Automated documentation update

PiperOrigin-RevId: 278690756

Author: Conchylicultor

docs/catalog/_toc.yaml

@@ -92,6 +92,8 @@ toc:
     title: kmnist
   - path: /datasets/catalog/lfw
     title: lfw
+  - path: /datasets/catalog/lost_and_found
+    title: lost_and_found
   - path: /datasets/catalog/lsun
     title: lsun
   - path: /datasets/catalog/malaria

docs/catalog/lost_and_found.md

@@ -0,0 +1,172 @@
+<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="lost_and_found" />
+  <meta itemprop="description" content="&#10;The LostAndFound Dataset addresses the problem of detecting unexpected small obstacles on&#10;the road often caused by lost cargo. The dataset comprises 112 stereo video sequences&#10;with 2104 annotated frames (picking roughly every tenth frame from the recorded data).&#10;&#10;The dataset is designed analogous to the 'Cityscapes' dataset. The datset provides:&#10;- stereo image pairs in either 8 or 16 bit color resolution&#10;- precomputed disparity maps&#10;- coarse semantic labels for objects and street&#10;&#10;Descriptions of the labels are given here: http://www.6d-vision.com/laf_table.pdf&#10;&#10;&#10;To use this dataset:&#10;&#10;```python&#10;import tensorflow_datasets as tfds&#10;&#10;ds = tfds.load('lost_and_found', split='train')&#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/lost_and_found" />
+  <meta itemprop="sameAs" content="http://www.6d-vision.com/lostandfounddataset" />
+  <meta itemprop="citation" content="&#10;@inproceedings{pinggera2016lost,&#10;  title={Lost and found: detecting small road hazards for self-driving vehicles},&#10;  author={Pinggera, Peter and Ramos, Sebastian and Gehrig, Stefan and Franke, Uwe and Rother, Carsten and Mester, Rudolf},&#10;  booktitle={2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},&#10;  year={2016}&#10;}&#10;" />
+</div>
+
+# `lost_and_found`
+
+*   URL:
+    [http://www.6d-vision.com/lostandfounddataset](http://www.6d-vision.com/lostandfounddataset)
+*   `DatasetBuilder`:
+    [`tfds.image.lost_and_found.LostAndFound`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/image/lost_and_found.py)
+
+`lost_and_found` is configured with
+`tfds.image.lost_and_found.LostAndFoundConfig` and has the following
+configurations predefined (defaults to the first one):
+
+*   `semantic_segmentation` (`v1.0.0`) (`Size: 5.44 GiB`): Lost and Found
+    semantic segmentation dataset.
+
+*   `stereo_disparity` (`v1.0.0`) (`Size: 12.16 GiB`): Lost and Found stereo
+    images and disparity maps.
+
+*   `full` (`v1.0.0`) (`Size: 12.19 GiB`): Full Lost and Found dataset.
+
+*   `full_16bit` (`v1.0.0`) (`Size: 34.90 GiB`): Full Lost and Found dataset.
+
+## `lost_and_found/semantic_segmentation`
+
+Lost and Found semantic segmentation dataset.
+
+Versions:
+
+*   **`1.0.0`** (default):
+
+### Statistics
+
+Split | Examples
+:---- | -------:
+ALL   | 2,239
+TEST  | 1,203
+TRAIN | 1,036
+
+### Features
+
+```python
+FeaturesDict({
+    'image_id': Text(shape=(), dtype=tf.string),
+    'image_left': Image(shape=(1024, 2048, 3), dtype=tf.uint8),
+    'segmentation_label': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+})
+```
+
+### Homepage
+
+*   [http://www.6d-vision.com/lostandfounddataset](http://www.6d-vision.com/lostandfounddataset)
+
+## `lost_and_found/stereo_disparity`
+
+Lost and Found stereo images and disparity maps.
+
+Versions:
+
+*   **`1.0.0`** (default):
+
+### Statistics
+
+Split | Examples
+:---- | -------:
+ALL   | 2,239
+TEST  | 1,203
+TRAIN | 1,036
+
+### Features
+
+```python
+FeaturesDict({
+    'disparity_map': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+    'image_id': Text(shape=(), dtype=tf.string),
+    'image_left': Image(shape=(1024, 2048, 3), dtype=tf.uint8),
+    'image_right': Image(shape=(1024, 2048, 3), dtype=tf.uint8),
+})
+```
+
+### Homepage
+
+*   [http://www.6d-vision.com/lostandfounddataset](http://www.6d-vision.com/lostandfounddataset)
+
+## `lost_and_found/full`
+
+Full Lost and Found dataset.
+
+Versions:
+
+*   **`1.0.0`** (default):
+
+### Statistics
+
+Split | Examples
+:---- | -------:
+ALL   | 2,239
+TEST  | 1,203
+TRAIN | 1,036
+
+### Features
+
+```python
+FeaturesDict({
+    'disparity_map': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+    'image_id': Text(shape=(), dtype=tf.string),
+    'image_left': Image(shape=(1024, 2048, 3), dtype=tf.uint8),
+    'image_right': Image(shape=(1024, 2048, 3), dtype=tf.uint8),
+    'instance_id': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+    'segmentation_label': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+})
+```
+
+### Homepage
+
+*   [http://www.6d-vision.com/lostandfounddataset](http://www.6d-vision.com/lostandfounddataset)
+
+## `lost_and_found/full_16bit`
+
+Full Lost and Found dataset.
+
+Versions:
+
+*   **`1.0.0`** (default):
+
+### Statistics
+
+Split | Examples
+:---- | -------:
+ALL   | 2,239
+TEST  | 1,203
+TRAIN | 1,036
+
+### Features
+
+```python
+FeaturesDict({
+    'disparity_map': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+    'image_id': Text(shape=(), dtype=tf.string),
+    'image_left': Image(shape=(1024, 2048, 3), dtype=tf.uint8),
+    'image_right': Image(shape=(1024, 2048, 3), dtype=tf.uint8),
+    'instance_id': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+    'segmentation_label': Image(shape=(1024, 2048, 1), dtype=tf.uint8),
+})
+```
+
+### Homepage
+
+*   [http://www.6d-vision.com/lostandfounddataset](http://www.6d-vision.com/lostandfounddataset)
+
+## Citation
+
+```
+@inproceedings{pinggera2016lost,
+  title={Lost and found: detecting small road hazards for self-driving vehicles},
+  author={Pinggera, Peter and Ramos, Sebastian and Gehrig, Stefan and Franke, Uwe and Rother, Carsten and Mester, Rudolf},
+  booktitle={2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
+  year={2016}
+}
+```
+
+--------------------------------------------------------------------------------

docs/catalog/overview.md

@@ -80,6 +80,7 @@ np_datasets = tfds.as_numpy(datasets)
     *   [`imagenet_resized`](imagenet_resized.md)
     *   [`kmnist`](kmnist.md)
     *   [`lfw`](lfw.md)
+    *   [`lost_and_found`](lost_and_found.md)
     *   [`lsun`](lsun.md)
     *   [`malaria`](malaria.md)
     *   [`mnist`](mnist.md)