Skip to main content

A Python library for different image processing tasks.

Project description

ipynta is a Python library designed for rapid development of image pre-processing pipelines.

High level overview

The diagram above describes the purpose of each iPynta class family and how can they be used collectively in an image pre-processing pipeline.

Sourcing Classes

Sourcing classes are used for retrieving image dataset metadata from different sources (local drive, zip files, etc.):

Loader Classes

Loader classes are used for instantiating / constructing / loading images from different sources.

Predicate Classes

Predicate classes are used for filtering unwanted data from image datasets.

Why was it named ipynta?

I-pinta means "to paint" in tagalog! This library is proudly developed by a Singapore-based Filipino lad with nothing better to do during evenings.

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

ipynta-0.0.23.tar.gz (4.9 kB view details)

Uploaded Source

Built Distribution

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

ipynta-0.0.23-py3-none-any.whl (5.9 kB view details)

Uploaded Python 3

File details

Details for the file ipynta-0.0.23.tar.gz.

File metadata

  • Download URL: ipynta-0.0.23.tar.gz
  • Upload date:
  • Size: 4.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for ipynta-0.0.23.tar.gz
Algorithm Hash digest
SHA256 1187dabe04d8f3153fd3bf35025b08739b0a6afea832bc04b766bad83f725a94
MD5 55b7bcd70487d2918f3081def2f4a059
BLAKE2b-256 1efb782bfcdc4b798551ad34ad55f9962628552d2cc4a7313d839f156402c8be

See more details on using hashes here.

File details

Details for the file ipynta-0.0.23-py3-none-any.whl.

File metadata

  • Download URL: ipynta-0.0.23-py3-none-any.whl
  • Upload date:
  • Size: 5.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for ipynta-0.0.23-py3-none-any.whl
Algorithm Hash digest
SHA256 94ec6f15f105372cf4ff461d2c0c27d8b312c6268e4d6914ab3a1849ff21b0ec
MD5 f532800bd7f5fe2b8aa2df8a8bff27c5
BLAKE2b-256 323b8c91eb217c218a616663f246124178cc4c21068a70e552d33c755bfa2d02

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