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484fcbbe
编写于
8月 08, 2019
作者:
K
Kaipeng Deng
提交者:
GitHub
8月 08, 2019
浏览文件
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差异文件
fix yolov3 voc eval in train (#3053)
* fix yolov3 voc eval in train * fix comment
上级
f8b2d8a4
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
61 addition
and
27 deletion
+61
-27
PaddleCV/PaddleDetection/ppdet/data/data_feed.py
PaddleCV/PaddleDetection/ppdet/data/data_feed.py
+1
-0
PaddleCV/PaddleDetection/ppdet/data/transform/arrange_sample.py
...CV/PaddleDetection/ppdet/data/transform/arrange_sample.py
+10
-5
PaddleCV/PaddleDetection/ppdet/modeling/model_input.py
PaddleCV/PaddleDetection/ppdet/modeling/model_input.py
+2
-0
PaddleCV/PaddleDetection/ppdet/utils/map_utils.py
PaddleCV/PaddleDetection/ppdet/utils/map_utils.py
+2
-2
PaddleCV/PaddleDetection/ppdet/utils/voc_eval.py
PaddleCV/PaddleDetection/ppdet/utils/voc_eval.py
+41
-18
PaddleCV/PaddleDetection/tools/train.py
PaddleCV/PaddleDetection/tools/train.py
+5
-2
未找到文件。
PaddleCV/PaddleDetection/ppdet/data/data_feed.py
浏览文件 @
484fcbbe
...
...
@@ -936,6 +936,7 @@ class YoloEvalFeed(DataFeed):
with_background
=
with_background
,
num_workers
=
num_workers
,
use_process
=
use_process
)
self
.
num_max_boxes
=
num_max_boxes
self
.
mode
=
'VAL'
self
.
bufsize
=
128
...
...
PaddleCV/PaddleDetection/ppdet/data/transform/arrange_sample.py
浏览文件 @
484fcbbe
...
...
@@ -245,8 +245,8 @@ class ArrangeEvalYOLO(BaseOperator):
context: a dict which contains additional info.
Returns:
sample: a tuple containing the following items:
(image,
gt_bbox, gt_class, gt_score
,
is_crowd, im_info, gt_masks
)
(image,
im_shape, im_id, gt_bbox, gt_class
,
difficult
)
"""
im
=
sample
[
'image'
]
if
len
(
sample
[
'gt_bbox'
])
!=
len
(
sample
[
'gt_class'
]):
...
...
@@ -255,9 +255,14 @@ class ArrangeEvalYOLO(BaseOperator):
h
=
sample
[
'h'
]
w
=
sample
[
'w'
]
im_shape
=
np
.
array
((
h
,
w
))
gt_bbox
=
sample
[
'gt_bbox'
]
gt_class
=
sample
[
'gt_class'
]
difficult
=
sample
[
'difficult'
]
gt_bbox
=
np
.
zeros
((
50
,
4
),
dtype
=
im
.
dtype
)
gt_class
=
np
.
zeros
((
50
,
),
dtype
=
np
.
int32
)
difficult
=
np
.
zeros
((
50
,
),
dtype
=
np
.
int32
)
gt_num
=
min
(
50
,
len
(
sample
[
'gt_bbox'
]))
if
gt_num
>
0
:
gt_bbox
[:
gt_num
,
:]
=
sample
[
'gt_bbox'
][:
gt_num
,
:]
gt_class
[:
gt_num
]
=
sample
[
'gt_class'
][:
gt_num
,
0
]
difficult
[:
gt_num
]
=
sample
[
'difficult'
][:
gt_num
,
0
]
outs
=
(
im
,
im_shape
,
im_id
,
gt_bbox
,
gt_class
,
difficult
)
return
outs
...
...
PaddleCV/PaddleDetection/ppdet/modeling/model_input.py
浏览文件 @
484fcbbe
...
...
@@ -54,9 +54,11 @@ def create_feed(feed, use_pyreader=True):
feed_var_map
[
'gt_label'
][
'shape'
]
=
[
feed
.
num_max_boxes
]
feed_var_map
[
'gt_score'
][
'shape'
]
=
[
feed
.
num_max_boxes
]
feed_var_map
[
'gt_box'
][
'shape'
]
=
[
feed
.
num_max_boxes
,
4
]
feed_var_map
[
'is_difficult'
][
'shape'
]
=
[
feed
.
num_max_boxes
]
feed_var_map
[
'gt_label'
][
'lod_level'
]
=
0
feed_var_map
[
'gt_score'
][
'lod_level'
]
=
0
feed_var_map
[
'gt_box'
][
'lod_level'
]
=
0
feed_var_map
[
'is_difficult'
][
'lod_level'
]
=
0
feed_vars
=
OrderedDict
([(
key
,
fluid
.
layers
.
data
(
name
=
feed_var_map
[
key
][
'name'
],
...
...
PaddleCV/PaddleDetection/ppdet/utils/map_utils.py
浏览文件 @
484fcbbe
...
...
@@ -105,7 +105,7 @@ class DetectionMAP(object):
# record class gt count
for
gtl
,
diff
in
zip
(
gt_label
,
difficult
):
if
self
.
evaluate_difficult
or
int
(
diff
)
==
0
:
self
.
class_gt_counts
[
int
(
gtl
[
0
]
)]
+=
1
self
.
class_gt_counts
[
int
(
np
.
array
(
gtl
)
)]
+=
1
# record class score positive
visited
=
[
False
]
*
len
(
gt_label
)
...
...
@@ -124,7 +124,7 @@ class DetectionMAP(object):
if
max_overlap
>
self
.
overlap_thresh
:
if
self
.
evaluate_difficult
or
\
int
(
difficult
[
max_idx
]
)
==
0
:
int
(
np
.
array
(
difficult
[
max_idx
])
)
==
0
:
if
not
visited
[
max_idx
]:
self
.
class_score_poss
[
int
(
label
)].
append
([
score
,
1.0
])
...
...
PaddleCV/PaddleDetection/ppdet/utils/voc_eval.py
浏览文件 @
484fcbbe
...
...
@@ -71,27 +71,39 @@ def bbox_eval(results,
continue
gt_boxes
=
t
[
'gt_box'
][
0
]
gt_box_lengths
=
t
[
'gt_box'
][
1
][
0
]
gt_labels
=
t
[
'gt_label'
][
0
]
assert
len
(
gt_boxes
)
==
len
(
gt_labels
)
difficults
=
t
[
'is_difficult'
][
0
]
if
not
evaluate_difficult
\
else
None
if
not
evaluate_difficult
:
assert
len
(
gt_labels
)
==
len
(
difficults
)
bbox_idx
=
0
gt_box_idx
=
0
for
i
in
range
(
len
(
bbox_lengths
)):
bbox_num
=
bbox_lengths
[
i
]
gt_box_num
=
gt_box_lengths
[
i
]
bbox
=
bboxes
[
bbox_idx
:
bbox_idx
+
bbox_num
]
gt_box
=
gt_boxes
[
gt_box_idx
:
gt_box_idx
+
gt_box_num
]
gt_label
=
gt_labels
[
gt_box_idx
:
gt_box_idx
+
gt_box_num
]
difficult
=
None
if
difficults
is
None
else
\
difficults
[
gt_box_idx
:
gt_box_idx
+
gt_box_num
]
detection_map
.
update
(
bbox
,
gt_box
,
gt_label
,
difficult
)
bbox_idx
+=
bbox_num
gt_box_idx
+=
gt_box_num
if
len
(
t
[
'gt_box'
][
1
])
==
0
:
# gt_box, gt_label, difficult read as zero padded Tensor
bbox_idx
=
0
for
i
in
range
(
len
(
gt_boxes
)):
gt_box
=
gt_boxes
[
i
]
gt_label
=
gt_labels
[
i
]
difficult
=
difficults
[
i
]
bbox_num
=
bbox_lengths
[
i
]
bbox
=
bboxes
[
bbox_idx
:
bbox_idx
+
bbox_num
]
gt_box
,
gt_label
,
difficult
=
prune_zero_padding
(
gt_box
,
gt_label
,
difficult
)
detection_map
.
update
(
bbox
,
gt_box
,
gt_label
,
difficult
)
bbox_idx
+=
bbox_num
else
:
# gt_box, gt_label, difficult read as LoDTensor
gt_box_lengths
=
t
[
'gt_box'
][
1
][
0
]
bbox_idx
=
0
gt_box_idx
=
0
for
i
in
range
(
len
(
bbox_lengths
)):
bbox_num
=
bbox_lengths
[
i
]
gt_box_num
=
gt_box_lengths
[
i
]
bbox
=
bboxes
[
bbox_idx
:
bbox_idx
+
bbox_num
]
gt_box
=
gt_boxes
[
gt_box_idx
:
gt_box_idx
+
gt_box_num
]
gt_label
=
gt_labels
[
gt_box_idx
:
gt_box_idx
+
gt_box_num
]
difficult
=
None
if
difficults
is
None
else
\
difficults
[
gt_box_idx
:
gt_box_idx
+
gt_box_num
]
detection_map
.
update
(
bbox
,
gt_box
,
gt_label
,
difficult
)
bbox_idx
+=
bbox_num
gt_box_idx
+=
gt_box_num
logger
.
info
(
"Accumulating evaluatation results..."
)
detection_map
.
accumulate
()
...
...
@@ -99,6 +111,17 @@ def bbox_eval(results,
map_type
,
100.
*
detection_map
.
get_map
()))
def
prune_zero_padding
(
gt_box
,
gt_label
,
difficult
=
None
):
valid_cnt
=
0
for
i
in
range
(
len
(
gt_box
)):
if
gt_box
[
i
,
0
]
==
0
and
gt_box
[
i
,
1
]
==
0
and
\
gt_box
[
i
,
2
]
==
0
and
gt_box
[
i
,
3
]
==
0
:
break
valid_cnt
+=
1
return
(
gt_box
[:
valid_cnt
],
gt_label
[:
valid_cnt
],
difficult
[:
valid_cnt
]
if
difficult
is
not
None
else
None
)
def
get_category_info
(
anno_file
=
None
,
with_background
=
True
,
use_default_label
=
False
):
...
...
PaddleCV/PaddleDetection/tools/train.py
浏览文件 @
484fcbbe
...
...
@@ -123,8 +123,11 @@ def main():
eval_pyreader
.
decorate_sample_list_generator
(
eval_reader
,
place
)
# parse eval fetches
extra_keys
=
[
'im_info'
,
'im_id'
,
'im_shape'
]
if
cfg
.
metric
==
'COCO'
else
[]
extra_keys
=
[]
if
cfg
.
metric
==
'COCO'
:
extra_keys
=
[
'im_info'
,
'im_id'
,
'im_shape'
]
if
cfg
.
metric
==
'VOC'
:
extra_keys
=
[
'gt_box'
,
'gt_label'
,
'is_difficult'
]
eval_keys
,
eval_values
,
eval_cls
=
parse_fetches
(
fetches
,
eval_prog
,
extra_keys
)
...
...
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