mnist plottting

Author: aamini

mitdeeplearning/lab2.py

@@ -9,6 +9,37 @@
 
 IM_SHAPE = (64, 64, 3)
 
+def plot_image_prediction(i, predictions_array, true_label, img):
+  predictions_array, true_label, img = predictions_array[i], true_label[i], img[i]
+  plt.grid(False)
+  plt.xticks([])
+  plt.yticks([])
+
+  plt.imshow(np.squeeze(img), cmap=plt.cm.binary)
+
+  predicted_label = np.argmax(predictions_array)
+  if predicted_label == true_label:
+    color = 'blue'
+  else:
+    color = 'red'
+
+  plt.xlabel("{} {:2.0f}% ({})".format(predicted_label,
+                                100*np.max(predictions_array),
+                                true_label),
+                                color=color)
+
+def plot_value_prediction(i, predictions_array, true_label):
+  predictions_array, true_label = predictions_array[i], true_label[i]
+  plt.grid(False)
+  plt.xticks([])
+  plt.yticks([])
+  thisplot = plt.bar(range(10), predictions_array, color="#777777")
+  plt.ylim([0, 1])
+  predicted_label = np.argmax(predictions_array)
+
+  thisplot[predicted_label].set_color('red')
+  thisplot[true_label].set_color('blue')
+
 
 class TrainingDatasetLoader(object):
     def __init__(self, data_path):

setup.py

@@ -21,13 +21,13 @@ def get_dist(pkgname):
 setup(
   name = 'mitdeeplearning',         # How you named your package folder (MyLib)
   packages = ['mitdeeplearning'],   # Chose the same as "name"
-  version = '0.3.8',      # Start with a small number and increase it with every change you make
+  version = '0.3.9',      # Start with a small number and increase it with every change you make
   license='MIT',        # Chose a license from here: https://help.github.com/articles/licensing-a-repository
   description = 'Official software labs for MIT Introduction to Deep Learning (http://introtodeeplearning.com)',   # Give a short description about your library
   author = 'Alexander Amini',                   # Type in your name
   author_email = '[email protected]',      # Type in your E-Mail
   url = 'http://introtodeeplearning.com',   # Provide either the link to your github or to your website
-  download_url = 'https://github.com/aamini/introtodeeplearning_labs/archive/v0.3.8.tar.gz',    # I explain this later on
+  download_url = 'https://github.com/aamini/introtodeeplearning_labs/archive/v0.3.9.tar.gz',    # I explain this later on
   keywords = ['deep learning', 'neural networks', 'tensorflow', 'introduction'],   # Keywords that define your package best
   install_requires=install_deps,
   classifiers=[