https://github.com/nahuelcostacortez/ecgbeatgeneralization
https://github.com/nahuelcostacortez/ecgbeatgeneralization
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/nahuelcostacortez/ecgbeatgeneralization
- Owner: NahuelCostaCortez
- Created: 2025-01-23T17:33:12.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-03-11T16:41:16.000Z (3 months ago)
- Last Synced: 2025-03-11T17:47:08.563Z (3 months ago)
- Language: Jupyter Notebook
- Size: 16.9 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ECG Classification Project
This project implements ECG signal classification using deep learning models.
## Environment Setup
This project uses `uv` for dependency management. Follow these steps to set up your environment:
1. Install `uv`:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
2. Create a new virtual environment:
```bash
uv venv --python 3.11 _name_
```
3. Activate the virtual environment:
```bash
source _name_/bin/activate
```
4. Install dependencies:
```bash
uv pip install -r requirements.txt
```
## Project Structure
- `data/`: Contains data processing scripts and datasets
- `data.py`: Dataset loading and preprocessing
- `models/`: Model implementations and training scripts
- `cnn.py`: CNN model architecture
- `seq2seq.py`: Seq2Seq model architecture
- `train.py`: Training script
- `notebooks/`: Jupyter notebooks for analysis and evaluation
## Usage
1. Prepare your data and place it in the `data/` directory
2. Train a model:
```bash
python models/train.py --model CNN --dataset MIT-BIH
```