Metadata-Version: 2.1
Name: i2s-ecg
Version: 0.1.8
Summary: the package for ECG signal processing
Author: zou linzhuang
Author-email: zoulinzhuang2204@hnu.edu.cn
License: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: scikit-learn ==1.2.2
Requires-Dist: scikit-image
Requires-Dist: unzip
Requires-Dist: joblib
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: natsort
Requires-Dist: streamlit ==1.37.0
Requires-Dist: streamlit-cropper
Requires-Dist: scipy
Requires-Dist: numpy ==1.25.2
Requires-Dist: pillow

# ecg_i2s

Transform ECG Images to Signals

You can use this code to transform ECG images into 1D signals. Follow the instructions below to get started.

We recommend you to use the newest version of the code.

## Setup Instructions

### 1.**Create a Conda Environment**

We recommend using Python version 3.9.19.

   ```
conda create -n ecg python=3.9.19
   ```

Then you should activate the environment using:

   ```
conda activate ecg
   ```

### 2.**Install Required Packages**

Install the necessary packages using the following:

   - `scikit-learn==1.2.2`
   - `scikit-image`
   - `unzip`
   - `joblib`
   - `pandas`
   - `matplotlib`
   - `natsort`
   - `streamlit_cropper`
   - `scipy`
   - `numpy==1.25.2`
   - `pillow`
   - `natsort`

   Alternatively, you can use the `requirements.txt` file to install the required packages by running:

   ```bash
pip install -r requirements.txt
   ```

### 3.**Run the Code**

1. you can run the code by:

```
python -m i2s_ecg.run
```

2. you can also write your own program, for example:

```main.py
from i2s_ecg import run_app
run_app()
```

### 4.**use the streamlit app**
![for i2s_ecg](https://github.com/xzxg001/i2s_ecg/blob/main/for%20i2s_ecg.jpg)
We prepare a picture to show the usage of the app.

![i2s_ecg](https://github.com/xzxg001/i2s_ecg/blob/main/i2s_ecg.gif)
You can use the streamlit app to upload your ECG images and get the corresponding 1D signals.\
