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Description:

cspot 1.0.12

🐊 Getting Started with CSPOT
Kindly note that CSPOT is not a plug-and-play solution. It's a framework that requires significant upfront investment of time from potential users for training and validating deep learning models, which can then be utilized in a plug-and-play manner for processing large volumes of similar multiplexed imaging data.
System Requirements:
Hardware :
CSPOT comprises two modules: training and prediction. Training can be efficiently executed on a standard laptop without the need for a GPU. However, for predictions, leveraging a GPU significantly enhances processing speed (particularly for large images).
Software :
This package is supported for Windows (10, 11), macOS (Sonoma, Ventura) and Linux (Ubuntu 16.04).
Dependencies :
The pyproject.toml file contains a comprehensive list of dependencies.
Installation Guide:
There are two ways to set it up based on how you would like to run the program

Using an interactive environment like Jupyter Notebooks
Using Command Line Interface

Before we set up CSPOT, we highly recommend using a environment manager like Conda. Using an environment manager like Conda allows you to create and manage isolated environments with specific package versions and dependencies.
Download and Install the right conda based on the opertating system that you are using
Create a new conda environment
# use the terminal (mac/linux) and anaconda promt (windows) to run the following command
conda create --name cspot -y python=3.9
conda activate cspot

Install cspot within the conda environment.
pip install cspot

The installation time for cspot generally falls under 5 minutes, based on internet speed and connectivity.
Interactive Mode
Using IDE or Jupyter notebooks
pip install notebook

# open the notebook and import CSPOT
import cspot as cs
# Go to the tutorial section to follow along

Command Line Interface
wget https://github.com/nirmalLab/cspot/archive/main.zip
unzip main.zip
cd cspot-main/cspot
# Go to the tutorial section to follow along

Docker Container
docker pull nirmallab/cspot:cspot
# Go to the tutorial section to follow along