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2021-115
2021-115
Commits
5d129a81
Commit
5d129a81
authored
Jul 03, 2021
by
Maduranga Jayakody
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Update microwave detection
parent
75c922eb
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1
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34 additions
and
24 deletions
+34
-24
Child_detection/electricalObject-detection.py
Child_detection/electricalObject-detection.py
+34
-24
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Child_detection/electricalObject-detection.py
View file @
5d129a81
...
...
@@ -5,27 +5,30 @@ from imageai.Detection import ObjectDetection, VideoObjectDetection
import
sys
import
os
import
cv2
import
time
from
shapely.geometry
import
box
THRESHOLD_ITEM
=
0.5
THRESHOLD_PERSON
=
0.5
print
(
"Sharp Object Detection Begins"
)
execution_path
=
"input/"
Output_Path
=
"output/"
#print("Sharp Object Detection Begins")
detector
=
VideoObjectDetection
()
detector2
=
VideoObjectDetection
()
detector
=
VideoObjectDetection
()
detector2
=
VideoObjectDetection
()
detector
.
setModelTypeAsYOLOv3
()
detector
.
setModelPath
(
"../model/yolo.h5"
)
detector
.
CustomObjects
(
microwave
=
True
,
oven
=
True
,
person
=
True
)
detector
.
setModelPath
(
"../models/yolo.h5"
)
detector
.
loadModel
(
detection_speed
=
"fast"
)
detector
.
loadModel
()
detector2
.
setModelTypeAsRetinaNet
()
detector2
.
setModelPath
(
"model/resnet50_coco_best_v2.1.0.h5"
)
detector2
.
loadModel
()
def
forFrame
(
frame_number
,
output_array
,
output_count
,
returned_frame
):
microwave_count
=
0
...
...
@@ -39,7 +42,7 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
count
=
0
persons
=
[]
# YOLO Model (Person) and RetinaModel (Toaster, Microwave and Oven, Hair Dryer) both - Single Frame - Person
for
detection
in
output_array
:
print
(
detection
[
'name'
]
+
" - "
+
str
(
detection
[
'percentage_probability'
])
+
" - "
+
str
(
detection
[
'box_points'
]))
...
...
@@ -71,7 +74,8 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
powercords
.
append
(
detection
[
'box_points'
])
print
(
detection
[
"name"
],
" : "
,
detection
[
"percentage_probability"
],
" : "
,
detection
[
"box_points"
])
# Check if Child is in 100 Pixels to Left and 100 Pixels to Right of the Identified Object(s)
# Check if there is a person in view
if
(
len
(
persons
)
==
0
):
print
(
"There is no Person in the Room!"
)
...
...
@@ -80,33 +84,38 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
if
(
len
(
persons
)
>=
1
):
for
person
in
persons
:
# Create Person(minx, miny, maxx, maxy)
person_box
=
box
(
person
[
0
],
person
[
3
],
person
[
1
],
person
[
2
])
coords
=
person
coords
=
person
# (x1, x2, y1, y2)
x1
=
person
[
0
]
x2
=
person
[
1
]
y1
=
person
[
2
]
y2
=
person
[
3
]
person_midpoint
=
((
x1
+
x2
)
/
2
,
(
y1
+
y2
)
/
2
)
x_center
=
(
x1
+
x2
)
/
2
y_center
=
(
y1
+
y2
)
/
2
x_center
=
(
x1
+
x2
)
/
2
# Center X Coordinate
y_center
=
(
y1
+
y2
)
/
2
# Center Y Coordinate
# x1 => Left, x2 => Right, y1 => Top, y2 => Bottom
# (x1, y1) - Top Left
# (x2, y2) - Bottom Right
# (x2, y1) - Top Right
# (x1, y2) - Bottom Left
if
microwave_count
>
0
:
# Iterate each Microwave
for
microwave
in
microwaves
:
# Create Microwave(minx, miny, maxx, maxy)
microwave_box
=
box
(
microwave
[
0
]
+
50
,
microwave
[
3
]
+
50
,
microwave
[
1
]
+
50
,
microwave
[
2
]
+
50
)
e_x1
=
microwave
[
0
]
+
50
e_x2
=
microwave
[
1
]
+
50
e_y1
=
microwave
[
2
]
+
50
e_y2
=
microwave
[
3
]
+
50
# Check if Microwave Overlaps with the Person's Safety Boundary
# We Add 50px in all directions of the Bounding Box - Top+50, Bottom+50, Left+50, Right+50
e_x1
=
microwave
[
0
]
+
50
# Left
e_x2
=
microwave
[
1
]
+
50
# Right
e_y1
=
microwave
[
2
]
+
50
# Top
e_y2
=
microwave
[
3
]
+
50
# Bottom
overlap
=
False
# Check if the Microwave Oven is in the Persons Danger Region
if
(
microwave_box
.
intersection
(
person_box
)
!=
None
):
print
(
"Microwave/Oven - Person is in the Microwave/Oven's Danger Region!"
)
overlap
=
True
...
...
@@ -125,7 +134,8 @@ def forFrame(frame_number, output_array, output_count, returned_frame):
overlap
=
True
if
(
overlap
==
True
):
# If the Bounding Boxes Overlap at some point
# Calculate Distnace between center point of two boxes
microwave_midpoint
=
((
e_x1
+
e_x2
)
/
2
,
(
e_y1
+
e_y2
)
/
2
)
distance
=
((((
microwave_midpoint
[
0
]
-
person_midpoint
[
0
])
**
2
)
+
(
(
microwave_midpoint
[
1
]
-
person_midpoint
[
1
])
**
2
))
**
0.5
)
...
...
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