Visualizing dataset class distribution in pytorch

Question

I have used in the past a seaborn plotting function to visualize the number of samples belonging to each class directory. That was very easy since each directory in which the dataset was divided represented a class, and within each directory there was a given number of samples. I visualized in pytorch the samples distribution in the classes or categories by this simple code :

import seaborn as sns
sns.countplot(x = train_dataset.targets)
plt.show()

The result of this code was the following visualization plot:

As you see the number of classes (=directories) was 25.

But now I need to visualize the same data structure with a larger number of directories. Actually about 1600 directories (or classes). Unfortunately I realized the I could not use the same piece of code because the result was the following :

What modification should I add to the code in order to make readable the visualization ? Thank you for you help

Answer 1

If your question is specifically about how to make the values on the x-axis legible, you can modify your code as follows:

import seaborn as sns

myplot = sns.countplot(x = train_dataset)

# 200 is an arbitrary number representing the spacing between x-ticks
myplot.set_xticks(range(0, num_classes, 200)) 
                                           
plt.show()