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体验新版 GitCode,发现更多精彩内容 >>
提交
e053c8c9
编写于
6月 20, 2018
作者:
B
baiyfbupt
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
code clean
上级
de4504d6
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
69 addition
and
95 deletion
+69
-95
fluid/face_detection/infer.py
fluid/face_detection/infer.py
+69
-92
fluid/face_detection/reader.py
fluid/face_detection/reader.py
+0
-3
未找到文件。
fluid/face_detection/infer.py
浏览文件 @
e053c8c9
...
...
@@ -3,7 +3,7 @@ import time
import
numpy
as
np
import
argparse
import
functools
import
datetime
import
cv2
from
PIL
import
Image
from
PIL
import
ImageDraw
...
...
@@ -12,7 +12,6 @@ import paddle.fluid as fluid
import
reader
from
pyramidbox
import
PyramidBox
from
utility
import
add_arguments
,
print_arguments
from
paddle.fluid.framework
import
Program
,
Parameter
,
default_main_program
,
Variable
parser
=
argparse
.
ArgumentParser
(
description
=
__doc__
)
add_arg
=
functools
.
partial
(
add_arguments
,
argparser
=
parser
)
# yapf: disable
...
...
@@ -21,8 +20,6 @@ add_arg('use_pyramidbox', bool, False, "Whether use PyramidBox model.")
add_arg
(
'confs_threshold'
,
float
,
0.25
,
"Confidence threshold to draw bbox."
)
add_arg
(
'image_path'
,
str
,
''
,
"The data root path."
)
add_arg
(
'model_dir'
,
str
,
''
,
"The model path."
)
add_arg
(
'resize_h'
,
int
,
0
,
"The resized image height."
)
add_arg
(
'resize_w'
,
int
,
0
,
"The resized image height."
)
# yapf: enable
...
...
@@ -115,19 +112,7 @@ def bbox_vote(det):
return
dets
def
detect_face
(
image
,
image_shape
,
raw_image
,
shrink
):
num_classes
=
2
place
=
fluid
.
CUDAPlace
(
0
)
if
args
.
use_gpu
else
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
if
shrink
!=
1
:
image
=
image
.
resize
((
int
(
image_shape
[
2
]
*
shrink
),
int
(
image_shape
[
1
]
*
shrink
)),
Image
.
ANTIALIAS
)
image_shape
=
[
image_shape
[
0
],
int
(
image_shape
[
1
]
*
shrink
),
int
(
image_shape
[
2
]
*
shrink
)
]
print
"image_shape:"
,
image_shape
def
image_preprocess
(
image
):
img
=
np
.
array
(
image
)
# HWC to CHW
if
len
(
img
.
shape
)
==
3
:
...
...
@@ -141,47 +126,54 @@ def detect_face(image, image_shape, raw_image, shrink):
img
=
img
*
0.007843
img
=
[
img
]
img
=
np
.
array
(
img
)
return
img
def
detect_face
(
image
,
shrink
):
image_shape
=
[
3
,
image
.
size
[
1
],
image
.
size
[
0
]]
num_classes
=
2
place
=
fluid
.
CUDAPlace
(
0
)
if
args
.
use_gpu
else
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
if
shrink
!=
1
:
image
=
image
.
resize
((
int
(
image_shape
[
2
]
*
shrink
),
int
(
image_shape
[
1
]
*
shrink
)),
Image
.
ANTIALIAS
)
image_shape
=
[
image_shape
[
0
],
int
(
image_shape
[
1
]
*
shrink
),
int
(
image_shape
[
2
]
*
shrink
)
]
print
"image_shape:"
,
image_shape
img
=
image_preprocess
(
image
)
scope
=
fluid
.
core
.
Scope
()
m
odel
_program
=
fluid
.
Program
()
m
ain
_program
=
fluid
.
Program
()
startup_program
=
fluid
.
Program
()
with
fluid
.
scope_guard
(
scope
):
with
fluid
.
unique_name
.
guard
():
with
fluid
.
program_guard
(
m
odel
_program
,
startup_program
):
with
fluid
.
program_guard
(
m
ain
_program
,
startup_program
):
fetches
=
[]
network
=
PyramidBox
(
image_shape
,
num_classes
,
sub_network
=
args
.
use_pyramidbox
,
is_infer
=
True
)
infer_program
,
nmsed_out
=
network
.
infer
()
infer_program
,
nmsed_out
=
network
.
infer
(
main_program
)
fetches
=
[
nmsed_out
]
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
network
.
feeds
())
fluid
.
io
.
load_persistables
(
exe
,
args
.
model_dir
,
main_program
=
model_program
)
#fluid.io.load_vars(exe, args.model_dir, predicate=if_exist)
exe
,
args
.
model_dir
,
main_program
=
main_program
)
detection
,
=
exe
.
run
(
infer_program
,
feed
=
feeder
.
feed
([
img
])
,
feed
=
{
'image'
:
img
}
,
fetch_list
=
fetches
,
return_numpy
=
False
)
detection
=
np
.
array
(
detection
)
# layout: xmin, ymin, xmax. ymax, score
det_conf
=
detection
[:,
1
]
if
args
.
resize_h
!=
0
and
args
.
resize_w
!=
0
:
det_xmin
=
raw_image
.
size
[
0
]
*
detection
[:,
2
]
det_ymin
=
raw_image
.
size
[
1
]
*
detection
[:,
3
]
det_xmax
=
raw_image
.
size
[
0
]
*
detection
[:,
4
]
det_ymax
=
raw_image
.
size
[
1
]
*
detection
[:,
5
]
else
:
det_xmin
=
image_shape
[
2
]
*
detection
[:,
2
]
/
shrink
det_ymin
=
image_shape
[
1
]
*
detection
[:,
3
]
/
shrink
det_xmax
=
image_shape
[
2
]
*
detection
[:,
4
]
/
shrink
det_ymax
=
image_shape
[
1
]
*
detection
[:,
5
]
/
shrink
det_xmin
=
image_shape
[
2
]
*
detection
[:,
2
]
/
shrink
det_ymin
=
image_shape
[
1
]
*
detection
[:,
3
]
/
shrink
det_xmax
=
image_shape
[
2
]
*
detection
[:,
4
]
/
shrink
det_ymax
=
image_shape
[
1
]
*
detection
[:,
5
]
/
shrink
det
=
np
.
column_stack
((
det_xmin
,
det_ymin
,
det_xmax
,
det_ymax
,
det_conf
))
keep_index
=
np
.
where
(
det
[:,
4
]
>=
0
)[
0
]
...
...
@@ -189,40 +181,37 @@ def detect_face(image, image_shape, raw_image, shrink):
return
det
def
flip_test
(
image
,
image_shape
,
raw_image
,
shrink
):
def
flip_test
(
image
,
shrink
):
image
=
image
.
transpose
(
Image
.
FLIP_LEFT_RIGHT
)
det_f
=
detect_face
(
image
,
image_shape
,
raw_image
,
shrink
)
det_f
=
detect_face
(
image
,
shrink
)
det_t
=
np
.
zeros
(
det_f
.
shape
)
det_t
[:,
0
]
=
raw_
image
.
size
[
0
]
-
det_f
[:,
2
]
det_t
[:,
0
]
=
image
.
size
[
0
]
-
det_f
[:,
2
]
det_t
[:,
1
]
=
det_f
[:,
1
]
det_t
[:,
2
]
=
raw_
image
.
size
[
0
]
-
det_f
[:,
0
]
det_t
[:,
2
]
=
image
.
size
[
0
]
-
det_f
[:,
0
]
det_t
[:,
3
]
=
det_f
[:,
3
]
det_t
[:,
4
]
=
det_f
[:,
4
]
return
det_t
def
multi_scale_test
(
image
,
image_shape
,
raw_image
,
max_im
_shrink
):
def
multi_scale_test
(
image
,
max
_shrink
):
# shrink detecting and shrink only detect big face
st
=
0.5
if
max_
im_shrink
>=
0.75
else
0.5
*
max_im
_shrink
det_s
=
detect_face
(
image
,
image_shape
,
raw_image
,
st
)
st
=
0.5
if
max_
shrink
>=
0.75
else
0.5
*
max
_shrink
det_s
=
detect_face
(
image
,
st
)
index
=
np
.
where
(
np
.
maximum
(
det_s
[:,
2
]
-
det_s
[:,
0
]
+
1
,
det_s
[:,
3
]
-
det_s
[:,
1
]
+
1
)
>
30
)[
0
]
det_s
=
det_s
[
index
,
:]
# enlarge one times
bt
=
min
(
2
,
max_im_shrink
)
if
max_im_shrink
>
1
else
(
st
+
max_im_shrink
)
/
2
det_b
=
detect_face
(
image
,
image_shape
,
raw_image
,
bt
)
bt
=
min
(
2
,
max_shrink
)
if
max_shrink
>
1
else
(
st
+
max_shrink
)
/
2
det_b
=
detect_face
(
image
,
bt
)
# enlarge small i
am
ge x times for small face
if
max_
im_
shrink
>
2
:
# enlarge small i
ma
ge x times for small face
if
max_shrink
>
2
:
bt
*=
2
while
bt
<
max_im_shrink
:
det_b
=
np
.
row_stack
(
(
det_b
,
detect_face
(
image
,
image_shape
,
raw_image
,
bt
)))
while
bt
<
max_shrink
:
det_b
=
np
.
row_stack
((
det_b
,
detect_face
(
image
,
bt
)))
bt
*=
2
det_b
=
np
.
row_stack
(
(
det_b
,
detect_face
(
image
,
image_shape
,
raw_image
,
max_im_shrink
)))
det_b
=
np
.
row_stack
((
det_b
,
detect_face
(
image
,
max_shrink
)))
# enlarge only detect small face
if
bt
>
1
:
...
...
@@ -239,30 +228,28 @@ def multi_scale_test(image, image_shape, raw_image, max_im_shrink):
def
get_im_shrink
(
image_shape
):
max_
im_
shrink_v1
=
(
0x7fffffff
/
577.0
/
(
image_shape
[
1
]
*
image_shape
[
2
]))
**
0.5
max_
im_
shrink_v2
=
(
max_shrink_v1
=
(
0x7fffffff
/
577.0
/
(
image_shape
[
1
]
*
image_shape
[
2
]))
**
0.5
max_shrink_v2
=
(
(
678
*
1024
*
2.0
*
2.0
)
/
(
image_shape
[
1
]
*
image_shape
[
2
]))
**
0.5
max_im_shrink
=
get_round
(
min
(
max_im_shrink_v1
,
max_im_shrink_v2
),
2
)
-
0.3
if
max_im_shrink
>=
1.5
and
max_im_shrink
<
2
:
max_im_shrink
=
max_im_shrink
-
0.1
elif
max_im_shrink
>=
2
and
max_im_shrink
<
3
:
max_im_shrink
=
max_im_shrink
-
0.2
elif
max_im_shrink
>=
3
and
max_im_shrink
<
4
:
max_im_shrink
=
max_im_shrink
-
0.3
elif
max_im_shrink
>=
4
and
max_im_shrink
<
5
:
max_im_shrink
=
max_im_shrink
-
0.4
elif
max_im_shrink
>=
5
and
max_im_shrink
<
6
:
max_im_shrink
=
max_im_shrink
-
0.5
elif
max_im_shrink
>=
6
:
max_im_shrink
=
max_im_shrink
-
0.5
print
'max_im_shrink = '
,
max_im_shrink
shrink
=
max_im_shrink
if
max_im_shrink
<
1
else
1
max_shrink
=
get_round
(
min
(
max_shrink_v1
,
max_shrink_v2
),
2
)
-
0.3
if
max_shrink
>=
1.5
and
max_shrink
<
2
:
max_shrink
=
max_shrink
-
0.1
elif
max_shrink
>=
2
and
max_shrink
<
3
:
max_shrink
=
max_shrink
-
0.2
elif
max_shrink
>=
3
and
max_shrink
<
4
:
max_shrink
=
max_shrink
-
0.3
elif
max_shrink
>=
4
and
max_shrink
<
5
:
max_shrink
=
max_shrink
-
0.4
elif
max_shrink
>=
5
:
max_shrink
=
max_shrink
-
0.5
print
'max_shrink = '
,
max_shrink
shrink
=
max_shrink
if
max_shrink
<
1
else
1
print
"shrink = "
,
shrink
return
shrink
,
max_
im_
shrink
return
shrink
,
max_shrink
def
infer
(
args
,
batch_size
,
data_args
):
...
...
@@ -277,33 +264,25 @@ def infer(args, batch_size, data_args):
image
=
img
[
0
][
0
]
image_path
=
img
[
0
][
1
]
raw_image
=
Image
.
open
(
image_path
)
image_shape
=
[
3
,
image
.
size
[
1
],
image
.
size
[
0
]]
if
args
.
resize_h
!=
0
and
args
.
resize_w
!=
0
:
image_shape
=
[
3
,
args
.
resize_h
,
args
.
resize_w
]
else
:
image_shape
=
[
3
,
image
.
size
[
1
],
image
.
size
[
0
]]
shrink
,
max_im_shrink
=
get_im_shrink
(
image_shape
)
det0
=
detect_face
(
image
,
image_shape
,
raw_image
,
shrink
)
det1
=
flip_test
(
image
,
image_shape
,
raw_image
,
shrink
)
[
det2
,
det3
]
=
multi_scale_test
(
image
,
image_shape
,
raw_image
,
max_im_shrink
)
shrink
,
max_shrink
=
get_im_shrink
(
image_shape
)
det0
=
detect_face
(
image
,
shrink
)
det1
=
flip_test
(
image
,
shrink
)
[
det2
,
det3
]
=
multi_scale_test
(
image
,
max_shrink
)
det
=
np
.
row_stack
((
det0
,
det1
,
det2
,
det3
))
dets
=
bbox_vote
(
det
)
image_name
=
image_path
.
split
(
'/'
)[
-
1
]
image_class
=
image_path
.
split
(
'/'
)[
-
2
]
if
not
os
.
path
.
exists
(
'./infer_results/'
+
image_class
.
encode
(
'utf-8'
)):
os
.
makedirs
(
'./infer_results/'
+
image_class
.
encode
(
'utf-8'
))
f
=
open
(
'./infer_results/'
+
image_class
.
encode
(
'utf-8'
)
+
'/'
+
image_name
.
encode
(
'utf-8'
)[:
-
4
]
+
'.txt'
,
'w'
)
write_to_txt
(
image_path
,
f
,
dets
)
#draw_bounding_box_on_image(image_path, dets, args.confs_threshold)
#
write_to_txt(image_path, f, dets)
#
draw_bounding_box_on_image(image_path, dets, args.confs_threshold)
print
"Done"
...
...
@@ -316,8 +295,6 @@ if __name__ == '__main__':
data_args
=
reader
.
Settings
(
data_dir
=
data_dir
,
resize_h
=
args
.
resize_h
,
resize_w
=
args
.
resize_w
,
mean_value
=
[
104.
,
117.
,
123
],
apply_distort
=
False
,
apply_expand
=
False
,
...
...
fluid/face_detection/reader.py
浏览文件 @
e053c8c9
...
...
@@ -269,9 +269,6 @@ def pyramidbox(settings, file_list, mode, shuffle):
yield
im
,
boxes
,
expand_bboxes
(
boxes
),
lbls
,
difficults
if
mode
==
'test'
:
if
settings
.
resize_w
and
settings
.
resize_h
:
im
=
im
.
resize
((
settings
.
resize_w
,
settings
.
resize_h
),
Image
.
ANTIALIAS
)
yield
im
,
image_path
return
reader
...
...
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