Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Data Generation
Our images are quite simple: They have black backgrounds and white lines drawn
on top of them. The lines can be drawn either in a diagonal or in a parallel (to one of
the edges, so they could be either horizontal or vertical) way. So, our classification
problem can be simply stated as: Is the line diagonal?
If the line is diagonal, then we assume it belongs to the positive class. If it is not
diagonal, it belongs to the negative class. We have our labels (y), which we can
summarize like this:
Line Value Class
Not Diagonal 0 Negative
Diagonal 1 Positive
Let’s generate 300 random images, each one five-by-five pixels in size:
Data Generation
1 images, labels = generate_dataset(
2 img_size=5, n_images=300, binary=True, seed=13
3 )
And then let’s visualize the first 30 images:
fig = plot_images(images, labels, n_plot=30)
Classifying Images | 267