Wolfram.com
WolframAlpha.com
WolframCloud.com
Wolfram Language
Example Repository
Ready-to-use examples for the Wolfram Language
Primary Navigation
Categories
Astronomy
Audio Processing
Calculus
Cellular Automata
Chemistry
Complex Systems
Computer Science
Computer Vision
Control Systems
Creative Arts
Data Science
Engineering
Finance & Economics
Finite Element Method
Food & Nutrition
Geography
Geometry
Graphs & Networks
Image Processing
Life Sciences
Machine Learning
Mathematics
Optimization
Physics
Puzzles and Recreation
Quantum Computation
Signal Processing
Social Sciences
System Modeling
Text & Language Processing
Time-Related Computation
Video Processing
Visualization & Graphics
Alphabetical List
Submit a New Resource
Learn More about
Wolfram Language
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
Open in Cloud
Download Notebook
Start with an image:
I
n
[
1
]
:
=
i
=
;
Get a summary of the content of the image:
I
n
[
2
]
:
=
o
b
j
e
c
t
s
=
I
m
a
g
e
C
o
n
t
e
n
t
s
[
i
,
A
c
c
e
p
t
a
n
c
e
T
h
r
e
s
h
o
l
d
.
2
5
]
O
u
t
[
2
]
=
I
m
a
g
e
C
o
n
c
e
p
t
B
o
u
n
d
i
n
g
B
o
x
P
r
o
b
a
b
i
l
i
t
y
c
u
p
R
e
c
t
a
n
g
l
e
[
{
2
8
2
.
1
2
8
,
1
0
8
.
1
1
3
}
,
{
4
2
1
.
1
3
2
,
3
0
0
.
9
8
7
}
]
0
.
8
9
7
0
4
7
d
o
n
u
t
R
e
c
t
a
n
g
l
e
[
{
1
5
9
.
8
8
5
,
1
5
.
8
5
1
3
}
,
{
3
0
6
.
0
2
3
,
1
5
9
.
4
2
}
]
0
.
8
4
1
8
6
9
d
i
n
i
n
g
t
a
b
l
e
R
e
c
t
a
n
g
l
e
[
{
1
7
.
2
9
4
6
,
0
.
9
6
1
7
4
2
}
,
{
4
4
7
.
9
3
8
,
3
0
1
.
2
7
1
}
]
0
.
9
0
5
4
9
3
c
u
p
R
e
c
t
a
n
g
l
e
[
{
6
6
.
3
6
3
1
,
1
4
6
.
9
3
2
}
,
{
1
5
9
.
8
6
9
,
2
6
5
.
3
5
4
}
]
0
.
7
4
2
7
8
s
p
o
o
n
R
e
c
t
a
n
g
l
e
[
{
1
3
.
9
2
9
,
1
3
0
.
6
0
7
}
,
{
1
2
3
.
1
6
,
2
0
6
.
2
0
1
}
]
0
.
2
8
1
3
1
Using
I
m
a
g
e
C
a
s
e
s
,
I
m
a
g
e
B
o
u
n
d
i
n
g
B
o
x
e
s
,
I
m
a
g
e
P
o
s
i
t
i
o
n
get immediate access to different properties of detected objects:
I
n
[
3
]
:
=
b
b
o
x
=
I
m
a
g
e
B
o
u
n
d
i
n
g
B
o
x
e
s
[
i
,
A
c
c
e
p
t
a
n
c
e
T
h
r
e
s
h
o
l
d
.
2
5
]
O
u
t
[
3
]
=
c
u
p
{
R
e
c
t
a
n
g
l
e
[
{
2
8
2
.
1
2
8
,
1
0
8
.
1
1
3
}
,
{
4
2
1
.
1
3
2
,
3
0
0
.
9
8
7
}
]
,
R
e
c
t
a
n
g
l
e
[
{
6
6
.
3
6
3
1
,
1
4
6
.
9
3
2
}
,
{
1
5
9
.
8
6
9
,
2
6
5
.
3
5
4
}
]
}
,
d
o
n
u
t
{
R
e
c
t
a
n
g
l
e
[
{
1
5
9
.
8
8
5
,
1
5
.
8
5
1
3
}
,
{
3
0
6
.
0
2
3
,
1
5
9
.
4
2
}
]
}
,
d
i
n
i
n
g
t
a
b
l
e
{
R
e
c
t
a
n
g
l
e
[
{
1
7
.
2
9
4
6
,
0
.
9
6
1
7
4
2
}
,
{
4
4
7
.
9
3
8
,
3
0
1
.
2
7
1
}
]
}
,
s
p
o
o
n
{
R
e
c
t
a
n
g
l
e
[
{
1
3
.
9
2
9
,
1
3
0
.
6
0
7
}
,
{
1
2
3
.
1
6
,
2
0
6
.
2
0
1
}
]
}
Highlight detected objects and their corresponding identification:
I
n
[
4
]
:
=
H
i
g
h
l
i
g
h
t
I
m
a
g
e
i
,
K
e
y
D
r
o
p
b
b
o
x
,
d
i
n
i
n
g
t
a
b
l
e
C
O
N
C
E
P
T
O
u
t
[
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
