Dataset objects (for training and testing)

The software below provides functionality (with PyTorch) to load datasets for training and testing.

Abstract base class

All dataset objects derive from this abstract base class, which lays out the notion of a dataset with pairs of images: one image is lensed (simulated or measured), and the other is lensless (simulated or measured).

Measured dataset objects

Simulated dataset objects

These dataset objects can be used for training and testing with simulated data. The main assumption is that the imaging system is linear shift-invariant (LSI), and that the lensless image is the result of a convolution of the lensed image with a point-spread function (PSF). Check out this Medium post for more details on the simulation procedure.

With simulated data, we can avoid the hassle of collecting a large amount of data. However, it’s important to note that the LSI assumption can sometimes be too idealistic, in particular for large angles.

Nevertheless, simulating data is the only option of learning the mask / PSF.