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Classify-Images-Project-1

In this project I use a created image classifier to identify dog breeds. Some images are not dog breeds but other pets. I need to use an already developed Python classifier to make sure the participants are dogs.

Notes: For this image classification project I will be using an image classification application using a deep learning model called a convolutional neural network (often abbreviated as CNN). CNNs work particularly well for detecting features in images like colors, textures, and edges; then using these features to identify objects in the images. I'll use a CNN that has already learned the features from a giant dataset of 1.2 million images called ImageNet. There are different types of CNNs that have different structures (architectures) that work better or worse depending on your criteria. With this project I'll explore the three different architectures (AlexNet, VGG, and ResNet) and determine which is best for my application.

A classifier function in classifier.py was provided which will allow me to use these CNNs to classify my images. The test_classifier.py file contains an example program that demonstrates how to use the classifier function.

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