数据集:

Francesco/underwater-pipes-4ng4t

语言:

en

计算机处理:

monolingual

大小:

1K<n<10K

语言创建人:

found

批注创建人:

crowdsourced

源数据集:

original

其他:

rf100

许可:

cc
中文

Dataset Card for underwater-pipes-4ng4t

** The original COCO dataset is stored at dataset.tar.gz **

Dataset Summary

underwater-pipes-4ng4t

Supported Tasks and Leaderboards

  • object-detection : The dataset can be used to train a model for Object Detection.

Languages

English

Dataset Structure

Data Instances

A data point comprises an image and its object annotations.

{
  'image_id': 15,
  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640 at 0x2373B065C18>,
  'width': 964043,
  'height': 640,
  'objects': {
    'id': [114, 115, 116, 117], 
    'area': [3796, 1596, 152768, 81002],
    'bbox': [
      [302.0, 109.0, 73.0, 52.0],
      [810.0, 100.0, 57.0, 28.0],
      [160.0, 31.0, 248.0, 616.0],
      [741.0, 68.0, 202.0, 401.0]
    ], 
    'category': [4, 4, 0, 0]
  }
}

Data Fields

  • image : the image id
  • image : PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0]
  • 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.
Who are the annotators?

Annotators are Roboflow users

Additional Information

Licensing Information

See original homepage https://universe.roboflow.com/object-detection/underwater-pipes-4ng4t

Citation Information

@misc{ underwater-pipes-4ng4t,
    title = { underwater pipes 4ng4t Dataset },
    type = { Open Source Dataset },
    author = { Roboflow 100 },
    howpublished = { \url{ https://universe.roboflow.com/object-detection/underwater-pipes-4ng4t } },
    url = { https://universe.roboflow.com/object-detection/underwater-pipes-4ng4t },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { nov },
    note = { visited on 2023-03-29 },
}"

Contributions

Thanks to @mariosasko for adding this dataset.