diff --git a/example.jl b/example.jl
index be3bfb725..4eae2df50 100755
--- a/example.jl
+++ b/example.jl
@@ -16,7 +16,7 @@ include(joinpath("src", "FaceDetection.jl"))
 
 using .FaceDetection
 using Printf: @printf
-using Images: Gray, clamp01nan, save, imresize
+using Images: Gray, clamp01nan, save, imresize, load
 
 
 function main(smartChooseFeats::Bool=false, alt::Bool=false, imageReconstruction::Bool=false, featValidaton::Bool=true)
@@ -93,6 +93,9 @@ function main(smartChooseFeats::Bool=false, alt::Bool=false, imageReconstruction
       
       @printf("%10.9s %10.9s %15s\n", "Faces:", facesFrac, facesPercent)
       @printf("%10.9s %10.9s %15s\n\n", "Non-faces:", nonFacesFrac, nonFacesPercent)
+      
+      randImg = FaceDetection.getRandomImage(posTestingPath, negTestingPath, true)
+      println("For face (or non-face) ", randImg, " we have a face-likeness of ", sum([c.weight * FaceDetection.getVote(c, FaceDetection.toIntegralImage(getImageMatrix(randImg))) for c in classifiers]))
 
       if imageReconstruction
             # Just for fun: putting all Haar-like features over each other generates a face-like image
@@ -115,4 +118,4 @@ end
 
 
 
-@time main(false, false, true, true)
+@time main(false, false, false, false)
diff --git a/src/AdaBoost.jl b/src/AdaBoost.jl
index f0ef262b1..3fd496c9f 100755
--- a/src/AdaBoost.jl
+++ b/src/AdaBoost.jl
@@ -18,7 +18,7 @@ using ProgressMeter: @showprogress
 using .HaarLikeFeature: FeatureTypes, HaarLikeObject, getVote
 using .Utils: notifyUser
 
-export learn #,  _get_feature_vote, _create_features
+export learn,  _get_feature_vote, _create_features
 
 
 function learn(positiveIIs::AbstractArray, negativeIIs::AbstractArray, numClassifiers::Int64=-1, minFeatureWidth::Int64=1, maxFeatureWidth::Int64=-1, minFeatureHeight::Int64=1, maxFeatureHeight::Int64=-1)#::Array{HaarLikeObject,1}
@@ -170,7 +170,7 @@ function _create_features(imgHeight::Int64, imgWidth::Int64, minFeatureWidth::In
         """)
     end
     
-    for feature in HaarLikeFeature.FeatureTypes # from HaarLikeObject.jl (FeatureTypes are just tuples)
+    for feature in HaarLikeFeature.FeatureTypes # (FeatureTypes are just tuples)
         featureStartWidth = max(minFeatureWidth, feature[1])
         for featureWidth in range(featureStartWidth, stop=maxFeatureWidth, step=feature[1])
             featureStartHeight = max(minFeatureHeight, feature[2])
diff --git a/src/FaceDetection.jl b/src/FaceDetection.jl
index 862745772..a1f238486 100755
--- a/src/FaceDetection.jl
+++ b/src/FaceDetection.jl
@@ -14,7 +14,7 @@ include("AdaBoost.jl")
 include("Utils.jl")
 
 using .IntegralImage: toIntegralImage, sumRegion
-using .HaarLikeFeature: FeatureTypes, HaarLikeObject, getScore, getVote
+using .HaarLikeFeature: FeatureTypes, HaarLikeObject, getScore, getVote, getFacelikeness
 using .AdaBoost: learn, _get_feature_vote, _create_features
 using .Utils: displaymatrix, notifyUser, loadImages, getImageMatrix, ensembleVote, ensembleVoteAll, reconstruct, getRandomImage, generateValidationImage
 
diff --git a/src/HaarLikeFeature.jl b/src/HaarLikeFeature.jl
index 51f9a237c..2ba8172d3 100755
--- a/src/HaarLikeFeature.jl
+++ b/src/HaarLikeFeature.jl
@@ -11,7 +11,7 @@ include("IntegralImage.jl")
 
 using .IntegralImage: sumRegion
 
-export FeatureTypes, HaarLikeObject, getScore, getVote
+export FeatureTypes, HaarLikeObject, getScore, getVote, getFacelikeness
 
 
 FeatureTypes = [(1, 2), (2, 1), (3, 1), (1, 3), (2, 2)]
@@ -114,4 +114,32 @@ function getVote(feature, intImg::AbstractArray)#function getVote(feature::HaarL
 end
 
 
+function getFacelikeness(feature, intImg::AbstractArray)
+        #=
+        Get facelikeness for a given feature.
+        
+        parameter `feature`: given Haar-like feature (parameterised replacement of Python's `self`) [type: HaarLikeObject]
+        parameter `intImg`: Integral image array [type: Abstract Array]
+        
+        return `score`: Score for given feature [type: Float]
+        =#
+        
+        score = 0
+
+        if feature.featureType == FeatureTypes[1] # two vertical
+            score = 1
+        elseif feature.featureType == FeatureTypes[2] # two horizontal
+            score = 2
+        elseif feature.featureType == FeatureTypes[3] # three horizontal
+            score = 3
+        elseif feature.featureType == FeatureTypes[4] # three vertical
+            score = 4
+        elseif feature.featureType == FeatureTypes[5] # four
+            score = 5
+        end
+        
+        return score
+end
+
+
 end # end module
diff --git a/src/Utils.jl b/src/Utils.jl
index f8a1da6c7..ff0aab2ee 100755
--- a/src/Utils.jl
+++ b/src/Utils.jl
@@ -199,7 +199,7 @@ function getRandomImage(facePath::AbstractString, nonFacePath::AbstractString=""
         face = rand(Bool)
         fileName = rand(filter!(f -> ! occursin(r".*\.DS_Store", f), readdir(face ? facePath : nonFacePath, join=true)))
         return fileName#, face
-    elseif ! nonFaces
+    else
         fileName = rand(filter!(f -> ! occursin(r".*\.DS_Store", f), readdir(facePath, join=true)))
         return fileName#, face
     end