Automated documentation update.

PiperOrigin-RevId: 675261508

Author: The TensorFlow Datasets Authors

docs/catalog/_toc.yaml

@@ -237,6 +237,11 @@ toc:
   - path: /datasets/catalog/cardiotox
     title: cardiotox
   title: Graphs
+- section:
+  - path: /datasets/catalog/pneumonia_mnist
+    status: nightly
+    title: pneumonia_mnist
+  title: Health
 - section:
   - path: /datasets/catalog/abstract_reasoning
     title: abstract_reasoning (manual)
@@ -344,6 +349,9 @@ toc:
     title: plant_village
   - path: /datasets/catalog/plantae_k
     title: plantae_k
+  - path: /datasets/catalog/pneumonia_mnist
+    status: nightly
+    title: pneumonia_mnist
   - path: /datasets/catalog/quickdraw_bitmap
     title: quickdraw_bitmap
   - path: /datasets/catalog/ref_coco
@@ -503,6 +511,9 @@ toc:
     title: places365_small
   - path: /datasets/catalog/plant_village
     title: plant_village
+  - path: /datasets/catalog/pneumonia_mnist
+    status: nightly
+    title: pneumonia_mnist
   - path: /datasets/catalog/resisc45
     title: resisc45 (manual)
   - path: /datasets/catalog/siscore

docs/catalog/overview.md

@@ -191,6 +191,11 @@ for ex in tfds.load('cifar10', split='train'):
 
 *   [`cardiotox`](cardiotox.md)
 
+### `Health`
+
+*   [`pneumonia_mnist`](pneumonia_mnist.md)
+    <span class="material-icons" title="Available only in the tfds-nightly package">nights_stay</span>
+
 ### `Image`
 
 *   [`abstract_reasoning`](abstract_reasoning.md)
@@ -246,6 +251,8 @@ for ex in tfds.load('cifar10', split='train'):
 *   [`plant_leaves`](plant_leaves.md)
 *   [`plant_village`](plant_village.md)
 *   [`plantae_k`](plantae_k.md)
+*   [`pneumonia_mnist`](pneumonia_mnist.md)
+    <span class="material-icons" title="Available only in the tfds-nightly package">nights_stay</span>
 *   [`quickdraw_bitmap`](quickdraw_bitmap.md)
 *   [`ref_coco`](ref_coco.md)
 *   [`resisc45`](resisc45.md)
@@ -328,6 +335,8 @@ for ex in tfds.load('cifar10', split='train'):
 *   [`oxford_iiit_pet`](oxford_iiit_pet.md)
 *   [`places365_small`](places365_small.md)
 *   [`plant_village`](plant_village.md)
+*   [`pneumonia_mnist`](pneumonia_mnist.md)
+    <span class="material-icons" title="Available only in the tfds-nightly package">nights_stay</span>
 *   [`resisc45`](resisc45.md)
 *   [`siscore`](siscore.md)
 *   [`smallnorb`](smallnorb.md)

docs/catalog/pneumonia_mnist.md

@@ -0,0 +1,96 @@
+<div itemscope itemtype="http://schema.org/Dataset">
+  <div itemscope itemprop="includedInDataCatalog" itemtype="http://schema.org/DataCatalog">
+    <meta itemprop="name" content="TensorFlow Datasets" />
+  </div>
+  <meta itemprop="name" content="pneumonia_mnist" />
+  <meta itemprop="description" content="# MedMNIST Pneumonia Dataset&#10;&#10;The PneumoniaMNIST is based on a prior dataset of 5,856 pediatric chest X-Ray&#10;images. The task is binary-class classification of pneumonia against normal. The&#10;source training set is split with a ratio of 9:1 into training and validation&#10;set, and use its source validation set as the test set. The source images are&#10;gray-scale, and their sizes are (384–2,916) × (127–2,713). The images are&#10;center-cropped with a window size of length of the short edge and resized into 1&#10;× 28 × 28.&#10;&#10;To use this dataset:&#10;&#10;```python&#10;import tensorflow_datasets as tfds&#10;&#10;ds = tfds.load(&#x27;pneumonia_mnist&#x27;, split=&#x27;train&#x27;)&#10;for ex in ds.take(4):&#10;  print(ex)&#10;```&#10;&#10;See [the guide](https://www.tensorflow.org/datasets/overview) for more&#10;informations on [tensorflow_datasets](https://www.tensorflow.org/datasets).&#10;&#10;" />
+  <meta itemprop="url" content="https://www.tensorflow.org/datasets/catalog/pneumonia_mnist" />
+  <meta itemprop="sameAs" content="https://medmnist.com//" />
+  <meta itemprop="citation" content="@article{yang2023medmnist,&#10;  title={Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification},&#10;  author={Yang, Jiancheng and Shi, Rui and Wei, Donglai and Liu, Zequan and Zhao, Lin and Ke, Bilian and Pfister, Hanspeter and Ni, Bingbing},&#10;  journal={Scientific Data},&#10;  volume={10},&#10;  number={1},&#10;  pages={41},&#10;  year={2023},&#10;  publisher={Nature Publishing Group UK London}&#10;}" />
+</div>
+
+# `pneumonia_mnist`
+
+
+Note: This dataset was added recently and is only available in our
+`tfds-nightly` package
+<span class="material-icons" title="Available only in the tfds-nightly package">nights_stay</span>.
+
+*   **Description**:
+
+# MedMNIST Pneumonia Dataset
+
+The PneumoniaMNIST is based on a prior dataset of 5,856 pediatric chest X-Ray
+images. The task is binary-class classification of pneumonia against normal. The
+source training set is split with a ratio of 9:1 into training and validation
+set, and use its source validation set as the test set. The source images are
+gray-scale, and their sizes are (384–2,916) × (127–2,713). The images are
+center-cropped with a window size of length of the short edge and resized into 1
+× 28 × 28.
+
+*   **Homepage**: [https://medmnist.com//](https://medmnist.com//)
+
+*   **Source code**:
+    [`tfds.datasets.pneumonia_mnist.Builder`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/datasets/pneumonia_mnist/pneumonia_mnist_dataset_builder.py)
+
+*   **Versions**:
+
+    *   **`1.0.0`** (default): Initial release.
+
+*   **Download size**: `Unknown size`
+
+*   **Dataset size**: `Unknown size`
+
+*   **Auto-cached**
+    ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
+    Unknown
+
+*   **Splits**:
+
+Split | Examples
+:---- | -------:
+
+*   **Feature structure**:
+
+```python
+FeaturesDict({
+    'image': Image(shape=(28, 28, 1), dtype=uint8),
+    'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
+})
+```
+
+*   **Feature documentation**:
+
+Feature | Class        | Shape       | Dtype | Description
+:------ | :----------- | :---------- | :---- | :----------
+        | FeaturesDict |             |       |
+image   | Image        | (28, 28, 1) | uint8 |
+label   | ClassLabel   |             | int64 |
+
+*   **Supervised keys** (See
+    [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
+    `('image', 'label')`
+
+*   **Figure**
+    ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):
+    Not supported.
+
+*   **Examples**
+    ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):
+    Missing.
+
+*   **Citation**:
+
+```
+@article{yang2023medmnist,
+  title={Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification},
+  author={Yang, Jiancheng and Shi, Rui and Wei, Donglai and Liu, Zequan and Zhao, Lin and Ke, Bilian and Pfister, Hanspeter and Ni, Bingbing},
+  journal={Scientific Data},
+  volume={10},
+  number={1},
+  pages={41},
+  year={2023},
+  publisher={Nature Publishing Group UK London}
+}
+```
+