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ai-programming-with-python/C02P8-pre-trained-image-classifier/test_classifier.py

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# */AIPND/intropylab-classifying-images/test_classifier.py
+#                                                                             
+# PROGRAMMER: Jennifer S.                                                    
+# DATE CREATED: 01/30/2018                                  
+# REVISED DATE:             <=(Date Revised - if any)                         
+# PURPOSE: To demonstrate the proper usage of the classifier() function that 
+#          is defined in classifier.py This function uses CNN model 
+#          architecture that has been pretrained on the ImageNet data to 
+#          classify images. The only model architectures that this function 
+#          will accept are: 'resnet', 'alexnet', and 'vgg'. See the example
+#          usage below.
+#
+# Usage: python test_classifier.py    -- will run program from commandline
+
+# Imports classifier function for using pretrained CNN to classify images 
+from classifier import classifier 
+
+# Defines a dog test image from pet_images folder
+test_image="pet_images/Collie_03797.jpg"
+
+# Defines a model architecture to be used for classification
+# NOTE: this function only works for model architectures: 
+#      'vgg', 'alexnet', 'resnet'  
+model = "vgg"
+
+# Demonstrates classifier() functions usage
+# NOTE: image_classication is a text string - It contains mixed case(both lower
+# and upper case letter) image labels that can be separated by commas when a 
+# label has more than one word that can describe it.
+image_classification = classifier(test_image, model)
+
+# prints result from running classifier() function
+print("\nResults from test_classifier.py\nImage:", test_image, "using model:",
+      model, "was classified as a:", image_classification)