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



  ![image/png](dataset_preview.jpg)



  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 697 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("jamarks/apples")


  # Launch the App

  session = fo.launch_app(dataset)

  ```

  '
---

# Dataset Card for apples

Dataset ported and adapted from https://huggingface.co/datasets/Francesco/apples-fvpl5




![image/png](dataset_preview.jpg)


This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 697 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("jamarks/apples")

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


## Dataset Details

### Dataset Description

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

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## Uses

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### Direct Use

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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]

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**BibTeX:**

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## Glossary [optional]

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