Feature conditioning for IVADO medical imaging project.
Project description
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.
Consult our Wiki(https://github.com/ivadomed/ivadomed/wiki) here for more help
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ivadomed-2.9.9.tar.gz.
File metadata
- Download URL: ivadomed-2.9.9.tar.gz
- Upload date:
- Size: 191.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c883e8e38cf7bbc3185a5cc6dd4c38fd01e63ab2a08ea29a9550cf701c4c57cc
|
|
| MD5 |
be4564aad8d47b157b1c5d8b4d2edab2
|
|
| BLAKE2b-256 |
d3bb12f532aea4c8206421a04beb32c30def618b2f505f8e9748c6109382ebfd
|
File details
Details for the file ivadomed-2.9.9-py3-none-any.whl.
File metadata
- Download URL: ivadomed-2.9.9-py3-none-any.whl
- Upload date:
- Size: 240.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
80bfa74eecdc51370851db4d6d9c7ad3b7b0560d8926f5014682e5d39ecde13c
|
|
| MD5 |
2503d27b13a47ea4370426e2c81df18a
|
|
| BLAKE2b-256 |
0094b7df3c11a42acefa38c0c69ee9a0d18162c961008869bb6b90b0c943b0c2
|
