Datasets:

Francesco
/

construction-safety-gsnvb

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457	640	640	{ "id": [ 2889, 2890, 2891 ], "area": [ 676, 2237, 8591 ], "bbox": [ [ 91, 281, 16.5, 41 ], [ 80, 315, 25, 89.5 ], [ 75, 282, 39.5, 217.5 ] ], "category": [ 1, 5, 4 ] }
322	640	640	{ "id": [ 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970 ], "area": [ 18887, 107032, 104832, 120277, 63176, 66470, 57340, 13754, 12587 ], "bbox": [ [ 120, 33, 125.5, 150.5 ], [ 227, 1,...
248	640	640	{ "id": [ 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571 ], "area": [ 5240, 4757, 31906, 90046, 30500, 27306, 84165, 81462, 5148 ], "bbox": [ [ 499, 129, 68.5, 76.5 ], [ 324, 149, ...
631	640	640	{ "id": [ 3993, 3994, 3995, 3996, 3997, 3998, 3999, 4000, 4001, 4002, 4003, 4004, 4005, 4006, 4007, 4008, 4009, 4010, 4011 ], "area": [ 1619, 3100, 780, 512, 630, 1029, 1382, 1375, 4758, 3150, 4...
869	640	640	{ "id": [ 5617, 5618, 5619 ], "area": [ 81692, 40481, 15612 ], "bbox": [ [ 264, 56, 205, 398.5 ], [ 275, 243, 190.5, 212.5 ], [ 273, 65, 121.5, 128.5 ] ], "category": [ 4, 3, ...
788	640	640	{ "id": [ 5024, 5025, 5026, 5027, 5028, 5029 ], "area": [ 36738, 33339, 97520, 119446, 3729, 2728 ], "bbox": [ [ 368, 95, 156, 235.5 ], [ 112, 91, 131, 254.5 ], [ 104, 11, 160,...
893	640	640	{ "id": [ 5726, 5727, 5728, 5729, 5730, 5731 ], "area": [ 8319, 12188, 65835, 57155, 33391, 37234 ], "bbox": [ [ 411, 150, 94, 88.5 ], [ 486, 150, 99.5, 122.5 ], [ 354, 142, 13...

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Dataset Card for construction-safety-gsnvb

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

Dataset Summary

construction-safety-gsnvb

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/construction-safety-gsnvb

Citation Information

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