diff --git a/head_pose.py b/head_pose.py
index 69c23ef..60c257b 100644
--- a/head_pose.py
+++ b/head_pose.py
@@ -13,6 +13,7 @@ import seaborn as sns
  
 from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
 from matplotlib.figure import Figure
+from matplotlib import cm
 import sys
 if sys.version_info[0] < 3:
     import Tkinter as Tk
@@ -38,7 +39,7 @@ screenDrawCorners = np.array([[10,60], [90, 60], [10, 110], [90, 110]])
 # metrics matrix
 metricsSize = [1920,1080]
 dataframe = pd.DataFrame(columns=['x','y'])
-metrics = np.zeros(metricsSize)
+metrics = np.zeros((metricsSize[1], metricsSize[0])) # (y, x)
 screenDrawCorners = np.array([[0,0], [1919,0], [0, 1079], [1919,1079]])
 
 def create_perspective_transform_matrix(src, dst):
@@ -337,7 +338,7 @@ while True:
         tm4 = 0
     else:
         tm1 = time.time()
-        newMetrics = np.zeros(metricsSize)
+        newMetrics = np.zeros((metricsSize[1], metricsSize[0]))
         tm2 = time.time()
         for point in currentPoints:
             # check if within coordinates:
@@ -355,9 +356,9 @@ while True:
             targetInt = (int(targetPoint[0]), int(targetPoint[1]))
             # check if point fits on screen:
             # if so, measure it
-            if targetInt[0] >= 0 and targetInt[1] >= 0 and targetInt[0] < metricsSize[0] and targetInt[1] < metricsSize[1]:
+            if targetInt[0] >= 0 and targetInt[1] >= 0 and targetInt[0] < metricsSize[1] and targetInt[1] < metricsSize[0]:
                 dataframe = dataframe.append({'x':targetInt[0],'y':targetInt[1]}, ignore_index=True)
-                newMetrics[targetInt[0],targetInt[1]] += 1
+                newMetrics[targetInt[1],targetInt[0]] += 1
         # after we collected all new metrics, blur them foor smoothness
         # and add to all metrics collected
         tm3 = time.time()
@@ -377,7 +378,9 @@ while True:
 
     # update the heatmap output
     tm21 = time.time()
-    normalisedMetrics = metrics / (np.max(metrics)/255)
+    normalisedMetrics = metrics / (np.max(metrics))
+    # convert to colormap, thanks to: https://stackoverflow.com/a/10967471
+    normalisedMetrics = np.uint8(cm.plasma(normalisedMetrics)*255)
     tm22 = time.time()
     logger.debug("Max normalised metrics: %f", np.max(normalisedMetrics))
     # print(normalisedMetrics)
@@ -397,7 +400,7 @@ while True:
     te4 = time.time()
     axes.clear()
     if(len(dataframe) > 2):
-        g = sns.kdeplot(dataframe['x'], dataframe['y'],ax=axes, n_levels=30, shade=True, cmap="rainbow")
+        g = sns.kdeplot(dataframe['x'], dataframe['y'],ax=axes, n_levels=30, shade=True, cmap=cm.rainbow)
     canvas.draw()
     windowRoot.update()
     te5 = time.time()