AI-For-Beginners/translations/en/lessons/4-ComputerVision/07-ConvNets/lab

Classification of Pets Faces

Lab Assignment from AI for Beginners Curriculum.

Task

Imagine you need to develop an application for a pet nursery to catalog all pets. One of the great features of such an application would be automatically identifying the breed from a photograph. This can be successfully achieved using neural networks.

Your task is to train a convolutional neural network to classify different breeds of cats and dogs using the Pet Faces dataset.

The Dataset

We will use the Oxford-IIIT Pet Dataset, which contains images of 37 different breeds of dogs and cats.

To download the dataset, use this code snippet:

!wget https://thor.robots.ox.ac.uk/~vgg/data/pets/images.tar.gz
!tar xfz images.tar.gz
!rm images.tar.gz

Note: The Oxford-IIIT Pet Dataset images are organized by filename (e.g., Abyssinian_1.jpg, Bengal_2.jpg). The notebook includes code to organize these images into breed-specific subdirectories for easier classification.

Starting Notebook

Begin the lab by opening PetFaces.ipynb

Takeaway

You have tackled a relatively complex problem of image classification from scratch! Despite the large number of classes, you were able to achieve reasonable accuracy! It’s also a good idea to measure top-k accuracy, as some classes can be easily confused, even by humans, due to their similarities.

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