Skip to main content

A Candy for Medical Image Processing

Project description

MIP Candy: A Candy for Medical Image Processing

GitHub code size in bytes PyPI GitHub Release GitHub Release Date - Published_At

MIP Candy is Project Neura's next-generation infrastructure framework for medical image processing. It integrates a handful number of common network architectures with their corresponding training, inference, and evaluation pipelines that are out-of-the-box ready to use. Additionally, it also provides adapters to popular frontend dashboards such as Notion, WandB, and TensorBoard.

:link: Home

:link: Docs

Installation

Note that MIP Candy requires Python >= 3.12.

pip install "mipcandy[standard]"

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

mipcandy-1.0.2b1.tar.gz (31.7 kB view details)

Uploaded Source

Built Distribution

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

mipcandy-1.0.2b1-py3-none-any.whl (44.2 kB view details)

Uploaded Python 3

File details

Details for the file mipcandy-1.0.2b1.tar.gz.

File metadata

  • Download URL: mipcandy-1.0.2b1.tar.gz
  • Upload date:
  • Size: 31.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mipcandy-1.0.2b1.tar.gz
Algorithm Hash digest
SHA256 4d4abd0db3508c6fff0d5608479d6329b1dc09133017cdd84702d987b8cd434f
MD5 0c7a0f6494f69d70070934fcc6ea220b
BLAKE2b-256 63b3962e6ed2800dcf2b3606403b887b61276f809af42603a6a19c905413a95c

See more details on using hashes here.

Provenance

The following attestation bundles were made for mipcandy-1.0.2b1.tar.gz:

Publisher: python-publish.yml on ProjectNeura/MIPCandy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mipcandy-1.0.2b1-py3-none-any.whl.

File metadata

  • Download URL: mipcandy-1.0.2b1-py3-none-any.whl
  • Upload date:
  • Size: 44.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mipcandy-1.0.2b1-py3-none-any.whl
Algorithm Hash digest
SHA256 62e619c3495e889efc3987eb4bec365a79d7565fef2a97b6ea166e53ecc22c5d
MD5 901832630d699b69f7691748ba5e6edd
BLAKE2b-256 ff2991e202e0bf913886b0dfde23cf330c2b6b13df0bad8423af49e1274c9944

See more details on using hashes here.

Provenance

The following attestation bundles were made for mipcandy-1.0.2b1-py3-none-any.whl:

Publisher: python-publish.yml on ProjectNeura/MIPCandy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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