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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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