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viewer: false
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# Boat Dataset for Object Detection
## Overview
This dataset contains images of real & virtual boats for object detection tasks. It can be used to train and evaluate object detection models.
## Dataset Structure
### Data Instances
A data point comprises an image and its object annotations.
```
{'image_id': 0,
'image_path': 'images/0720_0937_2023-07-20-09-37-30_0_middle_color000220.jpg',
'width': 640,
'height': 480,
'objects': {'id': [1],
'area': [328.0],
'bbox': [[153.69000244140625,
101.76499938964844,
21.924999237060547,
14.972999572753906]],
'category': [8]}}
```
### Data Fields
- `image_id`: the image id
- `width`: the image width
- `height`: the image height
- `objects`: a dictionary containing bounding box metadata for the objects present on the image
- `id`: the annotation id
- `area`: the area of the bounding box
- `bbox`: the object's bounding box (in the [coco](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#coco) format)
- `category`: the object's category, with possible values including
- `BallonBoat` (0)
- `BigBoat` (1)
- `Boat` (2)
- `JetSki` (3)
- `Katamaran` (4)
- `SailBoat` (5)
- `SmallBoat` (6)
- `SpeedBoat` (7)
- `WAM_V` (8)
### Data Splits
- `Training dataset` (42833)
- `Real`
- `WAM_V` (2333)
- `Virtual`
- `BallonBoat` (4500)
- `BigBoat` (4500)
- `Boat` (4500)
- `JetSki` (4500)
- `Katamaran` (4500)
- `SailBoat` (4500)
- `SmallBoat` (4500)
- `SpeedBoat` (4500)
- `WAM_V` (4500)
- `Val dataset` (5400)
- `Real`
- `WAM_V` (900)
- `Virtual`
- `BallonBoat` (500)
- `BigBoat` (500)
- `Boat` (500)
- `JetSki` (500)
- `Katamaran` (500)
- `SailBoat` (500)
- `SmallBoat` (500)
- `SpeedBoat` (500)
- `WAM_V` (500)
## Usage
```
from datasets import load_dataset
dataset = load_dataset("zhuchi76/Boat_dataset")
```
## Citation
If you use this dataset in your research, please cite the following paper:
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