Installation
$ pip install eeg-dementia-classification-MNet
Pretrained Weights
Pretrained weights are available on our Google Drive.
- Download 'pretrained_weights.tar.gz'.
- Extract the file using the following command:
$ tar xvf pretrained_weights.tar.gz
- Locate the extradcted 'pretrained_weights' directory at the working directory. As an illustration, the weight files (.pth) should be organized as follows:
./pretrained_weights/
├── AD_vs_DLB
│ ├── model_fold#0_epoch#045.pth
│ ├── model_fold#1_epoch#031.pth
│ ├── model_fold#2_epoch#029.pth
│ ├── model_fold#3_epoch#031.pth
│ └── model_fold#4_epoch#028.pth
├── AD_vs_DLB_vs_NPH
│ ├── model_fold#0_epoch#024.pth
│ ├── model_fold#1_epoch#035.pth
...
Usage
from eeg_dementia_classification_MNet import MNet_1000
import torch
## Parameters
DISEASE_TYPES = ["HV", "AD", "DLB", "NPH"]
## MNet
model = MNet_1000(DISEASE_TYPES, is_ensemble=True)
model.load_weights(i_fold=0)
## Feeds data
bs, n_chs, seq_len = 16, 19, 1000
x = torch.rand(bs, n_chs, seq_len)
y = model(x)
Contact
Please feel free to contact the author.
1 maintainer
Metadata
1 maintainer
Release files for eeg-dementia-classification-MNet 1.4.1
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| File | Size | Uploaded | Provenance | |
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| eeg_dementia_classification_MNet-1.4.1.tar.gz | 6.6 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| eeg_dementia_classification_MNet-1.4.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.7 kB
Release files / eeg_dementia_classification_MNet-1.4.1.tar.gz
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| Tags | Python 3 |
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