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