---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: epoch
    dtype: int64
  - name: label_str
    dtype:
      class_label:
        names:
          '0': No Event
          '1': bckg
          '2': seiz
  - name: label
    dtype:
      class_label:
        names:
          '0': No Event
          '1': bckg
          '2': seiz
  splits:
  - name: train
    num_bytes: 23742147634.792
    num_examples: 814568
  download_size: 24165936927
  dataset_size: 23742147634.792
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
# Dataset Card for "seizure_eeg_train"

```python
from datasets import load_dataset

dataset_name = "JLB-JLB/seizure_eeg_train"

dataset = load_dataset(
    dataset_name,
    split="train",
)

display(dataset)

# create train and test/val split
train_testvalid = dataset.train_test_split(test_size=0.1, shuffle=True, seed=12071998)
display(train_testvalid)

# get the number of different labels in the train, test and validation set
display(train_testvalid["train"].features["label"])
display(train_testvalid["test"].features["label"].num_classes)

# check how many labels/number of classes
num_classes = len(set(train_testvalid["train"]['label']))
labels = train_testvalid["train"].features['label']
print(um_classes, labels)


display(train_testvalid["train"][0]['image'])

```


[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)