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Related Pages
Related Symbols
ImageBoundingBoxes
ImageCases
ImageContainsQ
ImageContents
ImagePosition
HighlightImage
Classify
NetModel
Related Categories
Machine Learning
Image Processing
Computer Vision
Detect, Recognize & Highlight Objects in an Image
Example Notebook
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Start with an image:
I
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:
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i
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;
Get a summary of the content of the image:
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o
b
j
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C
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p
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B
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P
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{
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0
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1
1
3
}
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{
4
2
1
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1
3
2
,
3
0
0
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9
8
7
}
]
0
.
8
9
7
0
4
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d
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[
{
1
5
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1
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1
3
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{
3
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6
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1
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9
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4
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}
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0
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{
4
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1
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]
0
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9
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[
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,
{
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0
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,
{
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]
0
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2
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1
Using
I
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,
I
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get immediate access to different properties of detected objects:
I
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[
3
]
:
=
b
b
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x
=
I
m
a
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B
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O
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[
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=
c
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{
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[
{
2
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1
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1
1
3
}
,
{
4
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.
1
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,
3
0
0
.
9
8
7
}
]
,
R
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a
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g
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e
[
{
6
6
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3
6
3
1
,
1
4
6
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2
}
,
{
1
5
9
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8
6
9
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2
6
5
.
3
5
4
}
]
}
,
d
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{
1
5
9
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8
8
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1
5
.
8
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1
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}
,
{
3
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6
.
0
2
3
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1
5
9
.
4
2
}
]
}
,
d
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i
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{
R
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c
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[
{
1
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2
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4
6
,
0
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4
2
}
,
{
4
4
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3
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1
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2
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1
}
]
}
,
s
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{
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[
{
1
3
.
9
2
9
,
1
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0
.
6
0
7
}
,
{
1
2
3
.
1
6
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2
0
6
.
2
0
1
}
]
}
Highlight detected objects and their corresponding identification:
I
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4
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H
i
g
h
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i
g
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I
m
a
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e
i
,
K
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y
D
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o
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b
b
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x
,
d
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g
t
a
b
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C
O
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C
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P
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O
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[
4
]
=
See Also
YOLOR Trained on MS-COCO Data
YOLOX Trained on MS-COCO Data
YOLOImageLabel
Related Symbols
ImageBoundingBoxes
ImageCases
ImageContainsQ
ImageContents
ImagePosition
HighlightImage
Classify
NetModel
Publisher Information
Contributed by:
Wolfram Staff
