Who's a good dog? Who likes ear scratches? Well, it seems those fancy deep neural networks don't have all the answers. However, maybe they can answer that ubiquitous question we all ask when meeting a four-legged stranger: what kind of good pup is that?
In this project, we have a strictly canine subset of ImageNet in order to practice fine-grained image categorization. How well can we differentiate Norfolk Terriers from Norwich Terriers? With 120 breeds of dogs and a limited number training images per class, the problem was more, err, ruff than I anticipated.
The dataset consists of a training set and a test set of images of dogs. Each image has a filename that is its unique id. The dataset comprises 120 breeds of dogs. The goal of the competition is to create a classifier capable of determining a dog's breed from a photo.
train.zip- the training set, you are provided the breed for these dogstest.zip- the test set, you must predict the probability of each breed for each imagesample_submission.csv- a sample submission file in the correct formatlabels.csv- the breeds for the images in the train set
Use Kaggle API to download dataset:
kaggle competitions download -c dog-breed-identification