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Kaohsiung_Port_dataset_2024

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train · 601 rows

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Kaohsiung Port Dataset for Object Detection

Overview

This dataset contains images of real Kaohsiung Port for object detection tasks. It can be used to train and evaluate object detection models.

Demo Example 1:

The video is available on video/1107_kaohsiung_port1_out.mp4 or by clicking the image youtube link.

Demo Example 2:

The video is available on video/1107_kaohsiung_port2_out.mp4 or by clicking the image youtube link.

Dataset Structure

Data Instances

A data point comprises an image and its object annotations.

{
  'image_id': 1, 
  'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x800 at 0x7C9E805B86D0>, 
  'image_path': 'images/output_video_path2_305.png', 
  'width': 800, 
  'height': 800, 
  'objects': 
    {
      'id': [1], 
      'area': [1496.0], 
      'bbox': [[430.0, 367.0, 44.0, 34.0]], 
      'category': [0]
    }
}

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 format)
- category: the object's category, with possible values including
  - Civilian_ship (0)
  - Buoy (1)
  - Warship (2)
  - Coast_guard (3)

Data Splits

Training dataset 601 images (1679 annotations)
- Civilian_ship (1188)
- Buoy (265)
- Warship (158)
- Coast_guard (68)
Val dataset 150 images (391 annotations)
- Civilian_ship (262)
- Buoy (59)
- Warship (47)
- Coast_guard (23)

Usage

from datasets import load_dataset

dataset = load_dataset("ARG-NCTU/Kaohsiung_Port_dataset_2024")

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