---
pretty_name: Fruits (Apples, Carrots, Oranges) – YOLO Annotations
tags:
- computer-vision
- object-detection
- yolo
- fruits
task_categories:
- object-detection
annotations_creators:
- expert-generated
language:
- en
license: cc-by-4.0
size_categories:
- 1K<n<10K
---

# Fruits Dataset (Apples / Carrots / Oranges)

This dataset contains **160 original images** of apples, carrots, and oranges, captured in different scenarios.  
The pictures include **variations in angles, distances, lighting conditions, shadows, quantities, and surfaces**, providing dynamic and diverse samples for training.  

Annotations were created using **Label Studio** and are formatted for direct use with **YOLO** object detection models.  

---

## Structure

The dataset is organized under the `fruitsdata/` folder:

fruitsdata/ </br>
├── images/ # original fruit photos (.jpg) </br>
├── labels/ # YOLO annotation files (.txt, one per image) </br>
├── classes.txt # class list (apple, carrot, orange) </br>
└── notes.json # dataset metadata and notes </br>
---

## How to Use

### Option A — Use my notebook (recommended)
1. Download this dataset.  
2. Run the Jupyter Notebook available on GitHub, which performs **train/val splitting and training**:  
   👉 [Fruit Detection Model with YOLO](https://github.com/Johnatanvq/fruit_detection_model)  

### Option B — Manual usage
If you want to manually prepare a YOLO-compatible dataset, split `images/` and `labels/` into `train/` and `val/`, then create a `dataset.yaml`.  

---

## Annotation Format (YOLO)

Each line in `labels/*.txt` follows:
class_id x_center y_center width height 

---

## Classes

1. apple  
2. carrot  
3. orange  

---

## License

This dataset is released under the [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.  
You are free to **share, use, and adapt** the dataset, including for commercial purposes, as long as you provide appropriate attribution.  

### Copyright & Attribution
The images and annotations are original work created by the author.  

If you use this dataset, please cite it as:  
> **Fruits (Apples/Carrots/Oranges) – YOLO Annotations**, by **Johnatanvq**, licensed under CC-BY 4.0.  

---

## Notes
- The dataset is intentionally compact (**160 images**) but highly varied.  
- Designed for quick prototyping and benchmarking object detection models.  
- Optimized for YOLO but can be adapted to other frameworks.