JeffBla / Image-and-porosity-analysis-By-Dash-plotly

This app uses Dash to explore core data. Compare images in the first row and interact with a line chart in the second row. Hovering reveals details, and clicking updates the images to match the selected data point.

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Image and porosity analysis By Dash & plotly

Demo

demo video

Fork From

Dash Exploration of COVID-19 chest X-ray CT images

About this app

This app shows how to explore core data using Dash.

With this app, you can compare images in the first row and interact with a line chart in the second row. By hovering your mouse over a point on the line chart, detailed information will be displayed. Additionally, clicking on a point will update the images above, allowing you to see the corresponding images for that specific data point. This feature enables you to correlate the data from the line chart with the visual details in the images.

The data used in this app come from the dataset obtained from the wells affiliated with the Department of Resource Engineering at National Cheng Kung University in Taiwan.

How to run this app

(The following instructions apply to Windows command line.)

To run this app first clone repository and then open a terminal to the app folder.

git clone https://github.com/JeffBla/Image-and-porosity-analysis-By-Dash-plotly.git
cd Image-and-porosity-analysis-By-Dash-plotly

Create and activate a new virtual environment (recommended) by running the following:

On Windows

virtualenv venv
\venv\scripts\activate

Or if using linux

python3 -m venv myvenv
source myvenv/bin/activate

Install the requirements:

pip install -r requirements.txt

Run the app:

python app.py

You can run the app on your browser at http://127.0.0.1:8050

Resources

To learn more about Dash, please visit documentation.

About

This app uses Dash to explore core data. Compare images in the first row and interact with a line chart in the second row. Hovering reveals details, and clicking updates the images to match the selected data point.


Languages

Language:Python 99.3%Language:CSS 0.6%Language:Procfile 0.1%