Detecting duplicates

What is it

The Duplicates class identifies exact and near duplicate data.

When to use it

The Duplicates class should be used if you need to check for duplicates in your dataset.

Theory behind it

With the Duplicates class, exact matches are found using a byte hash of the data information, while near matches (such as a crop of another image or a distoration of another image) use a perception based hash.

The byte hash is achieved through the use of the python-xxHash Python module, which is based on Yann Collet’s xxHash C library.

The perceptual hash is achieved on an image by resizing to a square NxN image using the Lanczos algorithm where N is 32x32 or the largest multiple of 8 that is smaller than the input image dimensions. The resampled image is compressed using a discrete cosine transform and the lowest frequency component is encoded as a bit array of greater or less than median value and returned as a hex string.