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