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-1.0.1b0.tar.gz (26.8 kB view details)

Uploaded Source

Built Distribution

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

mipcandy-1.0.1b0-py3-none-any.whl (37.9 kB view details)

Uploaded Python 3

File details

Details for the file mipcandy-1.0.1b0.tar.gz.

File metadata

  • Download URL: mipcandy-1.0.1b0.tar.gz
  • Upload date:
  • Size: 26.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mipcandy-1.0.1b0.tar.gz
Algorithm Hash digest
SHA256 36237348f45ecea07c1aeb9a27316a36de6aef2412f6938a95d18ac8681442d5
MD5 ce7850b3e619e765f478dc59928fbab4
BLAKE2b-256 cf1cd879f2afb8a1a2a3fa2aaa8007831469c3cff3fc1c5ca470a75ea152ec86

See more details on using hashes here.

Provenance

The following attestation bundles were made for mipcandy-1.0.1b0.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-1.0.1b0-py3-none-any.whl.

File metadata

  • Download URL: mipcandy-1.0.1b0-py3-none-any.whl
  • Upload date:
  • Size: 37.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mipcandy-1.0.1b0-py3-none-any.whl
Algorithm Hash digest
SHA256 100c744ed2555fca8fb568f36ae8ce4df0a59d2bce05423cfe75efdcadc2b30d
MD5 2c83edc1fcd8471aa4288d818da69fde
BLAKE2b-256 f479aaf33bd6f3e4ee33a64c75b5327bbb75b525e244b4bcc6caca72111a9d5a

See more details on using hashes here.

Provenance

The following attestation bundles were made for mipcandy-1.0.1b0-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