elf

elf implements image analysis functionality for large microscopy data.

Overview

elf provides functionality for different image analysis tasks. The main functionality is:

  • elf.evaluation: Common metrics for evaluating segmentation results.
  • elf.io: Common interface for reading file formats for large microscopy data.
  • elf.parallel: Parallel implementations of image analysis functions.
  • elf.segmentation: Segmentation functions based on clustering, (lifted) multicut, mutex watershed and more.
  • elf.tracking: Graph-based tracking algorithms.
  • elf.wrapper: Wrapper for large microscopy data to enable on-the-fly processing.

Installation

elf is available on conda-forge. You can install it into an existing conda environment via:

conda install -c conda-forge python-elf

We also provide a environment for a development environment. To set it up:

  1. Clone the elf repository:
git clone https://github.com/constantinpape/elf
  1. Enter the root elf directory:
cd elf
  1. Create the development environment:
conda create -f environment.yaml
  1. Activate the environment:
conda activate elf-dev
  1. Install elf in development mode:
pip install -e .

Usage & Examples

Example scripts for many of elf's features can be found in example.

elf also provides command line functionality. Currently provided are the command line interfaces:

  • view_container: Visualize the content of any file supported by elf.io with napari.
 1"""[elf](https://github.com/constantinpape/elf) implements image analysis functionality for large microscopy data.
 2
 3# Overview
 4
 5`elf` provides functionality for different image analysis tasks. The main functionality is:
 6- `elf.evaluation`: Common metrics for evaluating segmentation results.
 7- `elf.io`: Common interface for reading file formats for large microscopy data.
 8- `elf.parallel`: Parallel implementations of image analysis functions.
 9- `elf.segmentation`: Segmentation functions based on clustering, (lifted) multicut, mutex watershed and more.
10- `elf.tracking`: Graph-based tracking algorithms.
11- `elf.wrapper`: Wrapper for large microscopy data to enable on-the-fly processing.
12
13# Installation
14
15`elf` is available on conda-forge. You can install it into an existing conda environment via:
16```
17conda install -c conda-forge python-elf
18```
19
20We also provide a environment for a development environment. To set it up:
211. Clone the elf repository:
22```
23git clone https://github.com/constantinpape/elf
24```
252. Enter the root elf directory:
26```
27cd elf
28```
293. Create the development environment:
30```
31conda create -f environment.yaml
32```
334. Activate the environment:
34```
35conda activate elf-dev
36```
375. Install elf in development mode:
38```
39pip install -e .
40```
41
42# Usage & Examples
43
44Example scripts for many of `elf`'s features can be found in [example](https://github.com/constantinpape/elf/tree/master/example).
45
46`elf` also provides command line functionality. Currently provided are the command line interfaces:
47- `view_container`: Visualize the content of any file supported by `elf.io` with napari.
48"""
49
50from .__version__ import __version__