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2014104149
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Authored by
Graduate
2020-11-23 18:16:11 +0900
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Commit
091bb35b36d579f45ddbbfc4910f359c5d065fc9
091bb35b
1 parent
d745b29d
Opencv.js face detection
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1 changed file
with
42 additions
and
47 deletions
flask/templates/index.html
flask/templates/index.html
View file @
091bb35
...
...
@@ -41,53 +41,48 @@ if (navigator.mediaDevices.getUserMedia){
}
</script>
<script>
function
openCvReady
()
{
cv
[
'onRuntimeInitialized'
]
=
()
=>
{
// do all your work here
let
video
=
document
.
getElementById
(
'videoElement'
);
let
src
=
new
cv
.
Mat
(
video
.
height
,
video
.
width
,
cv
.
CV_8UC4
);
let
dst
=
new
cv
.
Mat
(
video
.
height
,
video
.
width
,
cv
.
CV_8UC4
);
let
gray
=
new
cv
.
Mat
();
let
cap
=
new
cv
.
RectVector
();
let
classifier
=
new
cv
.
CascadeClassifier
();
classifier
.
load
(
"{{url_for('static', filename='js/haarcascade_frontalface_default.xml')}}"
)
const
FPS
=
30
;
function
processVideo
()
{
try
{
if
(
!
streaming
)
{
// clean and stop.
src
.
delete
();
dst
.
delete
();
gray
.
delete
();
faces
.
delete
();
classifier
.
delete
();
return
;
}
let
begin
=
Date
.
now
();
// start processing.
cap
.
read
(
src
);
src
.
copyTo
(
dst
);
cv
.
cvtColor
(
dst
,
gray
,
cv
.
COLOR_RGBA2GRAY
,
0
);
// detect faces.
classifier
.
detectMultiScale
(
gray
,
faces
,
1.1
,
3
,
0
);
// draw faces.
for
(
let
i
=
0
;
i
<
faces
.
size
();
++
i
)
{
let
face
=
faces
.
get
(
i
);
let
point1
=
new
cv
.
Point
(
face
.
x
,
face
.
y
);
let
point2
=
new
cv
.
Point
(
face
.
x
+
face
.
width
,
face
.
y
+
face
.
height
);
cv
.
rectangle
(
dst
,
point1
,
point2
,
[
255
,
0
,
0
,
255
]);
}
cv
.
imshow
(
'canvasOutput'
,
dst
);
// schedule the next one.
let
delay
=
1000
/
FPS
-
(
Date
.
now
()
-
begin
);
setTimeout
(
processVideo
,
delay
);
}
catch
(
err
)
{
utils
.
printError
(
err
);
}
// schedule the first one.
setTimeout
(
processVideo
,
0
);
};
}
let
video
=
document
.
getElementById
(
'videoElement'
);
let
src
=
new
cv
.
Mat
(
video
.
height
,
video
.
width
,
cv
.
CV_8UC4
);
let
dst
=
new
cv
.
Mat
(
video
.
height
,
video
.
width
,
cv
.
CV_8UC4
);
let
gray
=
new
cv
.
Mat
();
let
cap
=
new
cv
.
RectVector
();
let
classifier
=
new
cv
.
CascadeClassifier
();
classifier
.
load
(
"{{url_for('static', filename='js/haarcascade_frontalface_default.xml')}}"
)
const
FPS
=
30
;
function
processVideo
()
{
try
{
if
(
!
streaming
)
{
// clean and stop.
src
.
delete
();
dst
.
delete
();
gray
.
delete
();
faces
.
delete
();
classifier
.
delete
();
return
;
}
let
begin
=
Date
.
now
();
// start processing.
cap
.
read
(
src
);
src
.
copyTo
(
dst
);
cv
.
cvtColor
(
dst
,
gray
,
cv
.
COLOR_RGBA2GRAY
,
0
);
// detect faces.
classifier
.
detectMultiScale
(
gray
,
faces
,
1.1
,
3
,
0
);
// draw faces.
for
(
let
i
=
0
;
i
<
faces
.
size
();
++
i
)
{
let
face
=
faces
.
get
(
i
);
let
point1
=
new
cv
.
Point
(
face
.
x
,
face
.
y
);
let
point2
=
new
cv
.
Point
(
face
.
x
+
face
.
width
,
face
.
y
+
face
.
height
);
cv
.
rectangle
(
dst
,
point1
,
point2
,
[
255
,
0
,
0
,
255
]);
}
cv
.
imshow
(
'canvasOutput'
,
dst
);
// schedule the next one.
let
delay
=
1000
/
FPS
-
(
Date
.
now
()
-
begin
);
setTimeout
(
processVideo
,
delay
);
}
catch
(
err
)
{
utils
.
printError
(
err
);
}
// schedule the first one.
setTimeout
(
processVideo
,
0
);
</script>
</body>
</html>
...
...
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