Mangaka Drawing Style Identication

Important Things

• SlicingWithFaceDetectionAndTextExtraction.py is the last updated file to extract the features.

  input : The mangas from 109Manga data set

  It produces :

    1- features.csv (List of features)
  
    2- mangaNames.csv (List of corresponding Manga names)
  

• MachineLearningReduced.py is the last updated file for machine learning.

  input :

    1- features.csv (List of features)
  
    2- mangaNames.csv (List of corresponding Manga names)
  

  output :

    - predicted.csv 
  
    	C1 : Manga Name
  
    	C2 : The first predicted Manga
  
    	C3 : The Second predicted Manga
  
    	C4 : The Third predicted Manga
  

• visualization.py is the last updated file for visualizing each feature.

  input :

    1- features.csv (List of features)
  
    2- mangaNames.csv (List of corresponding Manga names)
  

  output :

    - Plots, Change FeatureIndex (Value from 0 -> N) to plot each feature.
  

• Colleration.py is the last updated file for finding colleration for each feature.

  input :

    1- features.csv (List of features)
  
    2- mangaNames.csv (List of corresponding Manga names)
  

  output :

    - Collaration.csv (List of colleration value per feature).
  
    - CollarationMargin80%.csv (All features that have 80% colleration or more).
  

Machine Learning - Final

1- Machine Learning Neural (Neural network solution)
2- Output : predictedFinal (The best we could get ^_^)

Taken Features

1-  Feature_Page_Average_Area_To_Rectangle_Ratio.
2-  Feature_Page_Average_Slope.
3-  Feature_Page_Average_Canny_Lines.
4-  Feature_SceneCanny_Average_Pixels.
5-  Feature_Tone_Average_Pixels.
6-  Feature_Outlines_To_Tones_Pixels_Ratio.
7-  Density per unit area deviation.
8-  Density per unit area.
9-  FaceCanny (Vectors Pixels) Pixels per unit area.
10- Feature_FaceTone_Pixels.
11- Ratio FaceCanny / Face Tone.
12- numberOfGradientColorsInFaces.
13- numberOfGradientColorsInScenes.