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P
PaddleDetection
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9229209b
编写于
11月 25, 2019
作者:
W
wangguanzhong
提交者:
GitHub
11月 25, 2019
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电子邮件补丁
差异文件
fix config for fluid.data (#37)
上级
3af2e211
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
15 addition
and
15 deletion
+15
-15
ppdet/data/data_feed.py
ppdet/data/data_feed.py
+12
-12
ppdet/modeling/model_input.py
ppdet/modeling/model_input.py
+3
-3
未找到文件。
ppdet/data/data_feed.py
浏览文件 @
9229209b
...
...
@@ -453,7 +453,7 @@ class FasterRCNNTrainFeed(DataFeed):
'image'
,
'im_info'
,
'im_id'
,
'gt_box'
,
'gt_label'
,
'is_crowd'
],
image_shape
=
[
None
,
3
,
None
,
None
],
image_shape
=
[
3
,
None
,
None
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
RandomFlipImage
(
prob
=
0.5
),
...
...
@@ -505,7 +505,7 @@ class FasterRCNNEvalFeed(DataFeed):
COCO_VAL_IMAGE_DIR
).
__dict__
,
fields
=
[
'image'
,
'im_info'
,
'im_id'
,
'im_shape'
,
'gt_box'
,
'gt_label'
,
'is_difficult'
],
image_shape
=
[
None
,
3
,
None
,
None
],
image_shape
=
[
3
,
None
,
None
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
NormalizeImage
(
mean
=
[
0.485
,
0.456
,
0.406
],
...
...
@@ -552,7 +552,7 @@ class FasterRCNNTestFeed(DataFeed):
dataset
=
SimpleDataSet
(
COCO_VAL_ANNOTATION
,
COCO_VAL_IMAGE_DIR
).
__dict__
,
fields
=
[
'image'
,
'im_info'
,
'im_id'
,
'im_shape'
],
image_shape
=
[
None
,
3
,
None
,
None
],
image_shape
=
[
3
,
None
,
None
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
NormalizeImage
(
mean
=
[
0.485
,
0.456
,
0.406
],
...
...
@@ -600,7 +600,7 @@ class MaskRCNNTrainFeed(DataFeed):
'image'
,
'im_info'
,
'im_id'
,
'gt_box'
,
'gt_label'
,
'is_crowd'
,
'gt_mask'
],
image_shape
=
[
None
,
3
,
None
,
None
],
image_shape
=
[
3
,
None
,
None
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
RandomFlipImage
(
prob
=
0.5
,
is_mask_flip
=
True
),
...
...
@@ -646,7 +646,7 @@ class MaskRCNNEvalFeed(DataFeed):
dataset
=
CocoDataSet
(
COCO_VAL_ANNOTATION
,
COCO_VAL_IMAGE_DIR
).
__dict__
,
fields
=
[
'image'
,
'im_info'
,
'im_id'
,
'im_shape'
],
image_shape
=
[
None
,
3
,
None
,
None
],
image_shape
=
[
3
,
None
,
None
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
NormalizeImage
(
mean
=
[
0.485
,
0.456
,
0.406
],
...
...
@@ -698,7 +698,7 @@ class MaskRCNNTestFeed(DataFeed):
dataset
=
SimpleDataSet
(
COCO_VAL_ANNOTATION
,
COCO_VAL_IMAGE_DIR
).
__dict__
,
fields
=
[
'image'
,
'im_info'
,
'im_id'
,
'im_shape'
],
image_shape
=
[
None
,
3
,
None
,
None
],
image_shape
=
[
3
,
None
,
None
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
NormalizeImage
(
...
...
@@ -743,7 +743,7 @@ class SSDTrainFeed(DataFeed):
def
__init__
(
self
,
dataset
=
VocDataSet
().
__dict__
,
fields
=
[
'image'
,
'gt_box'
,
'gt_label'
],
image_shape
=
[
None
,
3
,
300
,
300
],
image_shape
=
[
3
,
300
,
300
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
,
with_mixup
=
False
),
NormalizeBox
(),
...
...
@@ -802,7 +802,7 @@ class SSDEvalFeed(DataFeed):
dataset
=
VocDataSet
(
VOC_VAL_ANNOTATION
).
__dict__
,
fields
=
[
'image'
,
'im_shape'
,
'im_id'
,
'gt_box'
,
'gt_label'
,
'is_difficult'
],
image_shape
=
[
None
,
3
,
300
,
300
],
image_shape
=
[
3
,
300
,
300
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
,
with_mixup
=
False
),
NormalizeBox
(),
...
...
@@ -847,7 +847,7 @@ class SSDTestFeed(DataFeed):
def
__init__
(
self
,
dataset
=
SimpleDataSet
(
VOC_VAL_ANNOTATION
).
__dict__
,
fields
=
[
'image'
,
'im_id'
,
'im_shape'
],
image_shape
=
[
None
,
3
,
300
,
300
],
image_shape
=
[
3
,
300
,
300
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
ResizeImage
(
target_size
=
300
,
use_cv2
=
False
,
interp
=
1
),
...
...
@@ -893,7 +893,7 @@ class YoloTrainFeed(DataFeed):
def
__init__
(
self
,
dataset
=
CocoDataSet
().
__dict__
,
fields
=
[
'image'
,
'gt_box'
,
'gt_label'
,
'gt_score'
],
image_shape
=
[
None
,
3
,
608
,
608
],
image_shape
=
[
3
,
608
,
608
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
,
with_mixup
=
True
),
MixupImage
(
alpha
=
1.5
,
beta
=
1.5
),
...
...
@@ -955,7 +955,7 @@ class YoloEvalFeed(DataFeed):
COCO_VAL_IMAGE_DIR
).
__dict__
,
fields
=
[
'image'
,
'im_size'
,
'im_id'
,
'gt_box'
,
'gt_label'
,
'is_difficult'
],
image_shape
=
[
None
,
3
,
608
,
608
],
image_shape
=
[
3
,
608
,
608
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
ResizeImage
(
target_size
=
608
,
interp
=
2
),
...
...
@@ -1013,7 +1013,7 @@ class YoloTestFeed(DataFeed):
dataset
=
SimpleDataSet
(
COCO_VAL_ANNOTATION
,
COCO_VAL_IMAGE_DIR
).
__dict__
,
fields
=
[
'image'
,
'im_size'
,
'im_id'
],
image_shape
=
[
None
,
3
,
608
,
608
],
image_shape
=
[
3
,
608
,
608
],
sample_transforms
=
[
DecodeImage
(
to_rgb
=
True
),
ResizeImage
(
target_size
=
608
,
interp
=
2
),
...
...
ppdet/modeling/model_input.py
浏览文件 @
9229209b
...
...
@@ -40,7 +40,7 @@ feed_var_def = [
def
create_feed
(
feed
,
iterable
=
False
,
sub_prog_feed
=
False
):
image_shape
=
feed
.
image_shape
image_shape
=
[
None
]
+
feed
.
image_shape
feed_var_map
=
{
var
[
'name'
]:
var
for
var
in
feed_var_def
}
feed_var_map
[
'image'
]
=
{
'name'
:
'image'
,
...
...
@@ -98,14 +98,14 @@ def create_feed(feed, iterable=False, sub_prog_feed=False):
'lod_level'
:
0
}
image_name_list
.
append
(
name
)
feed_var_map
[
'im_info'
][
'shape'
]
=
[
feed
.
num_scale
*
3
]
feed_var_map
[
'im_info'
][
'shape'
]
=
[
None
,
feed
.
num_scale
*
3
]
feed
.
fields
=
image_name_list
+
feed
.
fields
[
1
:]
if
sub_prog_feed
:
box_names
=
[
'bbox'
,
'bbox_flip'
]
for
box_name
in
box_names
:
sub_prog_feed
=
{
'name'
:
box_name
,
'shape'
:
[
6
],
'shape'
:
[
None
,
6
],
'dtype'
:
'float32'
,
'lod_level'
:
1
}
...
...
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