ezMM 0.1.1

Lightweight Python kit for easy multimodal data processing.

ezMM: Mini-Suite for Easy Multimodal Data Processing

This lightweight Python package aims to streamline and simplify the processing of multimodal data. The core philosophy of ezMM is to treat any data (whether strings, images, audios, tables, etc.) as a multimodal sequence.

Usage

Core is the MultimodalSequence class. Here is an example:

from ezmm import MultimodalSequence, Image

img1 = Image("in/roses.jpg")
img2 = Image("in/garden.jpg")

seq = MultimodalSequence("The image", img1, "shows two beautiful roses while",
                         img2, "shows a nice garden with many flowers.")

seq comprehensively aggregates the different modalities into one handy object. It also offers some useful features:

MultimodalSequence is stringifyable

print(seq)

will return

The image <image:1> shows two beautiful roses while <image:2> shows a nice garden with many flowers.

That is, non-string items in the MultimodalSequence get replaced by their unique reference when turned into strings.

MultimodalSequence understands references

Conversely, you can do

seq2 = MultimodalSequence("The image <image:1> shows two beautiful roses while <image:2> shows a nice garden with many flowers.")

which obeys seq == seq2. That is, MultimodalSequence resolves references within the input string and loads the corresponding items under the hood.

Access MultimodalSequence like a list

You can apply list comprehension to seq. For example, seq[1] == img.

Easy modality checks

You can check for specific modalities like images quickly, e.g., with seq.has_images().