Skip to main content

Fluorescence Signal Analyzer for calcium imaging on user-defined neural structures.

Project description

FluoSA

Fluorescence Signal Analyzer (FluoSA) for calcium imaging on user-defined neural structures.

FluoSA inputs *.LIF files, detects user-defined neural structures, and quantifies the fluorescence signal changes (frame-wise fluorescence intensity and the dF/F0) in these structures.

 

Installation

1 Install FluoSA

python3 -m pip install FluoSA

 

2 Install CUDA toolkit v11.8

https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Windows&target_arch=x86_64

 

3 Install PyTorch 2.0.1

3.1 For Windows and Linux

3.1.1 If using GPU
python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
3.1.2 CPU only
python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cpu

3.2 For Mac

python3 -m pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2

 

4 Install Detectron2

python3 -m pip install 'git+https://github.com/facebookresearch/detectron2.git'

 

Usage

In your terminal / command prompt, type:

FluoSA

Then the user interface will be initiated:

alt text

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fluosa-0.9.4.tar.gz (25.8 kB view hashes)

Uploaded Source

Built Distribution

fluosa-0.9.4-py3-none-any.whl (30.4 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page