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Installation Guide

octopi is available on PyPI and can be installed using pip:

pip install octopi
This will install the latest stable release along with all required dependencies.

Development Installation

If you want to contribute to octopi or need the latest development version, you can install from source:

git clone https://github.com/chanzuckerberg/octopi.git
cd octopi
pip install -e .

The editable (-e) install ensures that local code changes are immediately reflected without reinstalling.

Verify installation

After installation, verify that the command-line interface is available:

octopi

You should see output similar to the following:

Octopi 🐙: 🛠️ Tools for Finding Proteins in 🧊 cryo-ET data                        

╭─ Options ───────────────────────────────────────────────────────────────────────╮
│ --help  -h  Show this message and exit.                                         │
╰─────────────────────────────────────────────────────────────────────────────────╯
╭─ Pre-Processing ────────────────────────────────────────────────────────────────╮
│ download        Download and (optionally) downsample tomograms from the         │
│                 CryoET-DataPortal.                                              │
│ import          Import MRC tomograms from a folder into a copick project.       │
│ create-targets  Generate segmentation targets from CoPick configurations.       │
╰─────────────────────────────────────────────────────────────────────────────────╯
╭─ Training ──────────────────────────────────────────────────────────────────────╮
│ train           Train 3D CNN U-Net models for Cryo-ET semantic segmentation.    │
│ model-explore   Perform model architecture search with Optuna.                  │
╰─────────────────────────────────────────────────────────────────────────────────╯
╭─ Inference ─────────────────────────────────────────────────────────────────────╮
│ segment           Segment volumes using trained neural network models.          │
│ localize          Convert Segmentation Masks to 3D Particle Coordinates.        │
│ membrane-extract  Extract membrane-bound picks based on proximity to organelle  │
│                   or membrane segmentation.                                     │
│ evaluate          Evaluate particle localization performance against ground     │
│                   truth annotations.                                            │
╰─────────────────────────────────────────────────────────────────────────────────╯

Next Steps