Skip to main content

Lightweight Python kit for easy multimodal data processing.

Project description

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 MultimodalSequence in a web UI
  • ⏳ Duplication management: Identify and re-use duplicates

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ezmm-0.3.1.tar.gz (19.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ezmm-0.3.1-py3-none-any.whl (20.6 kB view details)

Uploaded Python 3

File details

Details for the file ezmm-0.3.1.tar.gz.

File metadata

  • Download URL: ezmm-0.3.1.tar.gz
  • Upload date:
  • Size: 19.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.11

File hashes

Hashes for ezmm-0.3.1.tar.gz
Algorithm Hash digest
SHA256 2b075bc3d78947fafec3e907aff2f58572a462cda0adf1d954b743dae59fb306
MD5 804641ba976c18d98e2aed2c9b2072db
BLAKE2b-256 317eb0a7ff11e9b6b70a59b501a665866fd44733d19b323c5387a6b668fa9bc2

See more details on using hashes here.

File details

Details for the file ezmm-0.3.1-py3-none-any.whl.

File metadata

  • Download URL: ezmm-0.3.1-py3-none-any.whl
  • Upload date:
  • Size: 20.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.11

File hashes

Hashes for ezmm-0.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 218db5001f6bddb7cfeab45f02ccaf2d3c2712ac1b9b542b265a8000e5d10631
MD5 9cfac41e9de99a114ee089efa9d71bbe
BLAKE2b-256 c5ccc0bfbe1fbe137815223516624d3e651456020ab1c617a213e00b81062f50

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page