Search is not available for this dataset
image_id
int64
0
102
image
imagewidth (px)
640
640
width
int32
640
640
height
int32
640
640
objects
sequence
89
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{ "id": [ 414, 415 ], "area": [ 18113, 3408 ], "bbox": [ [ 313, 137, 168.5, 107.5 ], [ 76, 371, 67.5, 50.5 ] ], "category": [ 1, 1 ] }
67
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{ "id": [ 482, 483, 484, 485, 486, 487, 488 ], "area": [ 796, 2320, 8134, 4606, 36223, 6496, 615 ], "bbox": [ [ 384, 91, 24.5, 32.5 ], [ 449, 184, 59.5, 39 ], [ 0, 0, 166, 49 ], [ 51, 298, 94, 49 ], [ 332, 300, 178, 203.5 ], [ 531, 450, 64, 101.5 ], [ 188, 613, 41, 15 ] ], "category": [ 1, 1, 1, 1, 1, 1, 1 ] }
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64
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47
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{ "id": [ 350, 351, 352, 353, 354, 355 ], "area": [ 371, 1937, 1485, 3480, 3375, 6533 ], "bbox": [ [ 197, 281, 27.5, 13.5 ], [ 133, 278, 61.5, 31.5 ], [ 483, 291, 67.5, 22 ], [ 72, 425, 87, 40 ], [ 0, 25, 50, 67.5 ], [ 8, 593, 139, 47 ] ], "category": [ 1, 1, 1, 1, 1, 1 ] }
54
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{ "id": [ 411, 412, 413 ], "area": [ 2340, 2946, 3675 ], "bbox": [ [ 279, 230, 45, 52 ], [ 318, 280, 35.5, 83 ], [ 141, 468, 52.5, 70 ] ], "category": [ 1, 1, 1 ] }
12
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{ "id": [ 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 ], "area": [ 4828, 2525, 3445, 19788, 4727, 20880, 16767, 17459, 9509, 11281 ], "bbox": [ [ 307, 91, 55.5, 87 ], [ 524, 135, 45.5, 55.5 ], [ 558, 138, 53, 65 ], [ 403, 131, 145.5, 136 ], [ 217, 190, 58, 81.5 ], [ 86, 233, 130.5, 160 ], [ 532, 340, 103.5, 162 ], [ 357, 358, 110.5, 158 ], [ 541, 27, 91, 104.5 ], [ 371, 30, 103.5, 109 ] ], "category": [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ] }
59
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{ "id": [ 434, 435, 436, 437, 438 ], "area": [ 4987, 3630, 5406, 2482, 24219 ], "bbox": [ [ 506, 185, 75, 66.5 ], [ 530, 255, 66, 55 ], [ 324, 383, 62.5, 86.5 ], [ 448, 433, 68, 36.5 ], [ 70, 373, 138, 175.5 ] ], "category": [ 1, 1, 1, 1, 1 ] }

Dataset Card for secondary-chains

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

Dataset Summary

secondary-chains

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/secondary-chains

Citation Information

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

Contributions

Thanks to @mariosasko for adding this dataset.

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