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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

  1. Install Miniforge for environment management:
    https://github.com/conda-forge/miniforge/releases
  2. Under the Start menu, open Miniforge3 > Miniforge Prompt

Install SVLT from source:

  1. Install Git:
    https://git-scm.com/download/win
  2. In the new terminal, clone the model_server repository:
    cd %userprofile%
    git clone git@git.embl.de:grp-almf/svlt.git
  3. 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
  4. Activate the target environment: mamba activate svlt-pheno-env
  5. Add the same packages from source in editable mode: pip install --no-deps -e ./svlt-core ./svlt-pheno

To start the server:

  1. From the Miniforge prompt, run mamba activate svlt-pheno-env
  2. Then run python -m scripts.run_server --port 6221
  3. A browser window should appear, with basic status information.