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().
Feature Overview
- ✅ Image support
- ✅ Video support
- ✅ Saving and organizing media in a database along with their origin URL
- ✅ Rendering
MultimodalSequencein a web UI - ⏳ Duplication management: Identify and re-use duplicates
1 maintainer
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