Search is not available for this dataset
image_id
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],
"bbox": [
[
282,
423,
115.5,
140.5
],
[
377,
52,
123.5,
139
],
[
225,
108,
107.5,
136
],
[
350,
216,
80.5,
129
],
[
179,
303,
80,
123
]
],
"category": [
15,
15,
9,
6,
10
]
} |
|
41 | 640 | 640 | {
"id": [
781,
782,
783,
784,
785,
786,
787,
788,
789,
790,
791,
792,
793,
794,
795,
796,
797,
798,
799,
800,
801,
802
],
"area": [
7065,
5712,
6562,
8635,
8530,
8700,
5876,
4484,
8295,
6979,
5376,
7875,
5618,
5731,
3850,
5997,
6063,
7812,
8366,
7158,
4661,
5934
],
"bbox": [
[
183,
373,
78.5,
90
],
[
318,
401,
84,
68
],
[
410,
422,
68,
96.5
],
[
275,
452,
78.5,
110
],
[
357,
472,
74.5,
114.5
],
[
313,
42,
116,
75
],
[
233,
78,
80.5,
73
],
[
387,
104,
59,
76
],
[
314,
126,
79,
105
],
[
173,
138,
70.5,
99
],
[
252,
152,
64,
84
],
[
399,
176,
75,
105
],
[
126,
190,
72.5,
77.5
],
[
324,
225,
87.5,
65.5
],
[
262,
244,
55,
70
],
[
402,
269,
80.5,
74.5
],
[
99,
268,
73.5,
82.5
],
[
183,
257,
72,
108.5
],
[
330,
304,
89,
94
],
[
256,
322,
69.5,
103
],
[
433,
342,
59,
79
],
[
114,
355,
69,
86
]
],
"category": [
13,
6,
3,
18,
14,
21,
20,
7,
4,
11,
17,
15,
10,
22,
7,
9,
16,
2,
1,
8,
19,
5
]
} |
Dataset Card for valentines-chocolate
** The original COCO dataset is stored at dataset.tar.gz**
Dataset Summary
valentines-chocolate
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.Imageobject 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/valentines-chocolate
Citation Information
@misc{ valentines-chocolate,
title = { valentines chocolate Dataset },
type = { Open Source Dataset },
author = { Roboflow 100 },
howpublished = { \url{ https://universe.roboflow.com/object-detection/valentines-chocolate } },
url = { https://universe.roboflow.com/object-detection/valentines-chocolate },
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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