region:us
---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': normal
          '1': pneumonia
  splits:
  - name: train
    num_bytes: 126684250.689
    num_examples: 4187
  - name: validation
    num_bytes: 27444182.485
    num_examples: 1045
  - name: test
    num_bytes: 16275660.0
    num_examples: 624
  download_size: 153021953
  dataset_size: 170404093.174
---
# Chest X-Ray Pneumonia Dataset

This dataset contains chest x-ray images of independent patients that can be classified into `normal` (healthy) or `pneumonia` (diseased) patients.

This dataset is a processed version of the original `Large Dataset of Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images` dataset provided by the *University of California San Diego*. 

The dataset contains three splits: 

- **Train**: 4187 images
- **Validation**: 1045 images
- **Test**: 624 images

The shape of the images is `[500, 500, 3]`, and the labels have two possible values:

- 0: **Normal**
- 1: **Pneumonia**

>**References**:
>
> - Kermany, Daniel; Zhang, Kang; Goldbaum, Michael (2018), “Large Dataset of Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images”, Mendeley Data, V3, doi: 10.17632/rscbjbr9sj.3