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27号BigBang
Mask_RCNN
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01e69849
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Mask_RCNN
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前往新版Gitcode,体验更适合开发者的 AI 搜索 >>
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01e69849
编写于
1月 05, 2018
作者:
C
Cory Pruce
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1 changed file
with
12 addition
and
6 deletion
+12
-6
model.py
model.py
+12
-6
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model.py
浏览文件 @
01e69849
...
...
@@ -781,11 +781,11 @@ def refine_detections_graph(rois, probs, deltas, window, config):
# TODO: Filter out boxes with zero area
# Filter out background boxes
keep
=
tf
.
where
(
class_ids
>
0
)[
0
]
keep
=
tf
.
where
(
class_ids
>
0
)[
:,
0
]
# Filter out low confidence boxes
if
config
.
DETECTION_MIN_CONFIDENCE
:
keep
=
tf
.
sets
.
set_intersection
(
keep
,
tf
.
where
(
class_scores
>=
config
.
DETECTION_MIN_CONFIDENCE
)[
0
])
keep
,
tf
.
where
(
class_scores
>=
config
.
DETECTION_MIN_CONFIDENCE
)[
:,
0
])
# Apply per-class NMS
pre_nms_class_ids
=
tf
.
gather
(
class_ids
,
keep
)
#class_ids[keep]
...
...
@@ -799,7 +799,9 @@ def refine_detections_graph(rois, probs, deltas, window, config):
nms_keep
=
[]
def
nms_keep_map
(
class_id
):
ixs
=
tf
.
where
(
pre_nms_class_ids
==
class_id
)[
0
]
print
(
'pre_nms_class_ids.shape'
,
pre_nms_class_ids
.
shape
)
print
(
'class_id'
,
class_id
.
shape
)
ixs
=
tf
.
where
(
pre_nms_class_ids
==
tf
.
expand_dims
(
class_id
,
-
1
))[
0
]
# Apply NMS
class_keep
=
tf
.
image
.
non_max_suppression
(
...
...
@@ -810,15 +812,19 @@ def refine_detections_graph(rois, probs, deltas, window, config):
# Map indicies
return
tf
.
gather
(
keep
,
tf
.
gather
(
ixs
,
class_keep
))
print
(
'uniq_pre_nms_class_ids: {}'
.
format
(
uniq_pre_nms_class_ids
.
shape
))
nms_keep
=
tf
.
to_int64
(
tf
.
unique
(
tf
.
concat
(
tf
.
map_fn
(
nms_keep_map
,
uniq_pre_nms_class_ids
),
axis
=
0
))[
0
])
print
(
keep
.
shape
,
nms_keep
.
shape
)
print
(
keep
.
dtype
,
nms_keep
.
dtype
)
#keep = tf.sets.set_intersection(keep, nms_keep)
#tf.to_int32(
"""keep = tf.sets.set_intersection(
tf.expand_dims(keep, 0),
tf.expand_dims(tf.sparse_to_dense(nms_keep), 0))[1]
"""
#tf.to_int32(
#np.intersect1d(keep, nms_keep).astype(np.int32)
result_keep
=
tf
.
concat
([
keep
,
nms_keep
],
axis
=
0
)
print
(
'result_keep: {}'
.
format
(
result_keep
.
shape
))
output_keep
,
idx_keep
,
count_keep
=
tf
.
unique_with_counts
(
result_keep
)
...
...
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