File size: 1,496 Bytes
3256afc d8fefa8 3256afc d8fefa8 3256afc d8fefa8 3256afc d8fefa8 3256afc 9bc57c3 e83ff38 9bc57c3 3256afc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
---
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) |