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体验新版 GitCode,发现更多精彩内容 >>
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c47d9f9e
编写于
1月 09, 2019
作者:
P
panjiacheng
提交者:
HongyiSun
1月 09, 2019
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差异文件
Prediction: refactored DataForLearning proto.
上级
f2e7ce85
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
4 addition
and
41 deletion
+4
-41
modules/prediction/common/feature_output.cc
modules/prediction/common/feature_output.cc
+0
-15
modules/prediction/proto/offline_features.proto
modules/prediction/proto/offline_features.proto
+4
-26
未找到文件。
modules/prediction/common/feature_output.cc
浏览文件 @
c47d9f9e
...
...
@@ -52,21 +52,6 @@ void FeatureOutput::Insert(const Feature& feature) {
void
FeatureOutput
::
InsertIntoLearningData
(
const
Feature
&
feature
)
{
data_for_learning_
.
set_id
(
feature
.
id
());
data_for_learning_
.
set_timestamp
(
feature
.
timestamp
());
for
(
int
i
=
0
;
i
<
feature
.
lane
().
lane_graph
().
lane_sequence_size
();
i
++
)
{
DataForLearning
::
LaneSequenceData
lane_sequence_data
;
auto
curr_lane_sequence
=
feature
.
lane
().
lane_graph
().
lane_sequence
(
i
);
lane_sequence_data
.
set_lane_sequence_id
(
curr_lane_sequence
.
lane_sequence_id
());
for
(
int
j
=
0
;
j
<
curr_lane_sequence
.
features
().
mlp_features_size
();
j
++
)
{
lane_sequence_data
.
add_features_lane_learning
(
curr_lane_sequence
.
features
().
mlp_features
(
j
));
}
data_for_learning_
.
add_lane_sequence_data
()
->
CopyFrom
(
lane_sequence_data
);
}
}
void
FeatureOutput
::
Write
()
{
...
...
modules/prediction/proto/offline_features.proto
浏览文件 @
c47d9f9e
...
...
@@ -17,36 +17,14 @@ message CNNFeatures {
optional
int32
label
=
5
;
}
// next id = 6;
message
DataForLearning
{
// The info. needed for identifying a unique data point:
optional
int32
id
=
1
;
optional
double
timestamp
=
2
;
// The
actual input
features for learning algorithms:
repeated
double
features_learning
=
3
;
// The features for learning algorithms:
repeated
double
features_
for_
learning
=
3
;
// The labels for each data point:
message
TrajectoryPoint
{
optional
double
x
=
1
;
optional
double
y
=
2
;
optional
double
velocity_heading
=
3
;
}
repeated
TrajectoryPoint
trajectory
=
4
;
// In case if the learning algorithm processes single lane.
message
LaneSequenceData
{
// The info. needed for identifying a unique data point:
optional
int32
lane_sequence_id
=
1
;
// The actual input features for learning algorithms:
repeated
double
features_lane_learning
=
2
;
// The labels for each data point:
optional
int32
label
=
3
;
optional
double
time_to_lane_center
=
4
;
optional
double
time_to_lane_edge
=
5
;
}
repeated
LaneSequenceData
lane_sequence_data
=
5
;
// The ground-truth labels:
repeated
double
labels
=
4
;
}
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