SVLT
Serving Vision to Living Things.
Summary
SVLT is a service for on-demand computer vision, adapted specifically to image-based feedback in microscopy and other life sciences applications. It abstracts image data access, persists machine learning models, and exposes an extensible API to facilitate low-latency analysis.
Install Git and miniforge
- Install Miniforge for environment management:
https://github.com/conda-forge/miniforge/releases - Under the Start menu, open
Miniforge3 > Miniforge Prompt
Install SVLT from source:
- Install Git:
https://git-scm.com/download/win - In the new terminal, clone the model_server repository:
cd %userprofile%
git clone git@git.embl.de:grp-almf/svlt.git
- Requirements depend on which SVLT packages to include. To create the target environment for svlt-pheno:
mamba env create --file svlt-pheno/requirements.yml --name svlt-pheno-env
- Activate the target environment:
mamba activate svlt-pheno-env
- Add the same packages from source in editable mode:
pip install --no-deps -e ./svlt-core ./svlt-pheno
To start the server:
- From the Miniforge prompt, run
mamba activate svlt-pheno-env
- Then run
python -m scripts.run_server --port 6221
- A browser window should appear, with basic status information.