https://github.com/chanzuckerberg/saber
Segment Organelles from Electron Microscopy Datasets with Segment-Anything 2
https://github.com/chanzuckerberg/saber
computer-vision deep-learning segmentation
Last synced: 9 months ago
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Segment Organelles from Electron Microscopy Datasets with Segment-Anything 2
- Host: GitHub
- URL: https://github.com/chanzuckerberg/saber
- Owner: chanzuckerberg
- License: mit
- Created: 2025-05-22T18:24:35.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-09-30T04:13:11.000Z (9 months ago)
- Last Synced: 2025-09-30T06:11:34.878Z (9 months ago)
- Topics: computer-vision, deep-learning, segmentation
- Language: Jupyter Notebook
- Homepage:
- Size: 18.4 MB
- Stars: 5
- Watchers: 3
- Forks: 1
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Security: SECURITY.md
Awesome Lists containing this project
README
# SABER⚔️
[](https://github.com/chanzuckerberg/saber/blob/main/LICENSE)
[](https://pypi.org/project/saber-em/)
[](https://www.python.org/)
**S**egment **A**nything **B**ased **E**lectron tomography **R**ecognition is a robust platform designed for autonomous segmentation of organelles from cryo-electron tomography (cryo-ET) or electron microscopy (EM) datasets.
## Introduction
Leveraging foundational models, SABER enables segmentation directly from video-based training translated into effective 3D tomogram analysis. Users can utilize zero-shot inference with morphological heuristics or enhance prediction accuracy through data-driven training.
## 💫 Key Features
* 🔍 Zero-shot segmentation: Segment EM/cryo-ET data without explicit retraining, using foundational vision models.
* 🖼️ Interactive GUI for labeling: Intuitive graphical interface for manual annotation and segmentation refinement.
* 🧠 Expert-driven classifier training: Fine-tune segmentation results by training custom classifiers on curated annotations.
* 🧊 3D organelle segmentation: Generate volumetric segmentation masks across tomographic slices.
## 🚀 Getting Started
### Installation
Saber is available on PyPI and can be installed using pip:
```bash
pip install saber-em
```
⚠️ **Note**:
- By default, the GUI is not included in the base installation.
To enable the graphical interface for manual annotation, install with:
```bash
pip install saber-em[gui]
```
- One of the current dependencies is currently not working with pip 25.1. We recommend using pip 25.2 or higher when installing saber:
```bash
pip install --upgrade "pip>=25.2"
```
### Basic Usage
SABER provides a clean, scriptable command-line interface. Run the following command to view all available subcommands:
```
saber --help
```
## 📚 Documentation
For detailed documentation, tutorials, CLI and API reference, visit our [documentation](http://chanzuckerberg.github.io/saber/)
## 🤝 Contributing
This project adheres to the Contributor Covenant [code of conduct](https://github.com/chanzuckerberg/.github/blob/master/CODE_OF_CONDUCT.md).
By participating, you are expected to uphold this code.
Please report unacceptable behavior to [opensource@chanzuckerberg.com](mailto:opensource@chanzuckerberg.com).
## 🔒 Security
If you believe you have found a security issue, please responsibly disclose by contacting us at security@chanzuckerberg.com.