![Flower Video Demonstration] (http://img.youtube.com/vi/_tNFDPvlLZs/0.jpg)
Flower is a new visualization tool for in-depth study of multi-sensor recordings in the time domain. It has been released for public download as a fully functioning tool available for experimental, research, and creative use. Flower uses unsupervised machine learning to extract latent representations for time-series data (EEG in particular) and show them through different visualization settings. In particular, it adds color and thickness to time-series plots, making them easier to understand and compare. Flower aims to enable more natural intuition around data results, using machine intelligence to translate time-series data for improved understanding by the human eye.
- Download and Install Anaconda from: https://www.anaconda.com/distribution/
- Clone the repository in a directory:
git clone https://github.com/NeoVand/Flower2.git- Create a python 3.7 environment by typing this command in the Anaconda Prompt (or any shell with conda in PATH):
cd Flower2
conda env create --name mneflower --file environment.yml- Activate the environment:
conda activate mneflowerif you are using macOS then run this line:
pip install "PyQt5>=5.10"- Run the application:
python app.py- Load the UI:
go to local host with port 5000 by pointing chrome to
127.0.0.1:5000