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
1 maintainer
Metadata
1 maintainer
Release files for ivadomed 2.9.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| ivadomed-2.9.9.tar.gz | 191.9 kB | Without provenance | Details for ivadomed-2.9.9.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| ivadomed-2.9.9-py3-none-any.whl | Python 3 | none | any | Details for ivadomed-2.9.9-py3-none-any.whl |
Total release size: 432.2 kB
Release files / ivadomed-2.9.9.tar.gz
| Download URL | ivadomed-2.9.9.tar.gz |
|---|---|
| Size | 191.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.7
|
Release files / ivadomed-2.9.9-py3-none-any.whl
| Download URL | ivadomed-2.9.9-py3-none-any.whl |
|---|---|
| Size | 240.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.7
|
Security for ivadomed 2.9.9
Provenance
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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