Search is not available for this dataset
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142,
320,
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72,
324,
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511,
334,
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340,
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[
540,
340,
52,
100.5
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[
71,
382,
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26
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[
225,
370,
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204,
399,
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[
490,
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421,
409,
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375,
400,
46,
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[
94,
426,
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38
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542,
437,
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135,
435,
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225,
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551,
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115,
465,
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33
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[
166,
468,
15.5,
29.5
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[
62,
468,
16,
31
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[
84,
489,
16.5,
28.5
],
[
499,
462,
52.5,
89
],
[
468,
504,
14.5,
23.5
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],
"category": [
2,
2,
2,
2,
2,
2,
2,
2,
2,
2,
1,
2,
2,
2,
1,
1,
1,
2,
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2,
2,
1,
2,
2,
1,
2,
2,
1,
2,
2,
2,
2,
2,
1
]
} |
|
15 | 640 | 640 | {
"id": [
774,
775,
776,
777,
778,
779,
780,
781,
782,
783,
784,
785,
786,
787,
788,
789,
790,
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792,
793,
794,
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798,
799,
800,
801,
802,
803,
804,
805,
806,
807,
808,
809,
810,
811,
812,
813
],
"area": [
1795,
1553,
2059,
1708,
1738,
1885,
1968,
1742,
2047,
1856,
1664,
2026,
1685,
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1455,
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2231,
1350,
1904,
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2171,
2080,
1330,
1534,
2057
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"bbox": [
[
218,
138,
31.5,
57
],
[
147,
145,
28.5,
54.5
],
[
489,
147,
35.5,
58
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[
438,
166,
33.5,
51
],
[
71,
166,
30.5,
57
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[
549,
207,
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[
173,
213,
32,
61.5
],
[
482,
223,
33.5,
52
],
[
96,
218,
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63
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[
520,
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58
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[
413,
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52
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[
139,
242,
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60.5
],
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367,
246,
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[
220,
254,
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64
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[
418,
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[
189,
301,
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[
382,
313,
36,
57
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[
120,
318,
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58
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[
557,
318,
36.5,
60.5
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[
90,
329,
32,
59.5
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[
225,
334,
33.5,
54.5
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[
420,
354,
36,
52
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[
145,
350,
33.5,
63
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[
527,
365,
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52
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[
369,
389,
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53.5
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[
78,
394,
32,
57
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[
413,
412,
30,
48.5
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[
198,
417,
31.5,
55.5
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[
98,
424,
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59.5
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[
472,
451,
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[
368,
448,
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[
555,
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53.5
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[
69,
464,
35.5,
59.5
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[
211,
467,
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[
162,
467,
32.5,
64
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[
418,
484,
28,
47.5
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[
513,
491,
29.5,
52
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[
132,
488,
34,
60.5
]
],
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2,
1,
2,
2,
2,
1,
2,
1,
2,
2,
2,
1,
2,
1,
1,
2,
1,
1,
1,
1,
2,
1,
2,
1,
1,
1,
2,
2,
2,
2,
1,
1,
2,
1,
2,
1,
1,
1,
1,
2
]
} |
Dataset Card for marbles
** The original COCO dataset is stored at dataset.tar.gz
**
Dataset Summary
marbles
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/marbles
Citation Information
@misc{ marbles,
title = { marbles Dataset },
type = { Open Source Dataset },
author = { Roboflow 100 },
howpublished = { \url{ https://universe.roboflow.com/object-detection/marbles } },
url = { https://universe.roboflow.com/object-detection/marbles },
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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