Initial Commit: TODO 0

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

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# */AIPND-revision/intropyproject-classify-pet-images/classify_images.py
+#                                                                             
+# PROGRAMMER: 
+# DATE CREATED:                                 
+# REVISED DATE: 
+# PURPOSE: Create a function classify_images that uses the classifier function 
+#          to create the classifier labels and then compares the classifier 
+#          labels to the pet image labels. This function inputs:
+#            -The Image Folder as image_dir within classify_images and function 
+#             and as in_arg.dir for function call within main. 
+#            -The results dictionary as results_dic within classify_images 
+#             function and results for the functin call within main.
+#            -The CNN model architecture as model wihtin classify_images function
+#             and in_arg.arch for the function call within main. 
+#           This function uses the extend function to add items to the list 
+#           that's the 'value' of the results dictionary. You will be adding the
+#           classifier label as the item at index 1 of the list and the comparison 
+#           of the pet and classifier labels as the item at index 2 of the list.
+#
+##
+# Imports classifier function for using CNN to classify images 
+from classifier import classifier 
+
+# TODO 3: Define classify_images function below, specifically replace the None
+#       below by the function definition of the classify_images function. 
+#       Notice that this function doesn't return anything because the 
+#       results_dic dictionary that is passed into the function is a mutable 
+#       data type so no return is needed.
+# 
+def classify_images(images_dir, results_dic, model):
+    """
+    Creates classifier labels with classifier function, compares pet labels to 
+    the classifier labels, and adds the classifier label and the comparison of 
+    the labels to the results dictionary using the extend function. Be sure to
+    format the classifier labels so that they will match your pet image labels.
+    The format will include putting the classifier labels in all lower case 
+    letters and strip the leading and trailing whitespace characters from them.
+    For example, the Classifier function returns = 'Maltese dog, Maltese terrier, Maltese' 
+    so the classifier label = 'maltese dog, maltese terrier, maltese'.
+    Recall that dog names from the classifier function can be a string of dog 
+    names separated by commas when a particular breed of dog has multiple dog 
+    names associated with that breed. For example, you will find pet images of
+    a 'dalmatian'(pet label) and it will match to the classifier label 
+    'dalmatian, coach dog, carriage dog' if the classifier function correctly 
+    classified the pet images of dalmatians.
+     PLEASE NOTE: This function uses the classifier() function defined in 
+     classifier.py within this function. The proper use of this function is
+     in test_classifier.py Please refer to this program prior to using the 
+     classifier() function to classify images within this function 
+     Parameters: 
+      images_dir - The (full) path to the folder of images that are to be
+                   classified by the classifier function (string)
+      results_dic - Results Dictionary with 'key' as image filename and 'value'
+                    as a List. Where the list will contain the following items: 
+                  index 0 = pet image label (string)
+                --- where index 1 & index 2 are added by this function ---
+                  NEW - index 1 = classifier label (string)
+                  NEW - index 2 = 1/0 (int)  where 1 = match between pet image
+                    and classifer labels and 0 = no match between labels
+      model - Indicates which CNN model architecture will be used by the 
+              classifier function to classify the pet images,
+              values must be either: resnet alexnet vgg (string)
+     Returns:
+           None - results_dic is mutable data type so no return needed.         
+    """
+    None