https://github.com/abailoni/segmfriends

https://github.com/abailoni/segmfriends

Last synced: 2 months ago
JSON representation

• Host: GitHub
• URL: https://github.com/abailoni/segmfriends
• Owner: abailoni
• Created: 2018-11-30T14:50:29.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2024-05-30T16:50:47.000Z (8 months ago)
• Last Synced: 2024-10-20T14:30:34.673Z (3 months ago)
• Language: Python
• Size: 282 KB
• Stars: 1
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Segmfriends

Bunch of tools and experiments for image segmentation

## Install

### Basic version from conda (Linux and Mac)

This version can run all the clustering/segmentation algorithms included the package. To install the package, you will need [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/) or [miniconda](https://docs.conda.io/en/latest/miniconda.html)

```bash

# Install the package:

conda create -n segmfriends -c abailoni segmfriends

# Activate your new 'speedrun' environment:

conda activate segmfriends

````

### Full version 

If you plan to work on the package or run the deep-learning tools in it, you will need to install some extra packages (including [inferno](https://github.com/abailoni/inferno), [speedrun](https://github.com/abailoni/speedrun), [neurofire](https://github.com/abailoni/neurofire), [ConfNets](https://github.com/imagirom/ConfNets/tree/multi-scale-unet)):

- Clone the repository: `git clone https://github.com/abailoni/segmfriends.git`

- `cd ./segmfriends`

- `chmod +x ./install_full_dependencies.sh`

- To install the dependencies, you will need [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/) or [miniconda](https://docs.conda.io/en/latest/miniconda.html)

- Install the dependencies and the package by running `./install_full_dependencies.sh`. While the script is running, you will need to confirm twice.

- The script will create a new conda environment called `segmFriends` including everything. You can activate your new environment with `conda activate segmFr`