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import
os
import
cv2
import
math
import
matplotlib.pyplot as pl
import
pandas as pd
from
PIL
import
Picture
import
numpy as np
def
face_detection(img):
faces
=
face_detector.detectMultiScale(img,
1.1
,
4
)
if
(
len
(faces) <
=
0
):
img_gray
=
cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
return
img, img_gray
else
:
X, Y, W, H
=
faces[
0
]
img
=
img[
int
(Y):
int
(Y
+
H),
int
(X):
int
(X
+
W)]
return
img, cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
def
trignometry_for_distance(a, b):
return
math.sqrt(((b[
0
]
-
a[
0
])
*
(b[
0
]
-
a[
0
]))
+
((b[
1
]
-
a[
1
])
*
(b[
1
]
-
a[
1
])))
def
Face_Alignement(img_path):
pl.imshow(cv2.imread(img_path)[:, :, ::
-
1
])
pl.present()
img_raw
=
cv2.imread(img_path).copy()
img, gray_img
=
face_detection(cv2.imread(img_path))
eyes
=
eye_detector.detectMultiScale(gray_img)
if
len
(eyes) >
=
2
:
eye
=
eyes[:,
2
]
container1
=
[]
for
i
in
vary
(
0
,
len
(eye)):
container
=
(eye[i], i)
container1.append(container)
df
=
pd.DataFrame(container1, columns
=
[
"length"
,
"idx"
]).sort_values(by
=
[
'length'
])
eyes
=
eyes[df.idx.values[
0
:
2
]]
eye_1
=
eyes[
0
]
eye_2
=
eyes[
1
]
if
eye_1[
0
] > eye_2[
0
]:
left_eye
=
eye_2
right_eye
=
eye_1
else
:
left_eye
=
eye_1
right_eye
=
eye_2
right_eye_center
=
(
int
(right_eye[
0
]
+
(right_eye[
2
]
/
2
)),
int
(right_eye[
1
]
+
(right_eye[
3
]
/
2
)))
right_eye_x
=
right_eye_center[
0
]
right_eye_y
=
right_eye_center[
1
]
cv2.circle(img, right_eye_center,
2
, (
255
,
0
,
0
),
3
)
left_eye_center
=
(
int
(left_eye[
0
]
+
(left_eye[
2
]
/
2
)),
int
(left_eye[
1
]
+
(left_eye[
3
]
/
2
)))
left_eye_x
=
left_eye_center[
0
]
left_eye_y
=
left_eye_center[
1
]
cv2.circle(img, left_eye_center,
2
, (
255
,
0
,
0
),
3
)
if
left_eye_y > right_eye_y:
print
(
"Rotate picture to clock path"
)
point_3rd
=
(right_eye_x, left_eye_y)
path
=
-
1
else
:
print
(
"Rotate to inverse clock path"
)
point_3rd
=
(left_eye_x, right_eye_y)
path
=
1
cv2.circle(img, point_3rd,
2
, (
255
,
0
,
0
),
2
)
a
=
trignometry_for_distance(left_eye_center,
point_3rd)
b
=
trignometry_for_distance(right_eye_center,
point_3rd)
c
=
trignometry_for_distance(right_eye_center,
left_eye_center)
cos_a
=
(b
*
b
+
c
*
c
-
a
*
a)
/
(
2
*
b
*
c)
angle
=
(np.arccos(cos_a)
*
180
)
/
math.pi
if
path
=
=
-
1
:
angle
=
90
-
angle
else
:
angle
=
-
(
90
-
angle)
new_img
=
Picture.fromarray(img_raw)
new_img
=
np.array(new_img.rotate(path
*
angle))
return
new_img
opencv_home
=
cv2.__file__
folders
=
opencv_home.cut up(os.path.sep)[
0
:
-
1
]
path
=
folders[
0
]
for
folder
in
folders[
1
:]:
path
=
path
+
"/"
+
folder
path_for_face
=
path
+
"/information/haarcascade_frontalface_default.xml"
path_for_eyes
=
path
+
"/information/haarcascade_eye.xml"
path_for_nose
=
path
+
"/information/haarcascade_mcs_nose.xml"
if
os.path.isfile(path_for_face) !
=
True
:
increase
ValueError(
"opencv shouldn't be put in pls set up utilizing pip set up opencv "
,
detector_path,
" violated."
)
face_detector
=
cv2.CascadeClassifier(path_for_face)
eye_detector
=
cv2.CascadeClassifier(path_for_eyes)
nose_detector
=
cv2.CascadeClassifier(path_for_nose)
test_set
=
[
"pic.png"
]
for
i
in
test_set:
alignedFace
=
Face_Alignement(i)
pl.imshow(alignedFace[:, :, ::
-
1
])
pl.present()
img, gray_img
=
face_detection(alignedFace)
pl.imshow(img[:, :, ::
-
1
])
pl.present()
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