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print_results.py
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print_results.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# */AIPND-revision/intropyproject-classify-pet-images/print_results.py
#
# PROGRAMMER: Chetas Pahuja
# DATE CREATED:23/08/2022
# 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\n*** Results Summary for CNN Model Architecture",model.upper(),"***")
print("MODEL USED : ", model)
print("NUMBER OF IMAGES : ", results_stats_dic['n_images'])
print("NUMBER OF DOG IMAGES : ", results_stats_dic['n_dogs_img'])
print("NUMBER OF NOT-DOG IMAGES : ", results_stats_dic['n_notdogs_img'])
for key in results_stats_dic:
if key[0] == 'p' :
print('{}: {}'.format(key, results_stats_dic[key]))
if print_incorrect_dogs == True and (results_stats_dic['n_correct_dogs'] + results_stats_dic['n_correct_notdogs'] != results_stats_dic['n_images']):
for key in results_dic:
if sum(results_dic[key][3:]) == 1:
print('\nINCORRECT DOGS: \n PET-IMAGE-LABEL :{} \n CLASSIFIER-LABEL : {}'.format(results_dic[key][0], results_dic[key][1]))
if print_incorrect_breed == True and (results_stats_dic['n_correct_dogs'] != results_stats_dic['n_correct_breed']) :
for key in results_dic:
if sum(results_dic[key][3:]) == 2 and results_dic[key][2] == 0:
print('\n INCORRECT BREEDS: \n PET IMAGE LABEL : {} \n CLASSIFIER LABEL : {}'.format(results_dic[key][0], results_dic[key][1]))
None