print_results.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# */AIPND-revision/intropyproject-classify-pet-images/print_results.py
#                                                                             
# PROGRAMMER: 
# DATE CREATED:
# REVISED DATE: 
# PURPOSE: Create a function print_results that prints the results statistics
#          from the results statistics dictionary (results_stats_dic). It 
#          should also allow the user to be able to print out cases of misclassified
#          dogs and cases of misclassified breeds of dog using the Results 
#          dictionary (results_dic).  
#         This function inputs:
#            -The results dictionary as results_dic within print_results 
#             function and results for the function call within main.
#            -The results statistics dictionary as results_stats_dic within 
#             print_results function and results_stats for the function call within main.
#            -The CNN model architecture as model wihtin print_results function
#             and in_arg.arch for the function call within main. 
#            -Prints Incorrectly Classified Dogs as print_incorrect_dogs within
#             print_results function and set as either boolean value True or 
#             False in the function call within main (defaults to False)
#            -Prints Incorrectly Classified Breeds as print_incorrect_breed within
#             print_results function and set as either boolean value True or 
#             False in the function call within main (defaults to False)
#         This function does not output anything other than printing a summary
#         of the final results.
##
# TODO 6: Define print_results function below, specifically replace the None
#       below by the function definition of the print_results function. 
#       Notice that this function doesn't to return anything because it  
#       prints a summary of the results using results_dic and results_stats_dic
# 
def print_results(results_dic, results_stats_dic, model, 
                  print_incorrect_dogs = False, print_incorrect_breed = False):
    """
    Prints summary results on the classification and then prints incorrectly 
    classified dogs and incorrectly classified dog breeds if user indicates 
    they want those printouts (use non-default values)
    Parameters:
      results_dic - Dictionary with key as image filename and value as a List 
             (index)idx 0 = pet image label (string)
                    idx 1 = classifier label (string)
                    idx 2 = 1/0 (int)  where 1 = match between pet image and 
                            classifer labels and 0 = no match between labels
                    idx 3 = 1/0 (int)  where 1 = pet image 'is-a' dog and 
                            0 = pet Image 'is-NOT-a' dog. 
                    idx 4 = 1/0 (int)  where 1 = Classifier classifies image 
                            'as-a' dog and 0 = Classifier classifies image  
                            'as-NOT-a' dog.
      results_stats_dic - Dictionary that contains the results statistics (either
                   a  percentage or a count) where the key is the statistic's 
                     name (starting with 'pct' for percentage or 'n' for count)
                     and the value is the statistic's value 
      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)
      print_incorrect_dogs - True prints incorrectly classified dog images and 
                             False doesn't print anything(default) (bool)  
      print_incorrect_breed - True prints incorrectly classified dog breeds and 
                              False doesn't print anything(default) (bool) 
    Returns:
           None - simply printing results.
    """    
    
    print ("\n")
    
    #reiterate through results_stats_dic and display only the statistics 
    for key in results_stats_dic:
        if "pct" in key:
            print (key+": "+str(results_stats_dic[key])) 

    #if print_incorrect_dogs is enabled make sure that there are misclassified dog images at all. This can be done by comparing the sum of correctly classified dogs and not-dogs images with the total number of images     
    if (print_incorrect_dogs and ( (results_stats_dic['n_correct_dogs'] + results_stats_dic['n_correct_notdogs']) != results_stats_dic['n_images'] ) ):
        print("\nINCORRECT Dog/NOT Dog Assignments:")          
        for key in results_dic:
            if results_dic[key][3] != results_dic[key][4]: #a misclassification is existing when classifier's dog label is not matching actual dog label
                print("Real: {}  Classifier: {}".format(results_dic[key][0], results_dic[key][1]))                

    #if print_incorrect_breed is enabled make sure that there are misclassified dog breeds at all. This can be done by comparing the total correctly classified dogs with the total number of total correctly classified dog breeds  
    if (print_incorrect_breed and (results_stats_dic['n_correct_dogs'] != results_stats_dic['n_correct_breed']) ):
        print("\nINCORRECT Dog Breed Assignments:")

        for key in results_dic:
            if ( (results_dic[key][3] + results_dic[key][4]) == 2  and results_dic[key][2] == 0 ): #a misclassification is existing when the pet labels are not matching but the dog labels do
                print("Real: {}   Classifier: {}".format(results_dic[key][0], results_dic[key][1]))