Skip to main content

ivadomed Overview

DOI Coverage Status test status publish package Documentation Status License: MIT Twitter Follow

ivadomed is an integrated framework for medical image analysis with deep learning.

The technical documentation is available here. The more detailed installation instruction is available there

Installation

ivadomed requires Python >= 3.7 and < 3.10 as well as PyTorch == 1.8. We recommend working under a virtual environment, which could be set as follows:

python -m venv ivadomed_env
source ivadomed_env/bin/activate

Install from release (recommended)

Install ivadomed and its requirements from Pypi <https://pypi.org/project/ivadomed/>__:

pip install --upgrade pip
pip install ivadomed

Install from source

Bleeding-edge developments builds are available on the project's master branch on Github. Installation procedure is the following:

git clone https://github.com/neuropoly/ivadomed.git
cd ivadomed
pip install -e .

Contributors

This project results from a collaboration between the NeuroPoly Lab and the Mila. The main funding source is IVADO.

List of contributors

Consult our Wiki(https://github.com/ivadomed/ivadomed/wiki) here for more help

Metadata

Release files for ivadomed 2.9.10

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ivadomed 2.9.10
File Size Uploaded
ivadomed-2.9.10.tar.gz 191.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for ivadomed 2.9.10
File Interpreter ABI Platform
ivadomed-2.9.10-py3-none-any.whl Python 3 none any Details

Total release size: 432.2 kB

Release files / ivadomed-2.9.10.tar.gz

Download URL ivadomed-2.9.10.tar.gz
Size 191.8 kB
Tags Source
SHA-256 checksum
How to use checksums
c209ea93229d5a2ffe5688589b3d9a993db2b03be3d965f640ea51f214f5af14
BLAKE2b-256 checksum
How to use checksums
dc93aab64c6543dabddc4f50451af84eeaba8fc76e1eae0b4ecce7740fc3b4d7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.12.2

Release files / ivadomed-2.9.10-py3-none-any.whl

Download URL ivadomed-2.9.10-py3-none-any.whl
Size 240.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
c19c47f246c6f942f064617fad60f3d2c5d4d3d39ccaebf8f377ca89d3c25286
BLAKE2b-256 checksum
How to use checksums
a963294ec438db13073fe992324fd247fffbdf2c097961cd28f5b2dac859fca9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.12.2

Release history Release notifications | RSS feed

This release

2.9.10 This release

2 release files

2.9.9

2 release files

2.9.8

2 release files

2.9.7

2 release files

2.9.6

2 release files

2.9.5

2 release files

2.9.4

2 release files

2.9.3

2 release files

2.9.2

2 release files

2.9.1

2 release files

2.9.0

2 release files

2.8.0

2 release files

2.7.4

2 release files

2.7.2

2 release files

2.7.1

2 release files

2.7.0

2 release files

2.6.1

2 release files

2.6.0

2 release files

2.5.0

2 release files

2.4.0

2 release files

2.3.1

2 release files

2.2.1

2 release files

2.2.0

2 release files

2.1.0

2 release files

2.0.2

2 release files

2.0.1

2 release files

1.2.1

2 release files

1.2

2 release files

1.1

2 release files

1.0

2 release files

0.14

2 release files

0.13

2 release files

0.12

2 release files

0.11

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page