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4,
5,
4,
4,
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,
1
]
} |
|
788 | 640 | 640 | {
"id": [
5024,
5025,
5026,
5027,
5028,
5029
],
"area": [
36738,
33339,
97520,
119446,
3729,
2728
],
"bbox": [
[
368,
95,
156,
235.5
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[
112,
91,
131,
254.5
],
[
104,
11,
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],
[
355,
19,
192.5,
620.5
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[
174,
10,
56.5,
66
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[
405,
18,
53.5,
51
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],
"category": [
5,
5,
4,
4,
1,
1
]
} |
|
893 | 640 | 640 | {
"id": [
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5727,
5728,
5729,
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5731
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"area": [
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12188,
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33391,
37234
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"bbox": [
[
411,
150,
94,
88.5
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[
486,
150,
99.5,
122.5
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[
354,
142,
133,
495
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[
485,
143,
115,
497
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[
368,
285,
113,
295.5
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[
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266,
103,
361.5
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],
"category": [
1,
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5,
5
]
} |
End of preview. Expand
in Dataset Viewer.
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 idimage
: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 overdataset["image"][0]
width
: the image widthheight
: the image heightobjects
: a dictionary containing bounding box metadata for the objects present on the imageid
: the annotation idarea
: the area of the bounding boxbbox
: 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 },
}"
Contributions
Thanks to @mariosasko for adding this dataset.
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