--- viewer: false --- # 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("cj94/Boat_dataset") ``` ## Citation If you use this dataset in your research, please cite the following paper: