diff --git a/pysegcnn/core/graphics.py b/pysegcnn/core/graphics.py
index 39321e54d0564cfdb8259a2bd0d3d028e6838c2f..0130baca096206b13e57756a6bcfc76c0a6303d5 100644
--- a/pysegcnn/core/graphics.py
+++ b/pysegcnn/core/graphics.py
@@ -345,7 +345,7 @@ def plot_sample(x, use_bands, labels,
 
 
 def plot_confusion_matrix(cm, labels, normalize=True, figsize=(10, 10),
-                          cmap='Blues', state_file=None, subset=None,
+                          cmap='viridis', state_file=None, subset=None,
                           outpath=os.path.join(HERE, '_graphics/')):
     """Plot the confusion matrix ``cm``.
 
@@ -360,7 +360,7 @@ def plot_confusion_matrix(cm, labels, normalize=True, figsize=(10, 10),
     figsize : `tuple` [`int`], optional
         The figure size in centimeters. The default is `(10, 10)`.
     cmap : `str`, optional
-        A matplotlib colormap. The default is `'Blues'`.
+        A matplotlib colormap. The default is `'viridis'`.
     state_file : `str` or `None` or :py:class:`pathlib.Path`, optional
         Filename to save the plot to. ``state`` should be an existing model
         state file ending with `'.pt'`. The default is `None`, i.e. the plot is
@@ -683,7 +683,8 @@ def plot_class_distribution(ds, figsize=(16, 9), alpha=0.5):
     return fig
 
 
-def plot_classification_report(report, labels, figsize=(10, 10), **kwargs):
+def plot_classification_report(report, labels, figsize=(10, 10),
+                               cmap='viridis', **kwargs):
     """Plot the :py:func:`sklearn.metrics.classification_report` as heatmap.
 
     Parameters
@@ -697,6 +698,8 @@ def plot_classification_report(report, labels, figsize=(10, 10), **kwargs):
         Names of the classes.
     figsize : `tuple` [`int`], optional
         The figure size in centimeters. The default is `(10, 10)`.
+    cmap : `str`, optional
+        A matplotlib colormap. The default is `'viridis'`.
     **kwargs :
         Additional keyword arguments passed to :py:func:`seaborn.heatmap`.
 
@@ -732,6 +735,14 @@ def plot_classification_report(report, labels, figsize=(10, 10), **kwargs):
     # set figure title
     ax.set_title('Accuracy: {:.2f}'.format(overall_accuracy), pad=20)
 
+    # rotate x-tick labels
+    for label in ax.get_xticklabels():
+        label.set_rotation(90)
+
+    # rotate y-tick labels
+    for label in ax.get_yticklabels():
+        label.set_rotation(0)
+
     return fig