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Frank Tjado Ihmels
medienverarbeitung17.projectmood
Commits
9ea9b986
Commit
9ea9b986
authored
Dec 19, 2017
by
tihmels
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.gitignore bearbeitet, und änderungen
parent
497b8e88
Changes
4
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4 changed files
with
18 additions
and
12 deletions
+18
-12
.gitignore
.gitignore
+4
-1
projectmood/face_detect.py
projectmood/face_detect.py
+6
-5
projectmood/process_model.py
projectmood/process_model.py
+7
-4
projectmood/sorted_set_facedetector.py
projectmood/sorted_set_facedetector.py
+1
-2
No files found.
.gitignore
View file @
9ea9b986
...
...
@@ -20,7 +20,10 @@ Icon
.Trashes
.VolumeIcon.icns
.com.apple.timemachine.donotpresent
basis_data/*
basis_data/dataset/*
basis_data/sorted_set/*
basis_data/source_emotion/*
basis_data/source_images/*
# Directories potentially created on remote AFP share
.AppleDB
...
...
projectmood/face_detect.py
View file @
9ea9b986
...
...
@@ -22,27 +22,28 @@ def normalize_face(face):
return
face
def
locate_faces
(
image
,
scaleFactor
=
1.4
,
minNeighbors
=
3
):
def
locate_faces
(
image
,
scaleFactor
=
1.4
,
minNeighbors
=
3
,
minSize
=
(
20
,
20
)):
minx
,
miny
=
minSize
face
=
faceDet_one
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
40
,
40
),
face
=
faceDet_one
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
minx
,
miny
),
flags
=
cv2
.
CASCADE_SCALE_IMAGE
)
if
len
(
face
)
==
1
:
return
face
face
=
faceDet_two
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
40
,
40
),
face
=
faceDet_two
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
minx
,
miny
),
flags
=
cv2
.
CASCADE_SCALE_IMAGE
)
if
len
(
face
)
==
1
:
return
face
face
=
faceDet_three
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
40
,
40
),
face
=
faceDet_three
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
minx
,
miny
),
flags
=
cv2
.
CASCADE_SCALE_IMAGE
)
if
len
(
face
)
==
1
:
return
face
face
=
faceDet_four
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
40
,
40
),
face
=
faceDet_four
.
detectMultiScale
(
image
,
scaleFactor
,
minNeighbors
,
minSize
=
(
minx
,
miny
),
flags
=
cv2
.
CASCADE_SCALE_IMAGE
)
if
len
(
face
)
==
1
:
...
...
projectmood/process_model.py
View file @
9ea9b986
...
...
@@ -12,7 +12,7 @@ logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)-8s %(m
args
=
sys
.
argv
# liest Input Parameter
logging
.
debug
(
'Fisherface training initialized'
)
file
=
open
(
"gray
_equalized
.csv"
,
"w"
)
file
=
open
(
"gray.csv"
,
"w"
)
def
_get_faces_from_emotion
(
emotion
):
"""
...
...
@@ -34,7 +34,8 @@ def image_preprocessing(image):
"""
img
=
cv2
.
imread
(
image
)
# open image
gray
=
cv2
.
cvtColor
(
img
,
cv2
.
COLOR_BGR2GRAY
)
# convert to grayscale
return
gray
equal
=
cv2
.
equalizeHist
(
gray
)
return
equal
def
make_sets
():
training_data
=
[]
...
...
@@ -85,11 +86,13 @@ fishface = cv2.face.FisherFaceRecognizer_create()
# Now run it
metascore
=
[]
for
i
in
range
(
0
,
2
0
):
for
i
in
range
(
0
,
1
0
):
correct
=
run_recognizer
()
file
.
write
(
"{}
\n
"
.
format
(
int
(
correct
)))
logging
.
debug
(
"{} : {}%"
.
format
(
i
,
int
(
correct
)))
file
.
write
(
"{}, {}"
.
format
(
i
,
int
(
correct
)))
metascore
.
append
(
correct
)
file
.
close
()
logging
.
debug
(
"{} iterations - {}% average
\n
"
.
format
(
len
(
metascore
),
np
.
mean
(
metascore
)))
...
...
projectmood/sorted_set_facedetector.py
View file @
9ea9b986
...
...
@@ -14,7 +14,6 @@ totalFiles: int = 0
totalFaces
:
int
=
0
undetected
:
list
=
[]
def
detect_faces
(
emotion
):
files
=
glob
.
glob
(
'basis_data/sorted_set/{}/*'
.
format
(
emotion
))
# Holt alle Dateien zu einer Emotion aus dem sorted_set
...
...
@@ -29,7 +28,7 @@ def detect_faces(emotion):
frame
=
cv2
.
imread
(
f
)
# Open image
gray
=
cv2
.
cvtColor
(
frame
,
cv2
.
COLOR_BGR2GRAY
)
# Convert image to grayscale
facefeatures
=
locate_faces
(
gray
,
1.
05
,
10
)
facefeatures
=
locate_faces
(
gray
,
1.
1
,
10
,
(
40
,
40
)
)
if
facefeatures
is
''
:
undetected
.
append
(
f
)
...
...
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