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sirunchained/fruit-dataset-annotation

FruitDet – Object Detection Dataset A community-driven fruit image dataset annotated for object detection, original repo.The images are real-world fruit photos collected from various environments. All images have been resized to 920×1080 pixels, and each fruit instance is labeled with a bounding box in YOLO format. Features Real-world images from diverse sources 19 fruit/vegetable categories, each containing 30 images All images resized to 920×1080 pixels… See the full description on the dataset page: https://huggingface.co/datasets/sirunchained/fruit-dataset-annotation.

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Dataset Card

FruitDet – Object Detection Dataset

A community-driven fruit image dataset annotated for object detection, original repo. The images are real-world fruit photos collected from various environments. All images have been resized to 920×1080 pixels, and each fruit instance is labeled with a bounding box in YOLO format.

Features

  • Real-world images from diverse sources
  • 19 fruit/vegetable categories, each containing 30 images
  • All images resized to 920×1080 pixels
  • YOLO‑format annotations: each image has a corresponding .txt file with bounding box coordinates
  • Dataset split into train (20 images), val (5 images), and test (5 images) per class
  • Each class folder includes a classes.txt file listing the category names (one per split)
  • Standardized naming convention ({class}_0000.jpg and {class}_0000.txt)
  • Clean folder structure, ready for YOLO-based frameworks (YOLOv5, YOLOv8, YOLOv9, etc.)

Annotation Format

Bounding boxes are stored in the standard YOLO format:

classid xcenter y_center width height

  • class_id – integer index of the class (0‑based)
  • x_center, y_center – normalized coordinates of the box center (0–1)
  • width, height – normalized dimensions of the box (0–1)

Each image file (e.g., apple_0000.jpg) has a corresponding label file with the same name (apple_0000.txt) placed in the same directory. Each class folder also contains a classes.txt file that maps class indices to class names.

Classes

  • Apple
  • Avocado
  • Banana
  • Blackberry
  • Carrot
  • Cherry
  • Grape
  • Kiwi
  • Lemon
  • Onion
  • Orange
  • Papaya
  • Peach
  • Pear
  • Pepper
  • Raspberry
  • Strawberry
  • Tomato

Repository Structure

The repository is organized with separate images/ and labels/ directories for each class, further split into train/, val/, and test/ subsets. Each split contains its own classes.txt file.

text
data/
├── apple/
│   ├── images/
│   │   ├── train/
│   │   │   ├── apple_0000.jpg
│   │   │   ├── apple_0001.jpg
│   │   │   └── ...
│   │   ├── val/
│   │   │   ├── apple_0025.jpg
│   │   │   └── ...
│   │   └── test/
│   │       ├── apple_0020.jpg
│   │       └── ...
│   └── labels/
│       ├── train/
│       │   ├── apple_0000.txt
│       │   ├── apple_0001.txt
│       │   ├── ...
│       │   └── classes.txt
│       ├── val/
│       │   ├── apple_0025.txt
│       │   ├── ...
│       │   └── classes.txt
│       └── test/
│           ├── apple_0020.txt
│           ├── ...
│           └── classes.txt
├── avocado/
│   ├── images/
│   │   ├── train/
│   │   ├── val/
│   │   └── test/
│   └── labels/
│       ├── train/
│       ├── val/
│       └── test/
├── banana/
│   └── ...
├── blackberry/
├── carrot/
├── cherry/
├── grape/
├── kiwi/
├── lemon/
├── onion/
├── orange/
├── papaya/
├── peach/
├── pear/
├── pepper/
├── raspberry/
├── strawberry/
└── tomato/

License

This dataset is licensed under CC BY 4.0.

You are free to:

  • Use
  • Modify
  • Redistribute
  • Use commercially

As long as proper attribution is provided.

Citation

If this dataset contributes to your research or project, please cite this repository.