https://github.com/lucasrla/wsi-preprocessing-sos-workflow
A pipeline to preprocess whole-slide images (WSI) towards deep learning
https://github.com/lucasrla/wsi-preprocessing-sos-workflow
deep-learning histopathology pathology preprocessing sos sos-workflow whole-slide-imaging
Last synced: about 2 months ago
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A pipeline to preprocess whole-slide images (WSI) towards deep learning
- Host: GitHub
- URL: https://github.com/lucasrla/wsi-preprocessing-sos-workflow
- Owner: lucasrla
- License: gpl-3.0
- Created: 2020-09-03T22:37:30.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-09-04T22:50:51.000Z (over 4 years ago)
- Last Synced: 2025-03-21T00:12:06.576Z (2 months ago)
- Topics: deep-learning, histopathology, pathology, preprocessing, sos, sos-workflow, whole-slide-imaging
- Homepage:
- Size: 14.6 KB
- Stars: 4
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: COPYING
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README
# wsi-preprocessing-sos-workflow
A simple pipeline built with [SoS Workflow](https://vatlab.github.io/sos-docs/workflow.html) that runs [wsi-preprocessing](https://github.com/lucasrla/wsi-preprocessing) on a remote machine.
[wsi-preprocessing](https://github.com/lucasrla/wsi-preprocessing) is a simple library for preprocessing histopathological whole-slide images (WSI) towards deep learning. Check out its [repository](https://github.com/lucasrla/wsi-preprocessing).
If you do not have a remote machine ready, you can launch a new AWS EC2 instance with [ec2-setup-sos-workflow](https://github.com/lucasrla/ec2-setup-sos-workflow).
## Installation
### conda
```sh
conda create --name YOUR_ENV_NAME --channel conda-forge python=3.6 pyyaml boto3 sos black
# black is optional, it is sort of a development dependency
git clone https://github.com/lucasrla/wsi-preprocessing-sos-workflow
cd wsi-preprocessing-sos-workflow
conda activate YOUR_ENV_NAME
```
### poetry or pip
```sh
git clone https://github.com/lucasrla/wsi-preprocessing-sos-workflow
cd wsi-preprocessing-sos-workflow
# create and activate a virtualenv, for example:
pyenv virtualenv YOUR_ENV_NAME && pyenv local YOUR_ENV_NAME
# install the dependencies, either with:
poetry install
# or:
pip install -r requirements.txt
# note, requirements.txt in this repository were generated via:
# poetry export --without-hashes -f requirements.txt -o requirements.txt
```
## Configuration
```sh
# edit project.TEMPLATE.yml to match your needs
vim project.TEMPLATE.yml
# and then save it as project.yml
# make sure that ~/.sos/hosts.yml has the path to your pem_file
# and that the naming of hosts matches project.yml
vim ~/.sos/hosts.yml
```
## Usage
```sh
sos run -c project.yml remote.sos -v4
```
For more tips and tricks on SoS, read the [official docs](https://vatlab.github.io/sos-docs/workflow.html).
You can also have a look at [ec2-setup-sos-workflow](https://github.com/lucasrla/ec2-setup-sos-workflow).
## License
This is [Free Software](https://www.gnu.org/philosophy/free-sw.html) distributed under the [GNU General Public License v3.0](https://choosealicense.com/licenses/gpl-3.0/).