"""

#!/usr/bin/env python3

# -*- coding: utf-8 -*-

# */AIPND-revision/intropyproject-classify-pet-images/check_images.py

#

# TODO 0: Add your information below for Programmer & Date Created.

# PROGRAMMER: Lars Krüger

# DATE CREATED: 14.04.2020

# REVISED DATE:

# PURPOSE: Classifies pet images using a pretrained CNN model, compares these

# classifications to the true identity of the pets in the images, and

# summarizes how well the CNN performed on the image classification task.

# Note that the true identity of the pet (or object) in the image is

# indicated by the filename of the image. Therefore, your program must

# first extract the pet image label from the filename before

# classifying the images using the pretrained CNN model. With this

# program we will be comparing the performance of 3 different CNN model

# architectures to determine which provides the 'best' classification.

#

# Use argparse Expected Call with <> indicating expected user input:

# python check_images.py --dir <directory with images> --arch <model>

# --dogfile <file that contains dognames>

# Example call:

# python check_images.py --dir pet_images/ --arch vgg --dogfile dognames.txt

#

"""

# Imports python modules

import time

# Imports print functions that check the lab

from print_functions_for_lab_checks import *

# Imports functions created for this program

from get_input_args import get_input_args

from get_pet_labels import get_pet_labels

from classify_images import classify_images

from adjust_results4_isadog import adjust_results4_isadog

from calculates_results_stats import calculates_results_stats

from print_results import print_results

# Main program function defined below

def main():

# Dictionary - called results_stats

# results_stats = calculates_results_stats(results)

# Function that checks Results Statistics Dictionary using results_stats

#check_calculating_results(results, results_stats)

# TODO 6: Define print_results function within the file print_results.py

# Once the print_results function has been defined replace 'None'

# in the function call with in_arg.arch Once you have done the

# replacements your function call should look like this:

# print_results(results, results_stats, in_arg.arch, True, True)

# Prints summary results, incorrect classifications of dogs (if requested)

# and incorrectly classified breeds (if requested)

# print_results(results, results_stats, None, True, True)

# Call to main function to run the program

if __name__ == "__main__":

main()