| # ECG Analysis Model | |
| This is a lightweight CNN model trained for ECG image classification. | |
| ## Model Details | |
| - **Model Type**: Convolutional Neural Network | |
| - **Classes**: NORM, AFIB, SBRAD, STACH, BIGEMINY, VT | |
| - **Input Size**: 224x224x3 (RGB images) | |
| - **Framework**: PyTorch | |
| ## Usage | |
| ```python | |
| import torch | |
| from model import SimpleCNN | |
| model = SimpleCNN(num_classes=6) | |
| model.load_state_dict(torch.load('model.pt')) | |
| model.eval() | |
| ``` | |
| ## Training Data | |
| - Synthetic ECG patterns | |
| - 6 classes: NORM, AFIB, SBRAD, STACH, BIGEMINY, VT | |
| - Training samples: 800 | |
| - Test samples: 200 | |
| Created: 2025-09-19 15:23:09 | |