---
annotations_creators: []
language: en
size_categories:
- n<1K
task_categories:
- image-classification
task_ids: []
pretty_name: validation_photos
tags:
- fiftyone
- image
- image-classification
dataset_summary: '

These photos are used in the FiftyOne getting started webinar. The images have a prediction label where were generated by 
self-supervised classification through a OpenClip Model. 
https://github.com/thesteve0/fiftyone-getting-started/blob/main/5_generating_labels.py
They were then manually cleaned to produce the ground truth label. 
https://github.com/thesteve0/fiftyone-getting-started/blob/main/6_clean_labels.md

They are public domain photos taken from Flickr.
They will be used to evaluate classification models. They are purely for teaching purposes and are not recommended for any other use. 
 No other guarantees provided.  


  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 143 samples.


  ## Installation


  If you haven''t already, install FiftyOne:


  ```bash

  pip install -U fiftyone

  ```


  ## Usage


  ```python

  import fiftyone as fo

  from fiftyone.utils.huggingface import load_from_hub


  # Load the dataset

  # Note: other available arguments include ''max_samples'', etc

  dataset = load_from_hub("TheSteve0/getting-started-labeled-validation")


  # Launch the App

  session = fo.launch_app(dataset)

  ```

  '
---

# Dataset Card for validation_photos

<!-- Provide a quick summary of the dataset. -->





This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 143 samples.

## Installation

If you haven't already, install FiftyOne:

```bash
pip install -U fiftyone
```

## Usage

```python
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("TheSteve0/getting-started-labeled-validation")

# Launch the App
session = fo.launch_app(dataset)
```


## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->



- **Curated by:** [More Information Needed]
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- **Language(s) (NLP):** en
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### Dataset Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
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## Uses

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### Direct Use

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### Out-of-Scope Use

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## Dataset Structure

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## Dataset Creation

### Curation Rationale

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### Source Data

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#### Data Collection and Processing

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#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

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## Bias, Risks, and Limitations

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### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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