating test and training sets
 Data is divided between two sets, where training set contains 80% of all data and test set only 20%. Images are randomly shuffled.
 ```
 allFileNames = os.listdir(sourceDir)
 np.random.shuffle(allFileNames)
 trainingFileNames, testFileNames = np.split(np.array(allFileNames), [int(len(allFileNames) * (1 - testRatio))])
 ```
-##Implementation
+## Implementation
 Functions in garbageDumpSorting.py:
 * createSets - divides images between test and training set. This function should be run only once, unless the folders with training and test set are removed,
 ```
@@ -66,10 +68,10 @@ prediction = clf.predict(features)[0]
 ```
 * sortDump - checks what kinds of trash are inside the garbage truck and their quantity, empties the garbage truck and sorts its contents on the garbage dump.
 
-##Changes in common part
+## Changes in common part
 I created class garbageDump in which I store information about the quantity of trash present on the garbage dump. I had to add a small function to Garbagetruck class in order to remove wastes from the garbage truck. In main I initialize garbage dump and at the end I display its contents.
 
-##Libraries
+## Libraries
 The following libraries are required to run the program:
 ```
 import os