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apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
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apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/common/online_to_offline.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import abc
import logging
import math
from google.protobuf.internal import decoder
from google.protobuf.internal import encoder
import numpy as np
from modules.prediction.proto import offline_features_pb2
from modules.tools.prediction.data_pipelines.common.bounding_rectangle import BoundingRectangle
from modules.tools.prediction.data_pipelines.common.configure import parameters
param_fea = parameters['feature']
class LabelGenerator(object):
def __init__(self):
self.filepath = None
'''
feature_dict contains the organized Feature in the following way:
obstacle_ID --> [Feature1, Feature2, Feature3, ...] (sequentially sorted)
'''
self.feature_dict = dict()
'''
observation_dict contains the important observations of the subsequent
Features for each obstacle at every timestamp:
obstacle_ID@timestamp --> dictionary of observations
where dictionary of observations contains:
'obs_traj': the trajectory points (x, y, vel_heading) up to
max_observation_time this trajectory poitns must
be consecutive (0.1sec sampling period)
'obs_traj_len': length of trajectory points
'obs_actual_lane_ids': the actual sequence of lane_segment ids
the obstacle steps on
'has_started_lane_change': whether the obstacle has started lane
changing within max_observation_time
'has_finished_lane_change': whether it has finished lane changing
'lane_change_start_time':
'lane_change_finish_time':
'is_jittering':
'new_lane_id':
'total_observed_time_span':
This observation_dict, once constructed, can be reused by various labeling
functions.
'''
self.observation_dict = dict()
self.future_status_dict = dict()
self.cruise_label_dict = dict()
self.junction_label_dict = dict()
def LoadFeaturePBAndSaveLabelFiles(self, input_filepath):
'''
This function will be used to replace all the functionalities in
generate_cruise_label.py
'''
self.filepath = input_filepath
feature_sequences = self.LoadPBFeatures(input_filepath)
self.OrganizeFeatures(feature_sequences)
del feature_sequences # Try to free up some memory
self.ObserveAllFeatureSequences()
'''
@brief: parse the pb file of Feature of all obstacles at all times.
@input filepath: the path of the pb file that contains all the features of
every obstacle at every timestamp.
@output: python readable format of the same content.
'''
def LoadPBFeatures(self, filepath):
self.filepath = filepath
offline_features = offline_features_pb2.Features()
with open(filepath, 'rb') as file_in:
offline_features.ParseFromString(file_in.read())
return offline_features.feature
'''
@brief: save the feature_sequences to an output protobuf file.
@input filepath: the path of the output pb file.
@input feature_sequences: the content to be saved.
'''
@staticmethod
def SaveOutputPB(filepath, pb_message):
with open(filepath, 'wb') as file:
serializedMessage = pb_message.SerializeToString()
file.write(serializedMessage)
'''
@brief: organize the features by obstacle IDs first, then sort each
obstacle's feature according to time sequence.
@input features: the unorganized features
@output: organized (meaning: grouped by obstacle ID and sorted by time)
features.
'''
def OrganizeFeatures(self, features):
# Organize Feature by obstacle_ID (put those belonging to the same obstacle together)
for feature in features:
if feature.id in self.feature_dict.keys():
self.feature_dict[feature.id].append(feature)
else:
self.feature_dict[feature.id] = [feature]
# For the same obstacle, sort the Feature sequentially.
for obs_id in self.feature_dict.keys():
if len(self.feature_dict[obs_id]) < 2:
del self.feature_dict[obs_id]
continue
self.feature_dict[obs_id].sort(key=lambda x: x.timestamp)
'''
@brief: observe all feature sequences and build observation_dict.
@output: the complete observation_dict.
'''
def ObserveAllFeatureSequences(self):
for obs_id, feature_sequence in self.feature_dict.items():
for idx, feature in enumerate(feature_sequence):
if not feature.HasField('lane') or \
not feature.lane.HasField('lane_feature'):
# print('No lane feature, cancel labeling')
continue
self.ObserveFeatureSequence(feature_sequence, idx)
np.save(self.filepath + '.npy', self.observation_dict)
'''
@brief: Observe the sequence of Features following the Feature at
idx_curr and save some important observations in the class
so that it can be used by various label functions.
@input feature_sequence: A sorted sequence of Feature corresponding to
one obstacle.
@input idx_curr: The index of the current Feature to be labelled.
We will look at the subsequent Features following this
one to complete labeling.
@output: All saved as class variables in observation_dict,
including: its trajectory info and its lane changing info.
'''
def ObserveFeatureSequence(self, feature_sequence, idx_curr):
# Initialization.
feature_curr = feature_sequence[idx_curr]
dict_key = "{}@{:.3f}".format(feature_curr.id, feature_curr.timestamp)
if dict_key in self.observation_dict.keys():
return
# Record all the lane segments belonging to the lane sequence that the
# obstacle is currently on.
curr_lane_segments = set()
for lane_sequence in feature_curr.lane.lane_graph.lane_sequence:
if lane_sequence.vehicle_on_lane:
for lane_segment in lane_sequence.lane_segment:
curr_lane_segments.add(lane_segment.lane_id)
if len(curr_lane_segments) == 0:
# print("Obstacle is not on any lane.")
return
# Declare needed varables.
new_lane_id = None
has_started_lane_change = False
has_finished_lane_change = False
lane_change_start_time = None
lane_change_finish_time = None
is_jittering = False
feature_seq_len = len(feature_sequence)
prev_timestamp = -1.0
obs_actual_lane_ids = []
obs_traj = []
total_observed_time_span = 0.0
# This goes through all the subsequent features in this sequence
# of features up to the maximum_observation_time.
for j in range(idx_curr, feature_seq_len):
# If timespan exceeds max. observation time, then end observing.
time_span = feature_sequence[j].timestamp - feature_curr.timestamp
if time_span > param_fea['maximum_observation_time']:
break
total_observed_time_span = time_span
#####################################################################
# Update the obstacle trajectory:
# Only update for consecutive (sampling rate = 0.1sec) points.
obs_traj.append((feature_sequence[j].position.x,
feature_sequence[j].position.y,
feature_sequence[j].velocity_heading,
feature_sequence[j].speed,
feature_sequence[j].length,
feature_sequence[j].width,
feature_sequence[j].timestamp))
#####################################################################
# Update the lane-change info (mainly for cruise scenario):
if feature_sequence[j].HasField('lane') and \
feature_sequence[j].lane.HasField('lane_feature'):
# If jittering or done, then jump over this part.
if (is_jittering or has_finished_lane_change):
continue
# Record the sequence of lane_segments the obstacle stepped on.
lane_id_j = feature_sequence[j].lane.lane_feature.lane_id
if lane_id_j not in obs_actual_lane_ids:
obs_actual_lane_ids.append(lane_id_j)
# If step into another lane, label lane change to be started.
if lane_id_j not in curr_lane_segments:
# If it's the first time, log new_lane_id
if not has_started_lane_change:
has_started_lane_change = True
lane_change_start_time = time_span
new_lane_id = lane_id_j
else:
# If it stepped into other lanes and now comes back, it's jittering!
if has_started_lane_change:
is_jittering = True
continue
# If roughly get to the center of another lane, label lane change to be finished.
left_bound = feature_sequence[j].lane.lane_feature.dist_to_left_boundary
right_bound = feature_sequence[j].lane.lane_feature.dist_to_right_boundary
if left_bound / (left_bound + right_bound) > (0.5 - param_fea['lane_change_finish_condition']) and \
left_bound / (left_bound + right_bound) < (0.5 + param_fea['lane_change_finish_condition']):
if has_started_lane_change:
# This means that the obstacle has finished lane change.
has_finished_lane_change = True
lane_change_finish_time = time_span
else:
# This means that the obstacle moves back to the center
# of the original lane for the first time.
if lane_change_finish_time is None:
lane_change_finish_time = time_span
if len(obs_actual_lane_ids) == 0:
# print("No lane id")
return
# Update the observation_dict:
dict_val = dict()
dict_val['obs_traj'] = obs_traj
dict_val['obs_traj_len'] = len(obs_traj)
dict_val['obs_actual_lane_ids'] = obs_actual_lane_ids
dict_val['has_started_lane_change'] = has_started_lane_change
dict_val['has_finished_lane_change'] = has_finished_lane_change
dict_val['lane_change_start_time'] = lane_change_start_time
dict_val['lane_change_finish_time'] = lane_change_finish_time
dict_val['is_jittering'] = is_jittering
dict_val['new_lane_id'] = new_lane_id
dict_val['total_observed_time_span'] = total_observed_time_span
self.observation_dict["{}@{:.3f}".format(
feature_curr.id, feature_curr.timestamp)] = dict_val
return
'''
@brief Based on the observation, label each lane sequence accordingly:
- label whether the obstacle is on the lane_sequence
within a certain amount of time.
- if there is lane chage, label the time it takes to get to that lane.
'''
def LabelSingleLane(self, period_of_interest=3.0):
output_features = offline_features_pb2.Features()
for obs_id, feature_sequence in self.feature_dict.items():
feature_seq_len = len(feature_sequence)
for idx, feature in enumerate(feature_sequence):
if not feature.HasField('lane') or \
not feature.lane.HasField('lane_feature'):
# print "No lane feature, cancel labeling"
continue
# Observe the subsequent Features
if "{}@{:.3f}".format(feature.id, feature.timestamp) not in self.observation_dict:
continue
observed_val = self.observation_dict["{}@{:.3f}".format(
feature.id, feature.timestamp)]
lane_sequence_dict = dict()
# Based on the observation, label data.
for lane_sequence in feature.lane.lane_graph.lane_sequence:
# Sanity check.
if len(lane_sequence.lane_segment) == 0:
print('There is no lane segment in this sequence.')
continue
# Handle jittering data
if observed_val['is_jittering']:
lane_sequence.label = -10
lane_sequence.time_to_lane_center = -1.0
lane_sequence.time_to_lane_edge = -1.0
continue
# Handle the case that we didn't obesrve enough Features to label
if observed_val['total_observed_time_span'] < period_of_interest and \
not observed_val['has_started_lane_change']:
lane_sequence.label = -20
lane_sequence.time_to_lane_center = -1.0
lane_sequence.time_to_lane_edge = -1.0
# The current lane is obstacle's original lane. (labels: 0,2,4)
if lane_sequence.vehicle_on_lane:
# Obs is following ONE OF its original lanes:
if not observed_val['has_started_lane_change'] or \
observed_val['lane_change_start_time'] > period_of_interest:
# Record this lane_sequence's lane_ids
current_lane_ids = []
for k in range(len(lane_sequence.lane_segment)):
if lane_sequence.lane_segment[k].HasField('lane_id'):
current_lane_ids.append(lane_sequence.lane_segment[k].lane_id)
is_following_this_lane = True
for l_id in range(1, min(len(current_lane_ids),
len(observed_val['obs_actual_lane_ids']))):
if current_lane_ids[l_id] != observed_val['obs_actual_lane_ids'][l_id]:
is_following_this_lane = False
break
# Obs is following this original lane:
if is_following_this_lane:
# Obstacle is following this original lane and moved to lane-center
if observed_val['lane_change_finish_time'] is not None:
lane_sequence.label = 4
lane_sequence.time_to_lane_edge = -1.0
lane_sequence.time_to_lane_center = -1.0
# Obstacle is following this original lane but is never at lane-center:
else:
lane_sequence.label = 2
lane_sequence.time_to_lane_edge = -1.0
lane_sequence.time_to_lane_center = -1.0
# Obs is following another original lane:
else:
lane_sequence.label = 0
lane_sequence.time_to_lane_edge = -1.0
lane_sequence.time_to_lane_center = -1.0
# Obs has stepped out of this lane within period_of_interest.
else:
lane_sequence.label = 0
lane_sequence.time_to_lane_edge = -1.0
lane_sequence.time_to_lane_center = -1.0
# The current lane is NOT obstacle's original lane. (labels: -1,1,3)
else:
# Obstacle is following the original lane.
if not observed_val['has_started_lane_change'] or \
observed_val['lane_change_start_time'] > period_of_interest:
lane_sequence.label = -1
lane_sequence.time_to_lane_edge = -1.0
lane_sequence.time_to_lane_center = -1.0
else:
new_lane_id_is_in_this_lane_seq = False
for lane_segment in lane_sequence.lane_segment:
if lane_segment.lane_id == observed_val['new_lane_id']:
new_lane_id_is_in_this_lane_seq = True
break
# Obstacle has changed to this lane.
if new_lane_id_is_in_this_lane_seq:
# Obstacle has finished lane changing within time_of_interest.
if observed_val['has_finished_lane_change'] and \
observed_val['lane_change_finish_time'] < period_of_interest:
lane_sequence.label = 3
lane_sequence.time_to_lane_edge = observed_val['lane_change_start_time']
lane_sequence.time_to_lane_center = observed_val['lane_change_finish_time']
# Obstacle started lane changing but haven't finished yet.
else:
lane_sequence.label = 1
lane_sequence.time_to_lane_edge = observed_val['lane_change_start_time']
lane_sequence.time_to_lane_center = -1.0
# Obstacle has changed to some other lane.
else:
lane_sequence.label = -1
lane_sequence.time_to_lane_edge = -1.0
lane_sequence.time_to_lane_center = -1.0
for lane_sequence in feature.lane.lane_graph.lane_sequence:
lane_sequence_dict[lane_sequence.lane_sequence_id] = [lane_sequence.label,
lane_sequence.time_to_lane_center, lane_sequence.time_to_lane_edge]
self.cruise_label_dict["{}@{:.3f}".format(
feature.id, feature.timestamp)] = lane_sequence_dict
np.save(self.filepath + '.cruise_label.npy', self.cruise_label_dict)
def LabelTrajectory(self, period_of_interest=3.0):
output_features = offline_features_pb2.Features()
for obs_id, feature_sequence in self.feature_dict.items():
for idx, feature in enumerate(feature_sequence):
# Observe the subsequent Features
if "{}@{:.3f}".format(feature.id, feature.timestamp) not in self.observation_dict:
continue
observed_val = self.observation_dict["{}@{:.3f}".format(
feature.id, feature.timestamp)]
self.future_status_dict["{}@{:.3f}".format(
feature.id, feature.timestamp)] = observed_val['obs_traj']
np.save(self.filepath + '.future_status.npy', self.future_status_dict)
# for point in observed_val['obs_traj']:
# traj_point = feature.future_trajectory_points.add()
# traj_point.path_point.x = point[0]
# traj_point.path_point.y = point[1]
# traj_point.path_point.velocity_heading = point[2]
# traj_point.timestamp = point[3]
# output_features.feature.add().CopyFrom(feature)
# self.SaveOutputPB(self.filepath + '.future_status.label', output_features)
def LabelJunctionExit(self):
'''
label feature trajectory according to real future lane sequence in 7s
'''
output_features = offline_features_pb2.Features()
for obs_id, feature_sequence in self.feature_dict.items():
feature_seq_len = len(feature_sequence)
for i, fea in enumerate(feature_sequence):
# Sanity check.
if not fea.HasField('junction_feature') or \
not len(fea.junction_feature.junction_exit):
# print("No junction_feature, junction_exit, or junction_mlp_feature, not labeling this frame.")
continue
curr_pos = np.array([fea.position.x, fea.position.y])
# Only keep speed > 1
# TODO(all) consider recovery
# if fea.speed <= 1:
# continue
heading = math.atan2(fea.raw_velocity.y, fea.raw_velocity.x)
# Construct dictionary of all exit with dict[exit_lane_id] = np.array(exit_position)
exit_dict = dict()
exit_pos_dict = dict()
mask = [0] * 12
for junction_exit in fea.junction_feature.junction_exit:
if junction_exit.HasField('exit_lane_id'):
exit_dict[junction_exit.exit_lane_id] = \
BoundingRectangle(junction_exit.exit_position.x,
junction_exit.exit_position.y,
junction_exit.exit_heading,
0.01,
junction_exit.exit_width)
exit_pos = np.array([junction_exit.exit_position.x,
junction_exit.exit_position.y])
exit_pos_dict[junction_exit.exit_lane_id] = exit_pos
delta_pos = exit_pos - curr_pos
angle = math.atan2(delta_pos[1], delta_pos[0]) - heading
d_idx = int((angle / (2.0 * np.pi) + 1.0 / 24) * 12 % 12)
mask[d_idx] = 1
# Searching for up to 100 frames (10 seconds)
for j in range(i, min(i + 100, feature_seq_len)):
car_bounding = BoundingRectangle(feature_sequence[j].position.x,
feature_sequence[j].position.y,
math.atan2(feature_sequence[j].raw_velocity.y,
feature_sequence[j].raw_velocity.x),
feature_sequence[j].length,
feature_sequence[j].width)
for key, value in exit_dict.items():
if car_bounding.overlap(value):
exit_pos = exit_pos_dict[key]
delta_pos = exit_pos - curr_pos
angle = math.atan2(
delta_pos[1], delta_pos[0]) - heading
d_idx = int((angle / (2.0 * np.pi) + 1.0 / 24) * 12 % 12)
label = [0] * 12
label[d_idx] = 1
fea.junction_feature.junction_mlp_label.extend(label)
self.junction_label_dict["{}@{:.3f}".format(
fea.id, fea.timestamp)] = label + mask
break # actually break two level
else:
continue
break
np.save(self.filepath + '.junction_label.npy', self.junction_label_dict)
# if fea.HasField('junction_feature') and \
# len(fea.junction_feature.junction_mlp_label) > 0:
# output_features.feature.add().CopyFrom(fea)
# self.SaveOutputPB(self.filepath + '.junction.label', output_features)
def Label(self):
self.LabelTrajectory()
self.LabelSingleLane()
self.LabelJunctionExit()
# TODO(all):
# - implement label multiple lane
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/common/BUILD
|
load("@rules_python//python:defs.bzl", "py_library")
package(default_visibility = ["//visibility:public"])
py_library(
name = "bounding_rectangle",
srcs = ["bounding_rectangle.py"],
deps = [
":rotation2d",
":util",
":vector2d",
],
)
py_library(
name = "configure",
srcs = ["configure.py"],
)
py_library(
name = "data_preprocess",
srcs = ["data_preprocess.py"],
)
py_library(
name = "feature_io",
srcs = ["feature_io.py"],
deps = [
"//modules/common_msgs/prediction_msgs:feature_py_pb2",
"//modules/prediction/proto:offline_features_py_pb2",
],
)
py_library(
name = "log",
srcs = ["log.py"],
)
py_library(
name = "online_to_offline",
srcs = ["online_to_offline.py"],
deps = [
":bounding_rectangle",
":configure",
"//modules/prediction/proto:offline_features_py_pb2",
],
)
py_library(
name = "rotation2d",
srcs = ["rotation2d.py"],
deps = [
":vector2d",
],
)
py_library(
name = "trajectory",
srcs = ["trajectory.py"],
deps = [
":bounding_rectangle",
":configure",
],
)
py_library(
name = "util",
srcs = ["util.py"],
)
py_library(
name = "vector2d",
srcs = ["vector2d.py"],
)
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/common/vector2d.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
from math import sqrt
class Vector2:
def __init__(self, x, y):
self.x = x
self.y = y
def add(self, v):
return Vector2(self.x + v.x, self.y + v.y)
def subtract(self, v):
return Vector2(self.x - v.x, self.y - v.y)
def dot(self, v):
return self.x * v.x + self.y * v.y
def norm(self):
return sqrt(self.x * self.x + self.y * self.y)
def norm_square(self):
return self.x * self.x + self.y * self.y
def print_point(self):
print(str(self.x) + "\t" + str(self.y) + "\n")
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/merge_label_dicts_script.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
#
# Usage:
# sudo bash /apollo/modules/tools/prediction/mlp_train/scripts/generate_labels.sh <input_feature.bin>
#
# The input feature.X.bin will generate furture_status.label, cruise.label, junction.label
SRC_FILE=$1
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
/apollo/bazel-bin/modules/tools/prediction/data_pipelines/data_preprocessing/merge_label_dicts ${SRC_FILE}
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/records_to_prediction_result.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
TARGET_DIR=$2
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ ! -z "$4" ]; then
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$4
fi
sudo mkdir -p ${TARGET_DIR}
if [ -z "$3" ]; then
MAP_DIR="sunnyvale"
else
MAP_DIR=$3
fi
/apollo/bazel-bin/modules/prediction/pipeline/records_to_offline_data \
--flagfile=/apollo/modules/prediction/conf/prediction.conf \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--prediction_offline_mode=3 \
--prediction_offline_bags=${SRC_DIR} \
--noenable_multi_thread \
--prediction_data_dir=${TARGET_DIR}
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/records_to_data_for_learning.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
TARGET_DIR=$2
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ ! -z "$4" ]; then
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$4
fi
sudo mkdir -p ${TARGET_DIR}
if [ -z "$3" ]; then
MAP_DIR="sunnyvale"
else
MAP_DIR=$3
fi
/apollo/bazel-bin/modules/prediction/pipeline/records_to_offline_data \
--flagfile=/apollo/modules/prediction/conf/prediction.conf \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--prediction_offline_mode=2 \
--prediction_offline_bags=${SRC_DIR} \
--prediction_data_dir=${TARGET_DIR} \
--noenable_multi_thread \
--noenable_async_draw_base_image
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/records_to_dump_feature_proto.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
TARGET_DIR=$2
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ ! -z "$4" ]; then
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$4
fi
sudo mkdir -p ${TARGET_DIR}
if [ -z "$3" ]; then
MAP_DIR="sunnyvale"
else
MAP_DIR=$3
fi
/apollo/bazel-bin/modules/prediction/pipeline/records_to_offline_data \
--flagfile=/apollo/modules/prediction/conf/prediction.conf \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--prediction_offline_mode=1 \
--noenable_multi_thread \
--prediction_offline_bags=${SRC_DIR} \
--prediction_data_dir=${TARGET_DIR}
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/combine_features_and_labels_script.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
#
# Usage:
# sudo bash /apollo/modules/tools/prediction/mlp_train/scripts/generate_labels.sh <input_feature.bin>
#
# The input feature.X.bin will generate furture_status.label, cruise.label, junction.label
SRC_DIR=$1
LBL_DIR=$2
SCENARIO=$3
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ ${SCENARIO} == "junction" ]; then
/apollo/bazel-bin/modules/tools/prediction/data_pipelines/data_preprocessing/combine_features_and_labels_for_junction ${SRC_DIR} ${LBL_DIR}
else
/apollo/bazel-bin/modules/tools/prediction/data_pipelines/data_preprocessing/combine_features_and_labels ${SRC_DIR} ${LBL_DIR}
fi
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/records_to_dump_records.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2020 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ ! -z "$3" ]; then
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$3
fi
if [ -z "$2" ]; then
MAP_DIR="sunnyvale"
else
MAP_DIR=$2
fi
/apollo/bazel-bin/modules/prediction/pipeline/records_to_offline_data \
--flagfile=/apollo/modules/prediction/conf/prediction.conf \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--prediction_offline_mode=6 \
--prediction_offline_bags=${SRC_DIR} \
--noenable_multi_thread \
--noenable_async_draw_base_image \
--enable_all_pedestrian_caution_in_front \
--noenable_rank_caution_obstacles
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/vector_net.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2021 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
OBSTACLE_X=$1
OBSTACLE_Y=$2
OBSTACLE_PHI=$3
TARGET_FILE=$4
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ -z "$5" ]; then
MAP_DIR="sunnyvale"
else
MAP_DIR=$5
fi
/apollo/bazel-bin/modules/prediction/pipeline/vector_net_feature \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--prediction_target_file=${TARGET_FILE} \
--obstacle_x=${OBSTACLE_X} \
--obstacle_y=${OBSTACLE_Y} \
--obstacle_phi=${OBSTACLE_PHI}
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/records_to_frame_env.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
TARGET_DIR=$2
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ ! -z "$4" ]; then
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$4
fi
sudo mkdir -p ${TARGET_DIR}
if [ -z "$3" ]; then
MAP_DIR="sunnyvale"
else
MAP_DIR=$3
fi
/apollo/bazel-bin/modules/prediction/pipeline/records_to_offline_data \
--flagfile=/apollo/modules/prediction/conf/prediction.conf \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--prediction_offline_mode=4 \
--noenable_multi_thread \
--prediction_offline_bags=${SRC_DIR} \
--prediction_data_dir=${TARGET_DIR} \
--max_num_dump_feature=1000 \
--noenable_semantic_map \
--noenable_async_draw_base_image
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/records_to_data_for_tuning.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
TARGET_DIR=$2
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
if [ ! -z "$4" ]; then
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$4
fi
sudo mkdir -p ${TARGET_DIR}
if [ -z "$3" ]; then
MAP_DIR="sunnyvale"
else
MAP_DIR=$3
fi
/apollo/bazel-bin/modules/prediction/pipeline/records_to_offline_data \
--flagfile=/apollo/modules/prediction/conf/prediction.conf \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--prediction_offline_mode=5 \
--noenable_multi_thread \
--prediction_offline_bags=${SRC_DIR} \
--prediction_data_dir=${TARGET_DIR} \
--noenable_multi_thread
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/evaluate_prediction_result_script.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
#
# Usage:
# sudo bash /apollo/modules/tools/prediction/data_pipelines/scripts/evaluate_prediction_result_script.sh
# <results_dir> <labels_dir> <time_range>
#
RESULTS_DIR=$1
LABELS_DIR=$2
TIME_RANGE=$3
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
/apollo/bazel-bin/modules/tools/prediction/data_pipelines/performance_evaluation/evaluate_prediction_result \
${RESULTS_DIR} ${LABELS_DIR} ${TIME_RANGE}
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/scripts/generate_labels.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
#
# Usage:
# sudo bash /apollo/modules/tools/prediction/mlp_train/scripts/generate_labels.sh <input_feature.bin>
#
# The input feature.X.bin will generate 4 files: .npy, .furture_status.npy, cruise_label.npy, junction_label.npy
SRC_FILE=$1
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
/apollo/bazel-bin/modules/tools/prediction/data_pipelines/data_preprocessing/generate_labels ${SRC_FILE}
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/merge_label_dicts.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import modules.tools.prediction.data_pipelines.data_preprocessing.features_labels_utils as features_labels_utils
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Merge all label_dicts in each'
'terminal folder.')
parser.add_argument('dirpath', type=str, help='Path of terminal folder.')
args = parser.parse_args()
features_labels_utils.MergeDicts(args.dirpath, dict_name='future_status')
features_labels_utils.MergeDicts(args.dirpath, dict_name='junction_label')
features_labels_utils.MergeDicts(args.dirpath, dict_name='cruise_label')
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/generate_cruise_labels.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import glob
import logging
import os
import sys
from modules.tools.prediction.data_pipelines.common.online_to_offline import LabelGenerator
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Generate labels')
parser.add_argument('input', type=str, help='input file')
args = parser.parse_args()
label_gen = LabelGenerator()
print("Create Label {}".format(args.input))
if os.path.isfile(args.input):
label_gen.LoadFeaturePBAndSaveLabelFiles(args.input)
label_gen.LabelSingleLane()
else:
print("{} is not a valid file".format(args.input))
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/features_labels_utils.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import h5py
import numpy as np
import os
from modules.prediction.proto import offline_features_pb2
junction_label_label_dim = 12
future_status_label_dim = 30
'''
Read a single dataforlearn.bin file and output a list of DataForLearning
that is contained in that file.
'''
def LoadDataForLearning(filepath):
list_of_data_for_learning = \
offline_features_pb2.ListDataForLearning()
with open(filepath, 'rb') as file_in:
list_of_data_for_learning.ParseFromString(file_in.read())
return list_of_data_for_learning.data_for_learning
'''
Read a single .npy dictionary file and get its content.
'''
def LoadLabels(filepath):
mydict = np.load(filepath).item()
return mydict
'''
Merge two dictionary into a single one and return.
'''
def MergeTwoDicts(dict1, dict2):
newdict = dict1.copy()
newdict.update(dict2)
return newdict
'''
Merge all dictionaries directly under a directory
'''
def MergeDicts(dirpath, dict_name='future_status'):
list_of_files = os.listdir(dirpath)
dict_merged = None
for file in list_of_files:
full_path = os.path.join(dirpath, file)
if file.split('.')[-1] == 'npy' and file.split('.')[-2] == dict_name:
dict_curr = LoadLabels(full_path)
if dict_merged is None:
dict_merged = dict_curr.copy()
else:
dict_merged.update(dict_curr)
np.save(dirpath + '/' + dict_name + '.npy', dict_merged)
return dict_merged
'''
Go through every entry of data_for_learn proto and get the corresponding labels.
Save the output file into h5 format (array of lists with each list being a data
point for training/validating).
'''
def CombineFeaturesAndLabels(feature_path, label_path, dict_name='future_status'):
list_of_data_for_learning = LoadDataForLearning(feature_path)
dict_labels = LoadLabels(label_path)
output_np_array = []
for data_for_learning in list_of_data_for_learning:
# features_for_learning: list of doubles
features_for_learning = list(data_for_learning.features_for_learning)
key = "{}@{:.3f}".format(data_for_learning.id, data_for_learning.timestamp)
# Sanity checks to see if this data-point is valid or not.
if key not in dict_labels:
print('Cannot find a feature-to-label mapping.')
continue
labels = None
list_curr = None
if dict_name == 'junction_label':
if len(dict_labels[key]) != junction_label_label_dim:
continue
labels = dict_labels[key]
list_curr = features_for_learning + labels
elif dict_name == 'future_status':
if len(dict_labels[key]) < future_status_label_dim:
continue
labels = dict_labels[key][:30]
list_curr = [len(features_for_learning)] + \
features_for_learning + labels
output_np_array.append(list_curr)
output_np_array = np.array(output_np_array)
np.save(feature_path + '.features+' + dict_name + '.npy', output_np_array)
'''
Merge all files of features+labels into a single one
'''
def MergeCombinedFeaturesAndLabels(dirpath):
list_of_files = os.listdir(dirpath)
features_labels_merged = []
for file in list_of_files:
full_path = os.path.join(dirpath, file)
if file.split('.')[-1] == 'npy' and \
file.split('.')[-2] == 'labels' and \
file.split('.')[0] == 'datalearn':
features_labels_curr = np.load(full_path).tolist()
features_labels_merged += features_labels_curr
np.save(dirpath + '/training_data.npy', np.array(features_labels_merged))
'''
It takes terminal folder as input, then
1. Merge all label dicts.
2. Go through every data_for_learn proto, and find the corresponding label
3. Merge all features+labels files into a single one: data.npy
'''
def PrepareDataForTraining(dirpath):
MergeDicts(dirpath)
list_of_files = os.listdir(dirpath)
for file in list_of_files:
full_path = os.path.join(dirpath, file)
if file.split('.')[-1] == 'bin' and \
file.split('.')[0] == 'datalearn':
CombineFeaturesAndLabels(full_path, dirpath + 'labels.npy')
MergeCombinedFeaturesAndLabels(dirpath)
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/combine_features_and_labels.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import os
import re
from modules.tools.prediction.data_pipelines.data_preprocessing.features_labels_utils import CombineFeaturesAndLabels, MergeCombinedFeaturesAndLabels
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Merge all label_dicts in each'
'terminal folder.')
parser.add_argument('features_dirpath', type=str,
help='Path of terminal folder for data_for_learn.')
parser.add_argument('labels_dirpath', type=str,
help='Path of terminal folder for labels')
args = parser.parse_args()
list_of_files = os.listdir(args.features_dirpath)
for file in list_of_files:
full_file_path = os.path.join(args.features_dirpath, file)
if file.split('.')[-1] == 'bin' and \
file.split('.')[0] == 'datalearn':
label_path = args.labels_dirpath
CombineFeaturesAndLabels(full_file_path, label_path + '/labels.npy')
MergeCombinedFeaturesAndLabels(args.features_dirpath)
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/generate_labels.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import glob
import logging
import os
import sys
from modules.tools.prediction.data_pipelines.common.online_to_offline import LabelGenerator
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Generate labels')
parser.add_argument('input', type=str, help='input file')
args = parser.parse_args()
label_gen = LabelGenerator()
print("Create Label {}".format(args.input))
if os.path.isfile(args.input):
label_gen.LoadFeaturePBAndSaveLabelFiles(args.input)
label_gen.Label()
else:
print("{} is not a valid file".format(args.input))
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/generate_junction_labels.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import glob
import logging
import os
import sys
from modules.tools.prediction.data_pipelines.common.online_to_offline import LabelGenerator
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Generate labels')
parser.add_argument('input', type=str, help='input file')
args = parser.parse_args()
label_gen = LabelGenerator()
print("Create Label {}".format(args.input))
if os.path.isfile(args.input):
label_gen.LoadFeaturePBAndSaveLabelFiles(args.input)
label_gen.LabelJunctionExit()
else:
print("{} is not a valid file".format(args.input))
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary", "py_library")
package(default_visibility = ["//visibility:public"])
py_library(
name = "combine_features_and_labels",
srcs = ["combine_features_and_labels.py"],
deps = [
":features_labels_utils",
],
)
py_library(
name = "combine_features_and_labels_for_junction",
srcs = ["combine_features_and_labels_for_junction.py"],
deps = [
":features_labels_utils",
],
)
py_library(
name = "features_labels_utils",
srcs = ["features_labels_utils.py"],
deps = [
"//modules/prediction/proto:offline_features_py_pb2",
],
)
py_binary(
name = "generate_cruise_labels",
srcs = ["generate_cruise_labels.py"],
deps = [
"//modules/tools/prediction/data_pipelines/common:online_to_offline",
],
)
py_binary(
name = "generate_future_trajectory",
srcs = ["generate_future_trajectory.py"],
deps = [
"//modules/tools/prediction/data_pipelines/common:online_to_offline",
],
)
py_binary(
name = "generate_junction_labels",
srcs = ["generate_junction_labels.py"],
deps = [
"//modules/tools/prediction/data_pipelines/common:online_to_offline",
],
)
py_binary(
name = "generate_labels",
srcs = ["generate_labels.py"],
deps = [
"//modules/tools/prediction/data_pipelines/common:online_to_offline",
],
)
py_binary(
name = "merge_label_dicts",
srcs = ["merge_label_dicts.py"],
deps = [
":features_labels_utils",
],
)
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/generate_future_trajectory.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import glob
import logging
import os
import sys
from modules.tools.prediction.data_pipelines.common.online_to_offline import LabelGenerator
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Generate labels')
parser.add_argument('input', type=str, help='input file')
args = parser.parse_args()
label_gen = LabelGenerator()
print("Create Label {}".format(args.input))
if os.path.isfile(args.input):
label_gen.LoadFeaturePBAndSaveLabelFiles(args.input)
label_gen.LabelTrajectory()
else:
print("{} is not a valid file".format(args.input))
| 0
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines
|
apollo_public_repos/apollo/modules/tools/prediction/data_pipelines/data_preprocessing/combine_features_and_labels_for_junction.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import os
import re
from modules.tools.prediction.data_pipelines.data_preprocessing.features_labels_utils import CombineFeaturesAndLabels
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description='Merge all label_dicts in each terminal folder.')
parser.add_argument('features_dirpath', type=str,
help='Path of terminal folder for data_for_learn.')
parser.add_argument('labels_dirpath', type=str,
help='Path of terminal folder for labels')
args = parser.parse_args()
list_of_files = os.listdir(args.features_dirpath)
for file in list_of_files:
full_file_path = os.path.join(args.features_dirpath, file)
if file.split('.')[-1] == 'bin' and \
file.split('.')[0] == 'datalearn':
label_path = args.labels_dirpath
CombineFeaturesAndLabels(full_file_path, label_path +
'/junction_label.npy', 'junction_label')
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/counting.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import numpy as np
import os
from collections import Counter
from glob import glob
feature_dim = 62
count = Counter()
filenames = glob('/tmp/data/feature_v1_bin/*/*.label.bin')
for filename in filenames:
bin_data = np.fromfile(filename, dtype=np.float32)
if bin_data.shape[0] % (feature_dim + 1) != 0:
raise ValueError('data size (%d) must be multiple of feature_dim + 1 (%d).' %
(bin_data.shape[0], feature_dim + 1))
label = bin_data[feature_dim::(feature_dim+1)].astype(np.int32)
count.update(label)
print(count)
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/convert_to_tfrecords.py
|
#!/usr/bin/env python3
###############################################################################
# Modification Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Converts MLP data to TFRecords file format with Example protos."""
import argparse
import os
import sys
import numpy as np
import tensorflow as tf
FLAGS = None
feature_dim = 62
def _float_feature(value):
return tf.train.Feature(float_list=tf.train.FloatList(value=value))
def convert_to(bin_data, name):
"""Converts bin_data to tfrecords."""
if bin_data.shape[0] % (feature_dim + 1) != 0:
raise ValueError(
'data size (%d) must be multiple of feature_dim + 1 (%d).' %
(bin_data.shape[0], feature_dim + 1))
num_examples = bin_data.shape[0] // (feature_dim + 1)
print("num_examples:", num_examples)
filename = os.path.join(name + '.tfrecords')
print('Writing', filename)
with tf.python_io.TFRecordWriter(filename) as writer:
for index in range(0, num_examples):
data_raw = bin_data[index * (feature_dim + 1):index *
(feature_dim + 1) + feature_dim]
label_raw = np.array(
[bin_data[index*(feature_dim + 1)+feature_dim]])
example = tf.train.Example(
features=tf.train.Features(
feature={
'data': _float_feature(data_raw),
'label': _float_feature(label_raw)
}))
writer.write(example.SerializeToString())
def main(unused_argv):
# Get the data.
for path, subdirs, files in os.walk(FLAGS.directory):
print("path:", path)
print("subdirs:", subdirs)
for name in files:
filename = os.path.join(path, name)
print("processing ", filename)
bin_data = np.fromfile(filename, dtype=np.float32)
# Convert to Examples and write the result to TFRecords.
convert_to(bin_data, filename)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'--directory',
type=str,
default='/tmp/data/prediction',
help='Directory to download data files and write the converted result')
FLAGS, unparsed = parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/mlp_main.py
|
#!/usr/bin/env python3
###############################################################################
# Modification Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Mlp model for classifying prediction from Mlp dataset.
"""
import argparse
import functools
import itertools
import os
import six
import modules.tools.multiple_gpu_estimator.mlp_data
import modules.tools.multiple_gpu_estimator.mlp_model
import modules.tools.multiple_gpu_estimator.mlp_utils
import numpy as np
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.INFO)
def get_model_fn(num_gpus, variable_strategy, num_workers):
"""Returns a function that will build the mlp model."""
def _mlp_model_fn(features, labels, mode, params):
"""Mlp model body.
Support single host, one or more GPU training. Parameter distribution can
be either one of the following scheme.
1. CPU is the parameter server and manages gradient updates.
2. Parameters are distributed evenly across all GPUs, and the first GPU
manages gradient updates.
Args:
features: a list of tensors, one for each tower
labels: a list of tensors, one for each tower
mode: ModeKeys.TRAIN or EVAL
params: Hyperparameters suitable for tuning
Returns:
A EstimatorSpec object.
"""
is_training = (mode == tf.estimator.ModeKeys.TRAIN)
weight_decay = params.weight_decay
momentum = params.momentum
tower_features = features
tower_labels = labels
tower_losses = []
tower_gradvars = []
tower_preds = []
# channels first (NCHW) is normally optimal on GPU and channels last (NHWC)
# on CPU. The exception is Intel MKL on CPU which is optimal with
# channels_last.
data_format = params.data_format
if not data_format:
if num_gpus == 0:
data_format = 'channels_last'
else:
data_format = 'channels_first'
if num_gpus == 0:
num_devices = 1
device_type = 'cpu'
else:
num_devices = num_gpus
device_type = 'gpu'
for i in range(num_devices):
worker_device = '/{}:{}'.format(device_type, i)
if variable_strategy == 'CPU':
device_setter = mlp_utils.local_device_setter(
worker_device=worker_device)
elif variable_strategy == 'GPU':
device_setter = mlp_utils.local_device_setter(
ps_device_type='gpu',
worker_device=worker_device,
ps_strategy=tf.contrib.training.
GreedyLoadBalancingStrategy(
num_gpus, tf.contrib.training.byte_size_load_fn))
with tf.variable_scope('mlp', reuse=bool(i != 0)):
with tf.name_scope('tower_%d' % i) as name_scope:
with tf.device(device_setter):
loss, gradvars, preds = _tower_fn(
is_training, weight_decay, tower_features[i],
tower_labels[i], data_format,
params.batch_norm_decay, params.batch_norm_epsilon)
tower_losses.append(loss)
tower_gradvars.append(gradvars)
tower_preds.append(preds)
if i == 0:
# Only trigger batch_norm moving mean and variance update from
# the 1st tower. Ideally, we should grab the updates from all
# towers but these stats accumulate extremely fast so we can
# ignore the other stats from the other towers without
# significant detriment.
update_ops = tf.get_collection(
tf.GraphKeys.UPDATE_OPS, name_scope)
# Now compute global loss and gradients.
gradvars = []
with tf.name_scope('gradient_averaging'):
all_grads = {}
for grad, var in itertools.chain(*tower_gradvars):
if grad is not None:
all_grads.setdefault(var, []).append(grad)
for var, grads in six.iteritems(all_grads):
# Average gradients on the same device as the variables
# to which they apply.
with tf.device(var.device):
if len(grads) == 1:
avg_grad = grads[0]
else:
avg_grad = tf.multiply(
tf.add_n(grads), 1. / len(grads))
gradvars.append((avg_grad, var))
# Device that runs the ops to apply global gradient updates.
consolidation_device = '/gpu:0' if variable_strategy == 'GPU' else '/cpu:0'
with tf.device(consolidation_device):
num_batches_per_epoch = mlp_data.MlpDataSet.num_examples_per_epoch(
'train') // (params.train_batch_size * num_workers)
boundaries = [
num_batches_per_epoch * x
for x in np.array([20, 50, 80], dtype=np.int64)
]
staged_lr = [
params.learning_rate * x for x in [1, 0.1, 0.01, 0.002]
]
learning_rate = tf.train.piecewise_constant(
tf.train.get_global_step(), boundaries, staged_lr)
loss = tf.reduce_mean(tower_losses, name='loss')
examples_sec_hook = mlp_utils.ExamplesPerSecondHook(
params.train_batch_size, every_n_steps=10)
tensors_to_log = {'learning_rate': learning_rate, 'loss': loss}
logging_hook = tf.train.LoggingTensorHook(
tensors=tensors_to_log, every_n_iter=100)
train_hooks = [logging_hook, examples_sec_hook]
optimizer = tf.train.MomentumOptimizer(
learning_rate=learning_rate, momentum=momentum)
if params.sync:
optimizer = tf.train.SyncReplicasOptimizer(
optimizer, replicas_to_aggregate=num_workers)
sync_replicas_hook = optimizer.make_session_run_hook(
params.is_chief)
train_hooks.append(sync_replicas_hook)
# Create single grouped train op
train_op = [
optimizer.apply_gradients(
gradvars, global_step=tf.train.get_global_step())
]
train_op.extend(update_ops)
train_op = tf.group(*train_op)
predictions = {
'classes':
tf.concat([p['classes'] for p in tower_preds], axis=0),
'probabilities':
tf.concat([p['probabilities'] for p in tower_preds], axis=0)
}
stacked_labels = tf.concat(labels, axis=0)
metrics = {
'accuracy':
tf.metrics.accuracy(stacked_labels, predictions['classes'])
}
return tf.estimator.EstimatorSpec(
mode=mode,
predictions=predictions,
loss=loss,
train_op=train_op,
training_hooks=train_hooks,
eval_metric_ops=metrics)
return _mlp_model_fn
def _tower_fn(is_training, weight_decay, feature, label, data_format,
batch_norm_decay, batch_norm_epsilon):
"""Build computation tower.
Args:
is_training: true if is training graph.
weight_decay: weight regularization strength, a float.
feature: a Tensor.
label: a Tensor.
data_format: channels_last (NHWC) or channels_first (NCHW).
batch_norm_decay: decay for batch normalization, a float.
batch_norm_epsilon: epsilon for batch normalization, a float.
Returns:
A tuple with the loss for the tower, the gradients and parameters, and
predictions.
"""
model = mlp_model.MlpModel(
batch_norm_decay=batch_norm_decay,
batch_norm_epsilon=batch_norm_epsilon,
is_training=is_training,
data_format=data_format)
logits = model.forward_pass(feature, input_data_format='channels_last')
tower_pred = {
'classes': tf.argmax(input=logits, axis=1),
'probabilities': tf.nn.softmax(logits)
}
tower_loss = tf.losses.sparse_softmax_cross_entropy(
logits=logits, labels=label)
tower_loss = tf.reduce_mean(tower_loss)
model_params = tf.trainable_variables()
tower_loss += weight_decay * tf.add_n(
[tf.nn.l2_loss(v) for v in model_params])
tower_grad = tf.gradients(tower_loss, model_params)
return tower_loss, list(zip(tower_grad, model_params)), tower_pred
def input_fn(data_dir, subset, num_shards, batch_size):
"""Create input graph for model.
Args:
data_dir: Directory where TFRecords representing the dataset are located.
subset: one of 'train', 'validate' and 'eval'.
num_shards: num of towers participating in data-parallel training.
batch_size: total batch size for training to be divided by the number of
shards.
Returns:
two lists of tensors for features and labels, each of num_shards length.
"""
with tf.device('/cpu:0'):
dataset = mlp_data.MlpDataSet(data_dir, subset)
image_batch, label_batch = dataset.make_batch(batch_size)
if num_shards <= 1:
# No GPU available or only 1 GPU.
return [image_batch], [label_batch]
# Note that passing num=batch_size is safe here, even though
# dataset.batch(batch_size) can, in some cases, return fewer than batch_size
# examples. This is because it does so only when repeating for a limited
# number of epochs, but our dataset repeats forever.
image_batch = tf.unstack(image_batch, num=batch_size, axis=0)
label_batch = tf.unstack(label_batch, num=batch_size, axis=0)
feature_shards = [[] for i in range(num_shards)]
label_shards = [[] for i in range(num_shards)]
for i in range(batch_size):
idx = i % num_shards
feature_shards[idx].append(image_batch[i])
label_shards[idx].append(label_batch[i])
feature_shards = [tf.parallel_stack(x) for x in feature_shards]
label_shards = [tf.parallel_stack(x) for x in label_shards]
return feature_shards, label_shards
def get_experiment_fn(
data_dir,
num_gpus,
variable_strategy,
):
"""Returns an Experiment function.
Experiments perform training on several workers in parallel,
in other words experiments know how to invoke train and eval in a sensible
fashion for distributed training. Arguments passed directly to this
function are not tunable, all other arguments should be passed within
tf.HParams, passed to the enclosed function.
Args:
data_dir: str. Location of the data for input_fns.
num_gpus: int. Number of GPUs on each worker.
variable_strategy: String. CPU to use CPU as the parameter server
and GPU to use the GPUs as the parameter server.
Returns:
A function (tf.estimator.RunConfig, tf.contrib.training.HParams) ->
tf.contrib.learn.Experiment.
Suitable for use by tf.contrib.learn.learn_runner, which will run various
methods on Experiment (train, evaluate) based on information
about the current runner in `run_config`.
"""
def _experiment_fn(run_config, hparams):
"""Returns an Experiment."""
# Create estimator.
train_input_fn = functools.partial(
input_fn,
data_dir,
subset='train',
num_shards=num_gpus,
batch_size=hparams.train_batch_size)
eval_input_fn = functools.partial(
input_fn,
data_dir,
subset='eval',
batch_size=hparams.eval_batch_size,
num_shards=num_gpus)
num_eval_examples = mlp_data.MlpDataSet.num_examples_per_epoch('eval')
if num_eval_examples % hparams.eval_batch_size != 0:
raise ValueError(
'validation set size must be multiple of eval_batch_size')
train_steps = hparams.train_steps
eval_steps = num_eval_examples // hparams.eval_batch_size
classifier = tf.estimator.Estimator(
model_fn=get_model_fn(num_gpus, variable_strategy,
run_config.num_worker_replicas or 1),
config=run_config,
params=hparams)
# Create experiment.
return tf.contrib.learn.Experiment(
classifier,
train_input_fn=train_input_fn,
eval_input_fn=eval_input_fn,
train_steps=train_steps,
eval_steps=eval_steps)
return _experiment_fn
def main(job_dir, data_dir, num_gpus, variable_strategy, log_device_placement,
num_intra_threads, **hparams):
# The env variable is on deprecation path, default is set to off.
os.environ['TF_SYNC_ON_FINISH'] = '0'
os.environ['TF_ENABLE_WINOGRAD_NONFUSED'] = '1'
# Session configuration.
sess_config = tf.ConfigProto(
allow_soft_placement=True,
log_device_placement=log_device_placement,
intra_op_parallelism_threads=num_intra_threads,
gpu_options=tf.GPUOptions(force_gpu_compatible=True))
config = mlp_utils.RunConfig(session_config=sess_config, model_dir=job_dir)
tf.contrib.learn.learn_runner.run(
get_experiment_fn(data_dir, num_gpus, variable_strategy),
run_config=config,
hparams=tf.contrib.training.HParams(
is_chief=config.is_chief, **hparams))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'--data-dir',
type=str,
required=True,
help='The directory where the CIFAR-10 input data is stored.')
parser.add_argument(
'--job-dir',
type=str,
required=True,
help='The directory where the model will be stored.')
parser.add_argument(
'--variable-strategy',
choices=['CPU', 'GPU'],
type=str,
default='CPU',
help='Where to locate variable operations')
parser.add_argument(
'--num-gpus',
type=int,
default=1,
help='The number of gpus used. Uses only CPU if set to 0.')
parser.add_argument(
'--train-steps',
type=int,
default=20000,
help='The number of steps to use for training.')
parser.add_argument(
'--train-batch-size',
type=int,
default=10000,
help='Batch size for training.')
parser.add_argument(
'--eval-batch-size',
type=int,
default=10000,
help='Batch size for validation.')
parser.add_argument(
'--momentum',
type=float,
default=0.9,
help='Momentum for MomentumOptimizer.')
parser.add_argument(
'--weight-decay',
type=float,
default=2e-4,
help='Weight decay for convolutions.')
parser.add_argument(
'--learning-rate',
type=float,
default=0.1,
help="""\
This is the initial learning rate value. The learning rate will decrease
during training. For more details check the model_fn implementation in
this file.\
""")
parser.add_argument(
'--sync',
action='store_true',
default=False,
help="""\
If present when running in a distributed environment will run on sync mode.\
""")
parser.add_argument(
'--num-intra-threads',
type=int,
default=0,
help="""\
Number of threads to use for intra-op parallelism. When training on CPU
set to 0 to have the system pick the appropriate number or alternatively
set it to the number of physical CPU cores.\
""")
parser.add_argument(
'--num-inter-threads',
type=int,
default=0,
help="""\
Number of threads to use for inter-op parallelism. If set to 0, the
system will pick an appropriate number.\
""")
parser.add_argument(
'--data-format',
type=str,
default=None,
help="""\
If not set, the data format best for the training device is used.
Allowed values: channels_first (NCHW) channels_last (NHWC).\
""")
parser.add_argument(
'--log-device-placement',
action='store_true',
default=False,
help='Whether to log device placement.')
parser.add_argument(
'--batch-norm-decay',
type=float,
default=0.997,
help='Decay for batch norm.')
parser.add_argument(
'--batch-norm-epsilon',
type=float,
default=1e-5,
help='Epsilon for batch norm.')
args = parser.parse_args()
if args.num_gpus > 0:
assert tf.test.is_gpu_available(), "Requested GPUs but none found."
if args.num_gpus < 0:
raise ValueError(
'Invalid GPU count: \"--num-gpus\" must be 0 or a positive integer.'
)
if args.num_gpus == 0 and args.variable_strategy == 'GPU':
raise ValueError(
'num-gpus=0, CPU must be used as parameter server. Set'
'--variable-strategy=CPU.')
if args.num_gpus != 0 and args.train_batch_size % args.num_gpus != 0:
raise ValueError('--train-batch-size must be multiple of --num-gpus.')
if args.num_gpus != 0 and args.eval_batch_size % args.num_gpus != 0:
raise ValueError('--eval-batch-size must be multiple of --num-gpus.')
main(**vars(args))
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/mlp_data.py
|
#!/usr/bin/env python3
###############################################################################
# Modification Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Prediction data set"""
import os
import tensorflow as tf
dim_input = 62
class MlpDataSet(object):
"""Prediction mlp data set.
"""
def __init__(self, data_dir, subset='train'):
self.data_dir = data_dir
self.subset = subset
def get_filenames(self):
if self.subset in ['train', 'validation', 'eval']:
return [os.path.join(self.data_dir, self.subset + '.tfrecords')]
else:
raise ValueError('Invalid data subset "%s"' % self.subset)
def parser(self, serialized_example):
"""Parses a single tf.Example into image and label tensors."""
# Dimensions of the images in the CIFAR-10 dataset.
features = tf.parse_single_example(
serialized_example,
features={
'data': tf.FixedLenFeature([62], tf.float32),
'label': tf.FixedLenFeature([1], tf.float32),
})
image = features['data']
label = tf.cast(features['label'], tf.int32)+1
return image, label
def make_batch(self, batch_size):
"""Read the images and labels from 'filenames'."""
filenames = self.get_filenames()
# Repeat infinitely.
dataset = tf.data.TFRecordDataset(filenames).repeat()
# Parse records.
dataset = dataset.map(self.parser, num_parallel_calls=batch_size)
# Potentially shuffle records.
if self.subset == 'train':
min_queue_examples = int(
MlpDataSet.num_examples_per_epoch(self.subset) * 0.1)
# Ensure that the capacity is sufficiently large to provide good random
# shuffling.
dataset = dataset.shuffle(buffer_size=min_queue_examples +
3 * batch_size)
# Batch it up.
dataset = dataset.batch(batch_size)
iterator = dataset.make_one_shot_iterator()
image_batch, label_batch = iterator.get_next()
return image_batch, label_batch
@staticmethod
def num_examples_per_epoch(subset='train'):
if subset == 'train':
return 13000000
elif subset == 'validation':
return 1600000
elif subset == 'eval':
return 1600000
else:
raise ValueError('Invalid data subset "%s"' % subset)
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/model_base.py
|
#!/usr/bin/env python3
###############################################################################
# Modification Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
import tensorflow as tf
class ModelBase(object):
def __init__(self,
is_training=True,
data_format='channels_last',
batch_norm_decay=0.999,
batch_norm_epsilon=0.001):
"""ModelBase constructor.
Args:
is_training: if build training or inference model.
data_format: the data_format used during computation.
one of 'channels_first' or 'channels_last'.
"""
self._batch_norm_decay = batch_norm_decay
self._batch_norm_epsilon = batch_norm_epsilon
self._is_training = is_training
assert data_format in ('channels_first', 'channels_last')
self._data_format = data_format
def forward_pass(self, x):
raise NotImplementedError(
'forward_pass() is implemented in ResNet sub classes')
def _conv(self, x, kernel_size, filters, strides, is_atrous=False):
"""Convolution."""
padding = 'SAME'
if not is_atrous and strides > 1:
pad = kernel_size - 1
pad_beg = pad // 2
pad_end = pad - pad_beg
if self._data_format == 'channels_first':
x = tf.pad(
x,
[[0, 0], [0, 0], [pad_beg, pad_end], [pad_beg, pad_end]])
else:
x = tf.pad(
x,
[[0, 0], [pad_beg, pad_end], [pad_beg, pad_end], [0, 0]])
padding = 'VALID'
return tf.layers.conv2d(
inputs=x,
kernel_size=kernel_size,
filters=filters,
strides=strides,
padding=padding,
use_bias=False,
data_format=self._data_format)
def _batch_norm(self, x):
if self._data_format == 'channels_first':
data_format = 'NCHW'
else:
data_format = 'NHWC'
return tf.contrib.layers.batch_norm(
x,
decay=self._batch_norm_decay,
center=True,
scale=True,
epsilon=self._batch_norm_epsilon,
is_training=self._is_training,
fused=True,
data_format=data_format)
def _relu(self, x):
return tf.nn.relu(x)
def _fully_connected(self,
x,
out_dim,
kernel_initializer=None,
kernel_regularizer=None):
with tf.name_scope('fully_connected') as name_scope:
x = tf.layers.dense(
x,
out_dim,
kernel_initializer=kernel_initializer,
kernel_regularizer=kernel_regularizer)
tf.logging.info('image after unit %s: %s', name_scope, x.get_shape())
return x
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/preprocessing.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import tensorflow as tf
import numpy as np
from glob import glob
feature_dim = 62
train_data = np.zeros([20000000, feature_dim+1], dtype=np.float32)
test_data = np.zeros([2000000, feature_dim+1], dtype=np.float32)
eval_data = np.zeros([2000000, feature_dim+1], dtype=np.float32)
train_idx, test_idx, eval_idx = 0, 0, 0
filenames = glob('/tmp/data/feature_v1_bin/*/*.label.bin')
for filename in filenames:
print(filename)
bin_data = np.fromfile(filename, dtype=np.float32)
if bin_data.shape[0] % (feature_dim + 1) != 0:
raise ValueError('data size (%d) must be multiple of feature_dim + 1 (%d).' %
(bin_data.shape[0], feature_dim + 1))
num_examples = bin_data.shape[0] // (feature_dim + 1)
for i in range(num_examples):
label = int(bin_data[i*(feature_dim + 1)+feature_dim])
data = bin_data[i*(feature_dim + 1):(i+1) *
(feature_dim + 1)].reshape([1, (feature_dim+1)])
if label == 2:
times = 17
new_data = np.repeat(data, times, axis=0)
elif label == 1:
times = np.random.choice([2, 2, 2, 3, 3])
new_data = np.repeat(data, times, axis=0)
else:
times = 1
new_data = data
if i % 10 == 8:
test_data[test_idx:test_idx+times, :] = new_data
test_idx += times
elif i % 10 == 9:
eval_data[eval_idx:eval_idx+times, :] = new_data
eval_idx += times
else:
train_data[train_idx:train_idx+times, :] = new_data
train_idx += times
train_data = train_data[:train_idx, :]
np.random.shuffle(train_data)
print(train_data.shape, train_idx)
test_data = test_data[:test_idx, :]
np.random.shuffle(test_data)
print(test_data.shape, test_idx)
eval_data = eval_data[:eval_idx, :]
np.random.shuffle(eval_data)
print(eval_data.shape, eval_idx)
# write to file
train_data[:13000000, :].tofile('/tmp/data/prediction/train.bin')
test_data[:1600000, :].tofile('/tmp/data/prediction/test.bin')
eval_data[:1600000, :].tofile('/tmp/data/prediction/eval.bin')
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/mlp_model.py
|
#!/usr/bin/env python3
###############################################################################
# Modification Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
import tensorflow as tf
import modules.tools.prediction.multiple_gpu_estimator.model_base
dim_input = 62
dim_hidden_1 = 30
dim_hidden_2 = 15
dim_output = 4
class MlpModel(model_base.ModelBase):
"""prediction model with fully connected layers."""
def __init__(self,
is_training=True,
batch_norm_decay=0.999,
batch_norm_epsilon=0.001,
data_format='channels_last'):
super(MlpModel, self).__init__(is_training, data_format,
batch_norm_decay, batch_norm_epsilon)
def forward_pass(self, x, input_data_format='channels_last'):
"""Build the core model within the graph."""
x = self._fully_connected_with_bn(
x,
dim_input,
kernel_initializer=tf.contrib.keras.initializers.he_normal(),
kernel_regularizer=tf.contrib.layers.l2_regularizer(0.01))
x = self._fully_connected_with_bn(
x,
dim_hidden_1,
kernel_initializer=tf.contrib.keras.initializers.he_normal(),
kernel_regularizer=tf.contrib.layers.l2_regularizer(0.01))
x = self._fully_connected_with_bn(
x,
dim_hidden_2,
kernel_initializer=tf.contrib.keras.initializers.he_normal(),
kernel_regularizer=tf.contrib.layers.l2_regularizer(0.01))
x = self._fully_connected(x, dim_output)
return x
def _fully_connected_with_bn(self,
x,
out_dim,
kernel_initializer=None,
kernel_regularizer=None):
x = self._fully_connected(
x,
out_dim,
kernel_initializer=kernel_initializer,
kernel_regularizer=kernel_regularizer)
x = self._relu(x)
x = self._batch_norm(x)
return x
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/mlp_utils.py
|
#!/usr/bin/env python3
###############################################################################
# Modification Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
import collections
import six
from tensorflow.contrib.learn.python.learn import run_config
from tensorflow.core.framework import node_def_pb2
from tensorflow.python.framework import device as pydev
from tensorflow.python.platform import tf_logging as logging
from tensorflow.python.training import basic_session_run_hooks
from tensorflow.python.training import device_setter
from tensorflow.python.training import session_run_hook
from tensorflow.python.training import training_util
import tensorflow as tf
class RunConfig(tf.contrib.learn.RunConfig):
def uid(self, whitelist=None):
"""Generates a 'Unique Identifier' based on all internal fields.
Caller should use the uid string to check `RunConfig` instance integrity
in one session use, but should not rely on the implementation details, which
is subject to change.
Args:
whitelist: A list of the string names of the properties uid should not
include. If `None`, defaults to `_DEFAULT_UID_WHITE_LIST`, which
includes most properties user allowes to change.
Returns:
A uid string.
"""
if whitelist is None:
whitelist = run_config._DEFAULT_UID_WHITE_LIST
state = {
k: v
for k, v in self.__dict__.items() if not k.startswith('__')
}
# Pop out the keys in whitelist.
for k in whitelist:
state.pop('_' + k, None)
ordered_state = collections.OrderedDict(
sorted(list(state.items()), key=lambda t: t[0]))
# For class instance without __repr__, some special cares are required.
# Otherwise, the object address will be used.
if '_cluster_spec' in ordered_state:
ordered_state['_cluster_spec'] = collections.OrderedDict(
sorted(
list(ordered_state['_cluster_spec'].as_dict().items()),
key=lambda t: t[0]))
return ', '.join(
'%s=%r' % (k, v) for (k, v) in six.iteritems(ordered_state))
class ExamplesPerSecondHook(session_run_hook.SessionRunHook):
"""Hook to print out examples per second.
Total time is tracked and then divided by the total number of steps
to get the average step time and then batch_size is used to determine
the running average of examples per second. The examples per second for the
most recent interval is also logged.
"""
def __init__(
self,
batch_size,
every_n_steps=100,
every_n_secs=None,
):
"""Initializer for ExamplesPerSecondHook.
Args:
batch_size: Total batch size used to calculate examples/second from
global time.
every_n_steps: Log stats every n steps.
every_n_secs: Log stats every n seconds.
"""
if (every_n_steps is None) == (every_n_secs is None):
raise ValueError('exactly one of every_n_steps'
' and every_n_secs should be provided.')
self._timer = basic_session_run_hooks.SecondOrStepTimer(
every_steps=every_n_steps, every_secs=every_n_secs)
self._step_train_time = 0
self._total_steps = 0
self._batch_size = batch_size
def begin(self):
self._global_step_tensor = training_util.get_global_step()
if self._global_step_tensor is None:
raise RuntimeError(
'Global step should be created to use StepCounterHook.')
def before_run(self, run_context): # pylint: disable=unused-argument
return basic_session_run_hooks.SessionRunArgs(self._global_step_tensor)
def after_run(self, run_context, run_values):
_ = run_context
global_step = run_values.results
if self._timer.should_trigger_for_step(global_step):
elapsed_time, elapsed_steps = self._timer.update_last_triggered_step(
global_step)
if elapsed_time is not None:
steps_per_sec = elapsed_steps / elapsed_time
self._step_train_time += elapsed_time
self._total_steps += elapsed_steps
average_examples_per_sec = self._batch_size * (
self._total_steps / self._step_train_time)
current_examples_per_sec = steps_per_sec * self._batch_size
# Average examples/sec followed by current examples/sec
logging.info('%s: %g (%g), step = %g', 'Average examples/sec',
average_examples_per_sec,
current_examples_per_sec, self._total_steps)
def local_device_setter(num_devices=1,
ps_device_type='cpu',
worker_device='/cpu:0',
ps_ops=None,
ps_strategy=None):
if ps_ops is None:
ps_ops = ['Variable', 'VariableV2', 'VarHandleOp']
if ps_strategy is None:
ps_strategy = device_setter._RoundRobinStrategy(num_devices)
if not six.callable(ps_strategy):
raise TypeError("ps_strategy must be callable")
def _local_device_chooser(op):
current_device = pydev.DeviceSpec.from_string(op.device or "")
node_def = op if isinstance(op, node_def_pb2.NodeDef) else op.node_def
if node_def.op in ps_ops:
ps_device_spec = pydev.DeviceSpec.from_string('/{}:{}'.format(
ps_device_type, ps_strategy(op)))
ps_device_spec.merge_from(current_device)
return ps_device_spec.to_string()
worker_device_spec = pydev.DeviceSpec.from_string(worker_device or "")
worker_device_spec.merge_from(current_device)
return worker_device_spec.to_string()
return _local_device_chooser
| 0
|
apollo_public_repos/apollo/modules/tools/prediction
|
apollo_public_repos/apollo/modules/tools/prediction/multiple_gpu_estimator/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary", "py_library")
package(default_visibility = ["//visibility:public"])
py_binary(
name = "convert_to_tfrecords",
srcs = ["convert_to_tfrecords.py"],
)
py_binary(
name = "counting",
srcs = ["counting.py"],
)
py_library(
name = "mlp_data",
srcs = ["mlp_data.py"],
)
py_binary(
name = "mlp_main",
srcs = ["mlp_main.py"],
deps = [
":mlp_data",
":mlp_model",
":mlp_utils",
],
)
py_library(
name = "mlp_model",
srcs = ["mlp_model.py"],
deps = [
":model_base",
],
)
py_library(
name = "mlp_utils",
srcs = ["mlp_utils.py"],
)
py_library(
name = "model_base",
srcs = ["model_base.py"],
)
py_binary(
name = "preprocessing",
srcs = ["preprocessing.py"],
)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/speed_dsteering_data.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
from modules.tools.plot_planning.record_reader import RecordItemReader
import matplotlib.pyplot as plt
from cyber.python.cyber_py3.record import RecordReader
from modules.common_msgs.chassis_msgs import chassis_pb2
class SpeedDsteeringData:
def __init__(self):
self.last_steering_percentage = None
self.last_speed_mps = None
self.last_timestamp_sec = None
self.speed_data = []
self.d_steering_data = []
def add(self, chassis):
steering_percentage = chassis.steering_percentage
speed_mps = chassis.speed_mps
timestamp_sec = chassis.header.timestamp_sec
if self.last_timestamp_sec is None:
self.last_steering_percentage = steering_percentage
self.last_speed_mps = speed_mps
self.last_timestamp_sec = timestamp_sec
return
if (timestamp_sec - self.last_timestamp_sec) > 0.02:
d_steering = (steering_percentage - self.last_steering_percentage) \
/ (timestamp_sec - self.last_timestamp_sec)
self.speed_data.append(speed_mps)
self.d_steering_data.append(d_steering)
self.last_steering_percentage = steering_percentage
self.last_speed_mps = speed_mps
self.last_timestamp_sec = timestamp_sec
def get_speed_dsteering(self):
return self.speed_data, self.d_steering_data
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots()
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
processor = SpeedDsteeringData()
last_pose_data = None
last_chassis_data = None
topics = ["/apollo/localization/pose", "/apollo/canbus/chassis"]
for data in reader.read(topics):
if "chassis" in data:
last_chassis_data = data["chassis"]
if last_chassis_data is not None:
processor.add(last_chassis_data)
#last_pose_data = None
#last_chassis_data = None
data_x, data_y = processor.get_speed_dsteering()
ax.scatter(data_x, data_y, c=color, marker=marker, alpha=0.2)
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/imu_speed_jerk.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from modules.tools.plot_planning.record_reader import RecordItemReader
from modules.tools.plot_planning.imu_speed_acc import ImuSpeedAcc
class ImuSpeedJerk:
def __init__(self, is_lateral=False):
self.timestamp_list = []
self.jerk_list = []
self.imu_speed_acc = ImuSpeedAcc(is_lateral)
def add(self, location_est):
self.imu_speed_acc.add(location_est)
acc_timestamp_list = self.imu_speed_acc.get_timestamp_list()
if len(acc_timestamp_list) <= 0:
return
index_500ms = len(acc_timestamp_list) - 1
found_index_500ms = False
last_timestamp = acc_timestamp_list[-1]
while index_500ms >= 0:
current_timestamp = acc_timestamp_list[index_500ms]
if (last_timestamp - current_timestamp) >= 0.5:
found_index_500ms = True
break
index_500ms -= 1
if found_index_500ms:
acc_list = self.imu_speed_acc.get_acc_list()
jerk = (acc_list[-1] - acc_list[index_500ms]) / \
(acc_timestamp_list[-1] - acc_timestamp_list[index_500ms])
self.jerk_list.append(jerk)
self.timestamp_list.append(acc_timestamp_list[-1])
def get_jerk_list(self):
return self.jerk_list
def get_timestamp_list(self):
return self.timestamp_list
def get_lastest_jerk(self):
if len(self.jerk_list) > 0:
return self.jerk_list[-1]
else:
return None
def get_lastest_timestamp(self):
if len(self.timestamp_list) > 0:
return self.timestamp_list[-1]
else:
return None
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
import numpy as np
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots(1, 1)
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
x = []
y = []
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
fns.sort()
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
processor = ImuSpeedJerk(True)
last_pose_data = None
last_chassis_data = None
topics = ["/apollo/localization/pose"]
for data in reader.read(topics):
if "pose" in data:
last_pose_data = data["pose"]
processor.add(last_pose_data)
data_x = processor.get_timestamp_list()
data_y = processor.get_jerk_list()
x.extend(data_x)
y.extend(data_y)
if len(x) <= 0:
continue
ax.scatter(x, y, c=color, marker=marker, alpha=0.4)
#ax.plot(x, y, c=color, alpha=0.4)
ax.set_xlabel('Timestamp')
ax.set_ylabel('Jerk')
plt.show()
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apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/plot_speed_steering.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
import matplotlib.pyplot as plt
from cyber.python.cyber_py3.record import RecordReader
from modules.common_msgs.chassis_msgs import chassis_pb2
def process(reader):
last_steering_percentage = None
last_speed_mps = None
last_timestamp_sec = None
speed_data = []
d_steering_data = []
for msg in reader.read_messages():
if msg.topic == "/apollo/canbus/chassis":
chassis = chassis_pb2.Chassis()
chassis.ParseFromString(msg.message)
steering_percentage = chassis.steering_percentage
speed_mps = chassis.speed_mps
timestamp_sec = chassis.header.timestamp_sec
if chassis.driving_mode != chassis_pb2.Chassis.COMPLETE_AUTO_DRIVE:
last_steering_percentage = steering_percentage
last_speed_mps = speed_mps
last_timestamp_sec = timestamp_sec
continue
if last_timestamp_sec is None:
last_steering_percentage = steering_percentage
last_speed_mps = speed_mps
last_timestamp_sec = timestamp_sec
continue
if (timestamp_sec - last_timestamp_sec) > 0.02:
d_steering = (steering_percentage - last_steering_percentage) \
/ (timestamp_sec - last_timestamp_sec)
speed_data.append(speed_mps)
d_steering_data.append(d_steering)
last_steering_percentage = steering_percentage
last_speed_mps = speed_mps
last_timestamp_sec = timestamp_sec
return speed_data, d_steering_data
if __name__ == "__main__":
fns = sys.argv[1:]
fig, ax = plt.subplots()
for fn in fns:
reader = RecordReader(fn)
speed_data, d_steering_data = process(reader)
ax.scatter(speed_data, d_steering_data)
ax.set_xlim(-5, 40)
ax.set_ylim(-300, 300)
plt.show()
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apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/chassis_speed.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from modules.tools.plot_planning.record_reader import RecordItemReader
class ChassisSpeed:
def __init__(self):
self.timestamp_list = []
self.speed_list = []
def add(self, chassis):
timestamp_sec = chassis.header.timestamp_sec
speed_mps = chassis.speed_mps
self.timestamp_list.append(timestamp_sec)
self.speed_list.append(speed_mps)
def get_speed_list(self):
return self.speed_list
def get_timestamp_list(self):
return self.timestamp_list
def get_lastest_speed(self):
if len(self.speed_list) > 0:
return self.speed_list[-1]
else:
return None
def get_lastest_timestamp(self):
if len(self.timestamp_list) > 0:
return self.timestamp_list[-1]
else:
return None
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots()
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
processor = ChassisSpeed()
last_chassis_data = None
topics = ["/apollo/canbus/chassis"]
for data in reader.read(topics):
if "chassis" in data:
last_chassis_data = data["chassis"]
processor.add(last_chassis_data)
last_pose_data = None
last_chassis_data = None
data_x = processor.get_timestamp_list()
data_y = processor.get_speed_list()
ax.scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
plt.show()
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|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/record_reader.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
from cyber.python.cyber_py3.record import RecordReader
from modules.common_msgs.chassis_msgs import chassis_pb2
from modules.common_msgs.localization_msgs import localization_pb2
from modules.common_msgs.planning_msgs import planning_pb2
class RecordItemReader:
def __init__(self, record_file):
self.record_file = record_file
def read(self, topics):
reader = RecordReader(self.record_file)
for msg in reader.read_messages():
if msg.topic not in topics:
continue
if msg.topic == "/apollo/canbus/chassis":
chassis = chassis_pb2.Chassis()
chassis.ParseFromString(msg.message)
data = {"chassis": chassis}
yield data
if msg.topic == "/apollo/localization/pose":
location_est = localization_pb2.LocalizationEstimate()
location_est.ParseFromString(msg.message)
data = {"pose": location_est}
yield data
if msg.topic == "/apollo/planning":
planning = planning_pb2.ADCTrajectory()
planning.ParseFromString(msg.message)
data = {"planning": planning}
yield data
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apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/imu_angular_velocity.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from modules.tools.plot_planning.record_reader import RecordItemReader
class ImuAngularVelocity:
def __init__(self):
self.timestamp_list = []
self.angular_velocity_list = []
self.corrected_angular_velocity_list = []
self.last_corrected_angular_velocity = None
self.last_timestamp = None
def add(self, location_est):
timestamp_sec = location_est.header.timestamp_sec
angular_velocity = location_est.pose.angular_velocity.z
if self.last_corrected_angular_velocity is not None:
corrected = self.correct_angular_velocity(
angular_velocity, timestamp_sec)
else:
corrected = angular_velocity
self.timestamp_list.append(timestamp_sec)
self.angular_velocity_list.append(angular_velocity)
self.corrected_angular_velocity_list.append(corrected)
self.last_corrected_angular_velocity = corrected
self.last_timestamp = timestamp_sec
def correct_angular_velocity(self, angular_velocity, timestamp_sec):
if self.last_corrected_angular_velocity is None:
return angular_velocity
delta = abs(angular_velocity - self.last_corrected_angular_velocity)\
/ abs(self.last_corrected_angular_velocity)
if delta > 0.25:
corrected = angular_velocity / 2.0
return corrected
else:
return angular_velocity
def get_anglular_velocity_list(self):
return self.angular_velocity_list
def get_corrected_anglular_velocity_list(self):
return self.corrected_angular_velocity_list
def get_timestamp_list(self):
return self.timestamp_list
def get_latest_angular_velocity(self):
if len(self.angular_velocity_list) == 0:
return None
else:
return self.angular_velocity_list[-1]
def get_latest_corrected_angular_velocity(self):
if len(self.corrected_angular_velocity_list) == 0:
return None
else:
return self.corrected_angular_velocity_list[-1]
def get_latest_timestamp(self):
if len(self.timestamp_list) == 0:
return None
else:
return self.timestamp_list[-1]
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots()
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
fns.sort()
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
processor = ImuAngularVelocity()
for data in reader.read(["/apollo/localization/pose"]):
processor.add(data["pose"])
data_x = processor.get_timestamp_list()
data_y = processor.get_corrected_anglular_velocity_list()
ax.scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
data_y = processor.get_anglular_velocity_list()
ax.scatter(data_x, data_y, c='k', marker="+", alpha=0.8)
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/planning_speed.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
class PlanningSpeed:
def __init__(self):
self.timestamp_list = []
self.speed_list = []
self.last_speed_mps = None
self.last_imu_speed = None
def add(self, planning_pb):
timestamp_sec = planning_pb.header.timestamp_sec
relative_time = planning_pb.debug.planning_data.init_point.relative_time
self.timestamp_list.append(timestamp_sec + relative_time)
speed = planning_pb.debug.planning_data.init_point.v
self.speed_list.append(speed)
def get_speed_list(self):
return self.speed_list
def get_timestamp_list(self):
return self.timestamp_list
def get_lastest_speed(self):
if len(self.speed_list) > 0:
return self.speed_list[-1]
else:
return None
def get_lastest_timestamp(self):
if len(self.timestamp_list) > 0:
return self.timestamp_list[-1]
else:
return None
if __name__ == "__main__":
import sys
import math
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
from record_reader import RecordItemReader
folders = sys.argv[1:]
fig, ax = plt.subplots()
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
processor = PlanningSpeed()
last_pose_data = None
last_chassis_data = None
topics = ["/apollo/planning"]
for data in reader.read(topics):
if "planning" in data:
planning_pb = data["planning"]
processor.add(planning_pb)
data_x = processor.get_timestamp_list()
data_y = processor.get_speed_list()
ax.scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/imu_speed.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from modules.tools.plot_planning.record_reader import RecordItemReader
class ImuSpeed:
def __init__(self, is_lateral=False):
self.timestamp_list = []
self.speed_list = []
self.last_speed_mps = None
self.last_imu_speed = None
self.is_lateral = is_lateral
def add(self, location_est):
timestamp_sec = location_est.measurement_time
self.timestamp_list.append(timestamp_sec)
if self.is_lateral:
speed = -1 * location_est.pose.linear_velocity.x \
* math.sin(location_est.pose.heading) + \
location_est.pose.linear_velocity.y * \
math.cos(location_est.pose.heading)
else:
speed = location_est.pose.linear_velocity.x \
* math.cos(location_est.pose.heading) + \
location_est.pose.linear_velocity.y * \
math.sin(location_est.pose.heading)
self.speed_list.append(speed)
def get_speed_list(self):
return self.speed_list
def get_timestamp_list(self):
return self.timestamp_list
def get_lastest_speed(self):
if len(self.speed_list) > 0:
return self.speed_list[-1]
else:
return None
def get_lastest_timestamp(self):
if len(self.timestamp_list) > 0:
return self.timestamp_list[-1]
else:
return None
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots(2, 1)
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
lat_speed_processor = ImuSpeed(True)
lon_speed_processor = ImuSpeed(False)
last_pose_data = None
last_chassis_data = None
topics = ["/apollo/localization/pose"]
for data in reader.read(topics):
if "pose" in data:
last_pose_data = data["pose"]
lat_speed_processor.add(last_pose_data)
lon_speed_processor.add(last_pose_data)
data_x = lon_speed_processor.get_timestamp_list()
data_y = lon_speed_processor.get_speed_list()
ax[0].scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
data_x = lat_speed_processor.get_timestamp_list()
data_y = lat_speed_processor.get_speed_list()
ax[1].scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
ax[0].set_xlabel('Timestamp')
ax[0].set_ylabel('Lon Acc')
ax[1].set_xlabel('Timestamp')
ax[1].set_ylabel('Lat Acc')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/plot_planning_acc.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
import threading
import gflags
import matplotlib.animation as animation
import matplotlib.pyplot as plt
from cyber.python.cyber_py3 import cyber
from modules.common_msgs.control_msgs import control_cmd_pb2
from modules.common_msgs.planning_msgs import planning_pb2
LAST_TRAJ_DATA = []
LAST_TRAJ_T_DATA = []
CURRENT_TRAJ_DATA = []
CURRENT_TRAJ_T_DATA = []
INIT_V_DATA = []
INIT_T_DATA = []
begin_t = None
last_t = None
last_v = None
lock = threading.Lock()
FLAGS = gflags.FLAGS
gflags.DEFINE_integer("data_length", 500, "Planning plot data length")
def callback(planning_pb):
global INIT_V_DATA, INIT_T_DATA
global CURRENT_TRAJ_DATA, LAST_TRAJ_DATA
global CURRENT_TRAJ_T_DATA, LAST_TRAJ_T_DATA
global begin_t, last_t, last_v
lock.acquire()
if begin_t is None:
begin_t = planning_pb.header.timestamp_sec
current_t = planning_pb.header.timestamp_sec
current_v = planning_pb.debug.planning_data.init_point.v
if last_t is not None and abs(current_t - last_t) > 1:
begin_t = planning_pb.header.timestamp_sec
LAST_TRAJ_DATA = []
LAST_TRAJ_T_DATA = []
CURRENT_TRAJ_DATA = []
CURRENT_TRAJ_T_DATA = []
INIT_V_DATA = []
INIT_T_DATA = []
last_t = None
last_v = None
if last_t is not None and last_v is not None and current_t > last_t:
INIT_T_DATA.append(current_t - begin_t)
INIT_V_DATA.append((current_v - last_v) / (current_t - last_t))
LAST_TRAJ_DATA = []
for v in CURRENT_TRAJ_DATA:
LAST_TRAJ_DATA.append(v)
LAST_TRAJ_T_DATA = []
for t in CURRENT_TRAJ_T_DATA:
LAST_TRAJ_T_DATA.append(t)
CURRENT_TRAJ_DATA = []
CURRENT_TRAJ_T_DATA = []
traj_point_last_v = None
traj_point_last_t = None
for traj_point in planning_pb.trajectory_point:
if traj_point_last_v is None:
CURRENT_TRAJ_DATA.append(traj_point.a)
else:
# CURRENT_TRAJ_DATA.append(traj_point.a)
cal_a = (traj_point.v - traj_point_last_v) / \
(traj_point.relative_time - traj_point_last_t)
CURRENT_TRAJ_DATA.append(cal_a)
CURRENT_TRAJ_T_DATA.append(current_t - begin_t + traj_point.relative_time)
traj_point_last_t = traj_point.relative_time
traj_point_last_v = traj_point.v
lock.release()
last_t = current_t
last_v = current_v
def listener():
cyber.init()
test_node = cyber.Node("planning_acc_listener")
test_node.create_reader("/apollo/planning",
planning_pb2.ADCTrajectory, callback)
def compensate(data_list):
comp_data = [0] * FLAGS.data_length
comp_data.extend(data_list)
if len(comp_data) > FLAGS.data_length:
comp_data = comp_data[-FLAGS.data_length:]
return comp_data
def update(frame_number):
lock.acquire()
last_traj.set_xdata(LAST_TRAJ_T_DATA)
last_traj.set_ydata(LAST_TRAJ_DATA)
current_traj.set_xdata(CURRENT_TRAJ_T_DATA)
current_traj.set_ydata(CURRENT_TRAJ_DATA)
init_data_line.set_xdata(INIT_T_DATA)
init_data_line.set_ydata(INIT_V_DATA)
lock.release()
#brake_text.set_text('brake = %.1f' % brake_data[-1])
#throttle_text.set_text('throttle = %.1f' % throttle_data[-1])
if len(INIT_V_DATA) > 0:
init_data_text.set_text('init point a = %.1f' % INIT_V_DATA[-1])
if __name__ == '__main__':
argv = FLAGS(sys.argv)
listener()
fig, ax = plt.subplots()
X = range(FLAGS.data_length)
Xs = [i * -1 for i in X]
Xs.sort()
init_data_line, = ax.plot(
INIT_T_DATA, INIT_V_DATA, 'b', lw=2, alpha=0.7, label='init_point_a')
current_traj, = ax.plot(
CURRENT_TRAJ_T_DATA, CURRENT_TRAJ_DATA, 'r', lw=1, alpha=0.5, label='current_traj')
last_traj, = ax.plot(
LAST_TRAJ_T_DATA, LAST_TRAJ_DATA, 'g', lw=1, alpha=0.5, label='last_traj')
#brake_text = ax.text(0.75, 0.85, '', transform=ax.transAxes)
#throttle_text = ax.text(0.75, 0.90, '', transform=ax.transAxes)
init_data_text = ax.text(0.75, 0.95, '', transform=ax.transAxes)
ani = animation.FuncAnimation(fig, update, interval=100)
ax.set_ylim(-6, 3)
ax.set_xlim(-1, 60)
ax.legend(loc="upper left")
plt.show()
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apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/imu_av_curvature.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from modules.tools.plot_planning.record_reader import RecordItemReader
from modules.tools.plot_planning.imu_angular_velocity import ImuAngularVelocity
from modules.tools.plot_planning.imu_speed import ImuSpeed
class ImuAvCurvature:
def __init__(self):
self.timestamp_list = []
self.curvature_list = []
self.last_angular_velocity_z = None
self.imu_angular_velocity = ImuAngularVelocity()
self.imu_speed = ImuSpeed()
def add(self, location_est):
timestamp_sec = location_est.header.timestamp_sec
self.imu_angular_velocity.add(location_est)
self.imu_speed.add(location_est)
angular_velocity_z \
= self.imu_angular_velocity.get_latest_corrected_angular_velocity()
speed_mps = self.imu_speed.get_lastest_speed()
if speed_mps > 0.03:
kappa = angular_velocity_z / speed_mps
else:
kappa = 0
self.timestamp_list.append(timestamp_sec)
self.curvature_list.append(kappa)
self.last_angular_velocity_z = angular_velocity_z
def get_timestamp_list(self):
return self.timestamp_list
def get_curvature_list(self):
return self.curvature_list
def get_last_timestamp(self):
if len(self.timestamp_list) > 0:
return self.timestamp_list[-1]
return None
def get_last_curvature(self):
if len(self.curvature_list) > 0:
return self.curvature_list[-1]
return None
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots()
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
fns.sort()
for fn in fns:
print(fn)
reader = RecordItemReader(folder+"/"+fn)
curvature_processor = ImuAvCurvature()
speed_processor = ImuSpeed()
av_processor = ImuAngularVelocity()
last_pose_data = None
last_chassis_data = None
for data in reader.read(["/apollo/localization/pose"]):
if "pose" in data:
last_pose_data = data["pose"]
curvature_processor.add(last_pose_data)
speed_processor.add(last_pose_data)
av_processor.add(last_pose_data)
data_x = curvature_processor.get_timestamp_list()
data_y = curvature_processor.get_curvature_list()
ax.scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
data_x = speed_processor.get_timestamp_list()
data_y = speed_processor.get_speed_list()
ax.scatter(data_x, data_y, c='r', marker=marker, alpha=0.4)
data_x = av_processor.get_timestamp_list()
data_y = av_processor.get_corrected_anglular_velocity_list()
ax.scatter(data_x, data_y, c='b', marker=marker, alpha=0.4)
plt.show()
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apollo_public_repos/apollo/modules/tools
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apollo_public_repos/apollo/modules/tools/plot_planning/plot_speed_jerk.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
from os import listdir
from os.path import isfile, join
import math
import sys
import matplotlib.pyplot as plt
import numpy as np
from modules.tools.plot_planning.imu_speed import ImuSpeed
from modules.tools.plot_planning.imu_speed_jerk import ImuSpeedJerk
from modules.tools.plot_planning.record_reader import RecordItemReader
def grid(data_list, shift):
data_grid = []
for data in data_list:
data_grid.append(round(data) + shift / 10.0)
return data_grid
def generate_speed_jerk_dict(speed_jerk_dict, speed_list, jerk_list):
for i in range(len(speed_list)):
speed = int(speed_list[i])
jerk = int(jerk_list[i])
if speed in speed_jerk_dict:
if jerk not in speed_jerk_dict[speed]:
speed_jerk_dict[speed].append(jerk)
else:
speed_jerk_dict[speed] = [jerk]
return speed_jerk_dict
if __name__ == "__main__":
folders = sys.argv[1:]
fig, ax = plt.subplots(1, 1)
colors = ["g", "b", "r", "m", "y"]
markers = [".", ".", ".", "."]
speed_jerk_dict = {}
for i in range(len(folders)):
x = []
y = []
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
fns.sort()
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
jerk_processor = ImuSpeedJerk(True)
speed_processor = ImuSpeed(True)
topics = ["/apollo/localization/pose"]
for data in reader.read(topics):
if "pose" in data:
pose_data = data["pose"]
speed_processor.add(pose_data)
jerk_processor.add(pose_data)
data_x = grid(speed_processor.get_speed_list(), i + 1)
data_y = grid(jerk_processor.get_jerk_list(), i + 1)
data_x = data_x[-1 * len(data_y):]
x.extend(data_x)
y.extend(data_y)
speed_jerk_dict = generate_speed_jerk_dict(speed_jerk_dict, x, y)
if len(x) <= 0:
continue
ax.scatter(x, y, c=color, marker=marker, alpha=0.4)
#ax.plot(x, y, c=color, alpha=0.4)
ax.set_xlabel('Speed')
ax.set_ylabel('Jerk')
print(speed_jerk_dict)
plt.show()
| 0
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apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/plot_chassis_acc.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
import threading
import gflags
import matplotlib.animation as animation
import matplotlib.pyplot as plt
from cyber.python.cyber_py3 import cyber
from modules.common_msgs.chassis_msgs import chassis_pb2
from modules.common_msgs.control_msgs import control_cmd_pb2
INIT_ACC_DATA = []
INIT_T_DATA = []
begin_t = None
last_t = None
last_v = None
lock = threading.Lock()
FLAGS = gflags.FLAGS
gflags.DEFINE_integer("data_length", 500, "Planning plot data length")
def callback(chassis_pb):
global INIT_ACC_DATA, INIT_T_DATA
global begin_t, last_t, last_v
if begin_t is None:
begin_t = chassis_pb.header.timestamp_sec
last_t = begin_t
current_t = chassis_pb.header.timestamp_sec
current_v = chassis_pb.speed_mps
print(current_v)
if abs(current_t - last_t) < 0.015:
return
lock.acquire()
if last_t is not None and abs(current_t - last_t) > 1:
begin_t = chassis_pb.header.timestamp_sec
INIT_ACC_DATA = []
INIT_T_DATA = []
last_t = None
last_v = None
if last_t is not None and last_v is not None and current_t > last_t:
INIT_T_DATA.append(current_t - begin_t)
INIT_ACC_DATA.append((current_v - last_v) / (current_t - last_t))
lock.release()
last_t = current_t
last_v = current_v
def listener():
cyber.init()
test_node = cyber.Node("chassis_acc_listener")
test_node.create_reader("/apollo/canbus/chassis",
chassis_pb2.Chassis, callback)
def compensate(data_list):
comp_data = [0] * FLAGS.data_length
comp_data.extend(data_list)
if len(comp_data) > FLAGS.data_length:
comp_data = comp_data[-FLAGS.data_length:]
return comp_data
def update(frame_number):
lock.acquire()
init_data_line.set_xdata(INIT_T_DATA)
init_data_line.set_ydata(INIT_ACC_DATA)
lock.release()
#brake_text.set_text('brake = %.1f' % brake_data[-1])
#throttle_text.set_text('throttle = %.1f' % throttle_data[-1])
if len(INIT_ACC_DATA) > 0:
init_data_text.set_text('chassis acc = %.1f' % INIT_ACC_DATA[-1])
if __name__ == '__main__':
argv = FLAGS(sys.argv)
listener()
fig, ax = plt.subplots()
X = range(FLAGS.data_length)
Xs = [i * -1 for i in X]
Xs.sort()
init_data_line, = ax.plot(
INIT_T_DATA, INIT_ACC_DATA, 'b', lw=2, alpha=0.7, label='chassis acc')
#brake_text = ax.text(0.75, 0.85, '', transform=ax.transAxes)
#throttle_text = ax.text(0.75, 0.90, '', transform=ax.transAxes)
init_data_text = ax.text(0.75, 0.95, '', transform=ax.transAxes)
ani = animation.FuncAnimation(fig, update, interval=100)
ax.set_ylim(-6, 3)
ax.set_xlim(-1, 60)
ax.legend(loc="upper left")
plt.show()
| 0
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apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/time_curvature_data.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
from modules.tools.plot_planning.record_reader import RecordItemReader
from modules.tools.plot_planning.time_angular_velocity_data import TimeAngularVelocityData
from modules.tools.plot_planning.time_speed_data import TimeSpeedData
import math
class TimeCurvatureData:
def __init__(self):
self.timestamp_list = []
self.curvature_list = []
self.speed_list = []
self.corrected_timestamp_list = []
self.corrected_velocity_list = []
self.last_angular_velocity_z = None
self.angular_velocity_data = TimeAngularVelocityData()
self.speed_data = TimeSpeedData()
def add(self, location_est, chassis):
timestamp_sec = location_est.header.timestamp_sec
self.angular_velocity_data.add_location_estimation(location_est)
self.speed_data.add(location_est, chassis)
angular_velocity_z = self.angular_velocity_data.get_latest()
speed_mps = self.speed_data.get_imu_based_lastest_speed()
if speed_mps > 0.5:
kappa = angular_velocity_z / speed_mps
if kappa > 0.05:
self.timestamp_list.append(timestamp_sec)
self.curvature_list.append(kappa)
self.speed_list.append(speed_mps)
self.last_angular_velocity_z = angular_velocity_z
def get_time_curvature(self):
return self.timestamp_list, self.curvature_list
def get_speed_curvature(self):
return self.speed_list, self.curvature_list
def get_fixed_ca_speed_curvature(self):
speed_list = list(range(1, 31))
curvature_list = []
for speed in speed_list:
curvature = 2.0 / (speed * speed)
curvature_list.append(curvature)
return speed_list, curvature_list
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots()
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
for fn in fns:
print(fn)
reader = RecordItemReader(folder+"/"+fn)
processor = TimeCurvatureData()
last_pose_data = None
last_chassis_data = None
for data in reader.read(["/apollo/localization/pose",
"/apollo/canbus/chassis"]):
if "pose" in data:
last_pose_data = data["pose"]
if "chassis" in data:
last_chassis_data = data["chassis"]
if last_chassis_data is not None and last_pose_data is not None:
processor.add(last_pose_data, last_chassis_data)
data_x, data_y = processor.get_speed_curvature()
data_y = [abs(i) for i in data_y]
ax.scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
#data_x, data_y = processor.speed_data.get_time_speed()
#ax.scatter(data_x, data_y, c=color, marker="+", alpha=0.4)
processor = TimeCurvatureData()
x, y = processor.get_fixed_ca_speed_curvature()
ax.plot(x, y)
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/imu_speed_acc.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from modules.tools.plot_planning.imu_speed import ImuSpeed
from modules.tools.plot_planning.record_reader import RecordItemReader
class ImuSpeedAcc:
def __init__(self, is_lateral=False):
self.timestamp_list = []
self.acc_list = []
self.imu_speed = ImuSpeed(is_lateral)
def add(self, location_est):
self.imu_speed.add(location_est)
speed_timestamp_list = self.imu_speed.get_timestamp_list()
index_50ms = len(speed_timestamp_list) - 1
found_index_50ms = False
last_timestamp = speed_timestamp_list[-1]
while index_50ms >= 0:
current_timestamp = speed_timestamp_list[index_50ms]
if (last_timestamp - current_timestamp) >= 0.05:
found_index_50ms = True
break
index_50ms -= 1
if found_index_50ms:
speed_list = self.imu_speed.get_speed_list()
acc = (speed_list[-1] - speed_list[index_50ms]) / \
(speed_timestamp_list[-1] - speed_timestamp_list[index_50ms])
self.acc_list.append(acc)
self.timestamp_list.append(speed_timestamp_list[-1])
def get_acc_list(self):
return self.acc_list
def get_timestamp_list(self):
return self.timestamp_list
def get_lastest_acc(self):
if len(self.acc_list) > 0:
return self.acc_list[-1]
else:
return None
def get_lastest_timestamp(self):
if len(self.timestamp_list) > 0:
return self.timestamp_list[-1]
else:
return None
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
import numpy as np
from os import listdir
from os.path import isfile, join
def plot_freq(x, y, ax, color):
Fs = len(y) / float(x[-1] - x[0])
n = len(y)
k = np.arange(n)
T = n / Fs
frq = k / T
frq = frq[range(n // 2)]
Y = np.fft.fft(y) / n
Y = Y[range(n // 2)]
ax.plot(frq, abs(Y), c=color)
folders = sys.argv[1:]
fig, ax = plt.subplots(2, 2)
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
lat_time = []
lat_acc = []
lon_time = []
lon_acc = []
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
fns.sort()
for fn in fns:
reader = RecordItemReader(folder + "/" + fn)
lat_acc_processor = ImuSpeedAcc(is_lateral=True)
lon_acc_processor = ImuSpeedAcc(is_lateral=False)
last_pose_data = None
last_chassis_data = None
topics = ["/apollo/localization/pose"]
for data in reader.read(topics):
if "pose" in data:
last_pose_data = data["pose"]
lat_acc_processor.add(last_pose_data)
lon_acc_processor.add(last_pose_data)
data_x = lat_acc_processor.get_timestamp_list()
data_y = lat_acc_processor.get_acc_list()
lat_time.extend(data_x)
lat_acc.extend(data_y)
data_x = lon_acc_processor.get_timestamp_list()
data_y = lon_acc_processor.get_acc_list()
lon_time.extend(data_x)
lon_acc.extend(data_y)
if len(lat_time) == 0:
continue
ax[0][0].plot(lon_time, lon_acc, c=color, alpha=0.4)
ax[0][1].plot(lat_time, lat_acc, c=color, alpha=0.4)
ax[1][0].plot(lat_acc, lon_acc, '.', c=color, alpha=0.4)
ax[0][0].set_xlabel('Timestamp')
ax[0][0].set_ylabel('Lon Acc')
ax[0][1].set_xlabel('Timestamp')
ax[0][1].set_ylabel('Lat Acc')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/plot_acc_jerk.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
import sys
import matplotlib.pyplot as plt
import numpy as np
from os import listdir
from os.path import isfile, join
from modules.tools.plot_planning.record_reader import RecordItemReader
from modules.tools.plot_planning.imu_speed_jerk import ImuSpeedJerk
from modules.tools.plot_planning.imu_speed_acc import ImuSpeedAcc
def grid(data_list, shift):
data_grid = []
for data in data_list:
data_grid.append(round(data) + shift/10.0)
return data_grid
if __name__ == "__main__":
folders = sys.argv[1:]
fig, ax = plt.subplots(1, 1)
colors = ["g", "b", "r", "m", "y"]
markers = [".", ".", ".", "."]
for i in range(len(folders)):
x = []
y = []
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
fns.sort()
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
jerk_processor = ImuSpeedJerk()
acc_processor = ImuSpeedAcc()
topics = ["/apollo/localization/pose"]
for data in reader.read(topics):
if "pose" in data:
pose_data = data["pose"]
acc_processor.add(pose_data)
jerk_processor.add(pose_data)
data_x = grid(acc_processor.get_acc_list(), i + 1)
data_y = grid(jerk_processor.get_jerk_list(), i + 1)
data_x = data_x[-1 * len(data_y):]
x.extend(data_x)
y.extend(data_y)
if len(x) <= 0:
continue
ax.scatter(x, y, c=color, marker=marker, alpha=0.4)
#ax.plot(x, y, c=color, alpha=0.4)
ax.set_xlabel('Acc')
ax.set_ylabel('Jerk')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/plot_planning_speed.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
import threading
import gflags
import matplotlib.animation as animation
import matplotlib.pyplot as plt
from cyber.python.cyber_py3 import cyber
from modules.common_msgs.control_msgs import control_cmd_pb2
from modules.common_msgs.planning_msgs import planning_pb2
LAST_TRAJ_DATA = []
LAST_TRAJ_T_DATA = []
CURRENT_TRAJ_DATA = []
CURRENT_TRAJ_T_DATA = []
INIT_V_DATA = []
INIT_T_DATA = []
begin_t = None
last_t = None
lock = threading.Lock()
FLAGS = gflags.FLAGS
gflags.DEFINE_integer("data_length", 500, "Planning plot data length")
def callback(planning_pb):
global INIT_V_DATA, INIT_T_DATA
global CURRENT_TRAJ_DATA, LAST_TRAJ_DATA
global CURRENT_TRAJ_T_DATA, LAST_TRAJ_T_DATA
global begin_t, last_t
lock.acquire()
if begin_t is None:
begin_t = planning_pb.header.timestamp_sec
current_t = planning_pb.header.timestamp_sec
if last_t is not None and abs(current_t - last_t) > 1:
begin_t = planning_pb.header.timestamp_sec
LAST_TRAJ_DATA = []
LAST_TRAJ_T_DATA = []
CURRENT_TRAJ_DATA = []
CURRENT_TRAJ_T_DATA = []
INIT_V_DATA = []
INIT_T_DATA = []
INIT_T_DATA.append(current_t - begin_t)
INIT_V_DATA.append(planning_pb.debug.planning_data.init_point.v)
LAST_TRAJ_DATA = []
for v in CURRENT_TRAJ_DATA:
LAST_TRAJ_DATA.append(v)
LAST_TRAJ_T_DATA = []
for t in CURRENT_TRAJ_T_DATA:
LAST_TRAJ_T_DATA.append(t)
CURRENT_TRAJ_DATA = []
CURRENT_TRAJ_T_DATA = []
for traj_point in planning_pb.trajectory_point:
CURRENT_TRAJ_DATA.append(traj_point.v)
CURRENT_TRAJ_T_DATA.append(current_t - begin_t + traj_point.relative_time)
lock.release()
last_t = current_t
def listener():
cyber.init()
test_node = cyber.Node("planning_listener")
test_node.create_reader("/apollo/planning",
planning_pb2.ADCTrajectory, callback)
def compensate(data_list):
comp_data = [0] * FLAGS.data_length
comp_data.extend(data_list)
if len(comp_data) > FLAGS.data_length:
comp_data = comp_data[-FLAGS.data_length:]
return comp_data
def update(frame_number):
lock.acquire()
last_traj.set_xdata(LAST_TRAJ_T_DATA)
last_traj.set_ydata(LAST_TRAJ_DATA)
current_traj.set_xdata(CURRENT_TRAJ_T_DATA)
current_traj.set_ydata(CURRENT_TRAJ_DATA)
init_data_line.set_xdata(INIT_T_DATA)
init_data_line.set_ydata(INIT_V_DATA)
lock.release()
#brake_text.set_text('brake = %.1f' % brake_data[-1])
#throttle_text.set_text('throttle = %.1f' % throttle_data[-1])
if len(INIT_V_DATA) > 0:
init_data_text.set_text('init point v = %.1f' % INIT_V_DATA[-1])
if __name__ == '__main__':
argv = FLAGS(sys.argv)
listener()
fig, ax = plt.subplots()
X = range(FLAGS.data_length)
Xs = [i * -1 for i in X]
Xs.sort()
init_data_line, = ax.plot(
INIT_T_DATA, INIT_V_DATA, 'b', lw=2, alpha=0.7, label='init_point_v')
current_traj, = ax.plot(
CURRENT_TRAJ_T_DATA, CURRENT_TRAJ_DATA, 'r', lw=1, alpha=0.5, label='current_traj')
last_traj, = ax.plot(
LAST_TRAJ_T_DATA, LAST_TRAJ_DATA, 'g', lw=1, alpha=0.5, label='last_traj')
#brake_text = ax.text(0.75, 0.85, '', transform=ax.transAxes)
#throttle_text = ax.text(0.75, 0.90, '', transform=ax.transAxes)
init_data_text = ax.text(0.75, 0.95, '', transform=ax.transAxes)
ani = animation.FuncAnimation(fig, update, interval=100)
ax.set_ylim(-1, 30)
ax.set_xlim(-1, 60)
ax.legend(loc="upper left")
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary", "py_library")
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
py_binary(
name = "chassis_speed",
srcs = ["chassis_speed.py"],
deps = [
":record_reader",
],
)
py_binary(
name = "imu_acc",
srcs = ["imu_acc.py"],
deps = [
":record_reader",
],
)
py_binary(
name = "imu_angular_velocity",
srcs = ["imu_angular_velocity.py"],
deps = [
":record_reader",
],
)
py_binary(
name = "imu_av_curvature",
srcs = ["imu_av_curvature.py"],
deps = [
":imu_angular_velocity",
":imu_speed",
":record_reader",
],
)
py_binary(
name = "imu_speed",
srcs = ["imu_speed.py"],
deps = [
":record_reader",
],
)
py_binary(
name = "imu_speed_acc",
srcs = ["imu_speed_acc.py"],
deps = [
":imu_speed",
":record_reader",
],
)
py_binary(
name = "imu_speed_jerk",
srcs = ["imu_speed_jerk.py"],
deps = [
":imu_speed_acc",
":record_reader",
],
)
py_binary(
name = "planning_speed",
srcs = ["planning_speed.py"],
)
py_binary(
name = "plot_acc_jerk",
srcs = ["plot_acc_jerk.py"],
deps = [
":imu_speed_acc",
":imu_speed_jerk",
":record_reader",
],
)
py_binary(
name = "plot_chassis_acc",
srcs = ["plot_chassis_acc.py"],
deps = [
"//cyber/python/cyber_py3:cyber",
"//modules/common_msgs/chassis_msgs:chassis_py_pb2",
"//modules/common_msgs/control_msgs:control_cmd_py_pb2",
],
)
py_binary(
name = "plot_planning_acc",
srcs = ["plot_planning_acc.py"],
deps = [
"//cyber/python/cyber_py3:cyber",
"//modules/common_msgs/chassis_msgs:chassis_py_pb2",
"//modules/common_msgs/control_msgs:control_cmd_py_pb2",
],
)
py_binary(
name = "plot_planning_speed",
srcs = ["plot_planning_speed.py"],
deps = [
"//cyber/python/cyber_py3:cyber",
"//modules/common_msgs/chassis_msgs:chassis_py_pb2",
"//modules/common_msgs/control_msgs:control_cmd_py_pb2",
],
)
py_binary(
name = "plot_speed_jerk",
srcs = ["plot_speed_jerk.py"],
deps = [
":imu_speed",
":imu_speed_jerk",
":record_reader",
],
)
py_binary(
name = "plot_speed_steering",
srcs = ["plot_speed_steering.py"],
deps = [
"//cyber/python/cyber_py3:record",
"//modules/common_msgs/chassis_msgs:chassis_py_pb2",
"//modules/common_msgs/planning_msgs:planning_py_pb2",
],
)
py_library(
name = "record_reader",
srcs = ["record_reader.py"],
deps = [
"//cyber/python/cyber_py3:record",
"//modules/common_msgs/chassis_msgs:chassis_py_pb2",
"//modules/common_msgs/localization_msgs:localization_py_pb2",
"//modules/common_msgs/planning_msgs:planning_py_pb2",
],
)
py_binary(
name = "speed_dsteering_data",
srcs = ["speed_dsteering_data.py"],
deps = [
"//cyber/python/cyber_py3:record",
"//modules/common_msgs/chassis_msgs:chassis_py_pb2",
],
)
install(
name = "install",
py_dest = "tools/plot_planning",
targets = [
":speed_dsteering_data",
":plot_speed_steering",
":plot_speed_jerk",
":plot_planning_speed",
":plot_planning_acc",
":plot_chassis_acc",
":plot_acc_jerk",
":planning_speed",
":imu_speed_jerk",
":imu_speed_acc",
":imu_speed",
":imu_av_curvature",
":imu_angular_velocity",
":imu_acc",
":chassis_speed",
]
)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/plot_planning/imu_acc.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from modules.tools.plot_planning.record_reader import RecordItemReader
class ImuAcc:
def __init__(self):
self.timestamp_list = []
self.corrected_acc_list = []
self.acc_list = []
self.last_corrected_acc = None
self.last_timestamp = None
def add(self, location_est):
timestamp = location_est.measurement_time
acc = location_est.pose.linear_acceleration.x * \
math.cos(location_est.pose.heading) + \
location_est.pose.linear_acceleration.y * \
math.sin(location_est.pose.heading)
if self.last_corrected_acc is not None:
corrected_acc = self._correct_acc(acc, self.last_corrected_acc)
else:
corrected_acc = acc
self.acc_list.append(acc)
self.corrected_acc_list.append(corrected_acc)
self.timestamp_list.append(timestamp)
self.last_timestamp = timestamp
self.last_corrected_acc = corrected_acc
def get_acc_list(self):
return self.acc_list
def get_corrected_acc_list(self):
return self.corrected_acc_list
def get_timestamp_list(self):
return self.timestamp_list
def get_lastest_corrected_acc(self):
if len(self.corrected_acc_list) > 0:
return self.corrected_acc_list[-1]
else:
return None
def get_lastest_acc(self):
if len(self.acc_list) > 0:
return self.acc_list[-1]
else:
return None
def get_lastest_timestamp(self):
if len(self.timestamp_list) > 0:
return self.timestamp_list[-1]
else:
return None
def _correct_acc(self, acc, last_acc):
if last_acc is None:
return last_acc
delta = abs(acc - last_acc) / abs(last_acc)
if delta > 0.4:
corrected = acc / 2.0
return corrected
else:
return acc
if __name__ == "__main__":
import sys
import matplotlib.pyplot as plt
from os import listdir
from os.path import isfile, join
folders = sys.argv[1:]
fig, ax = plt.subplots()
colors = ["g", "b", "r", "m", "y"]
markers = ["o", "o", "o", "o"]
for i in range(len(folders)):
folder = folders[i]
color = colors[i % len(colors)]
marker = markers[i % len(markers)]
fns = [f for f in listdir(folder) if isfile(join(folder, f))]
for fn in fns:
reader = RecordItemReader(folder+"/"+fn)
processor = ImuAcc()
last_pose_data = None
last_chassis_data = None
topics = ["/apollo/localization/pose"]
for data in reader.read(topics):
if "pose" in data:
last_pose_data = data["pose"]
processor.add(last_pose_data)
last_pose_data = None
last_chassis_data = None
data_x = processor.get_timestamp_list()
data_y = processor.get_corrected_acc_list()
ax.scatter(data_x, data_y, c=color, marker=marker, alpha=0.4)
data_y = processor.get_acc_list()
ax.scatter(data_x, data_y, c="k", marker="+", alpha=0.4)
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/map_datachecker/server.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
set -e
function print_usage() {
RED='\033[0;31m'
BLUE='\033[0;34m'
BOLD='\033[1m'
NONE='\033[0m'
echo -e "\n${RED}Usage${NONE}:
${BOLD}bash server.sh${NONE} COMMAND"
echo -e "\n${RED}Commands${NONE}:
${BLUE}start${NONE}: start server
${BLUE}stop${NONE}: stop server
"
}
function set_global_var() {
SCRIPT_PATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
APOLLO_ROOT_PATH="${SCRIPT_PATH}/../../.."
MAP_DATACHECKER_SERVER=${APOLLO_ROOT_PATH}/bazel-bin/modules/map/tools/map_datachecker/server/map_datachecker_server
CONF=${APOLLO_ROOT_PATH}/modules/map/tools/map_datachecker/server/conf/map-datachecker.conf
LOG_DIR=${SCRIPT_PATH}/log
}
function start_server() {
if [ ! -e ${MAP_DATACHECKER_SERVER} ];then
echo "/apollo/apollo.sh build should be executed before run this script"
exit -1
fi
if [ ! -e "${LOG_DIR}" ];then
mkdir -p ${LOG_DIR}
fi
server_count=`ps -ef | grep map_datachecker_server | grep -v grep | wc -l`
if [ ${server_count} -ne 0 ];then
echo 'Start server failed, there is already a process called map_datachecker_server'
echo 'You can kill the preceding map_datachecker_server and rerun this command'
exit -1
fi
server_log=server_`date '+%Y%m%d%H%M%S'`.log
${MAP_DATACHECKER_SERVER} --flagfile=${CONF} > ${LOG_DIR}/${server_log} 2>&1 &
if [ $? -ne 0 ];then
echo 'Start server failed'
exit -1
fi
echo 'Server has been started successfully'
}
function stop_server() {
kill_cmd="kill -INT $(ps -ef | grep map_datachecker_server | grep -v grep | awk '{print $2}')"
server_count=`ps -ef | grep map_datachecker_server | grep -v grep | wc -l`
if [ ${server_count} -eq 1 ];then
${kill_cmd}
echo "stop server done"
elif [ ${server_count} -eq 0 ];then
echo "System has no server to stop"
else
read -p "System has more than one server, stop all server?[Y/N]" is_stop
case ${is_stop} in
[Yy]*)
${kill_cmd}
echo "Stop server done"
;;
[Nn]*)
;;
esac
fi
}
function main() {
set_global_var
local cmd=$1
case $cmd in
start)
start_server
;;
stop)
stop_server
;;
usage)
print_usage
;;
*)
print_usage
;;
esac
}
main $@
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/map_datachecker/client.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
set -ue
function print_usage() {
RED='\033[0;31m'
BLUE='\033[0;34m'
BOLD='\033[1m'
NONE='\033[0m'
echo -e "\n${RED}Usage${NONE}:
${BOLD}bash client.sh${NONE} --stage STAGE [--cmd COMMAND, default is start] [--record_path PATH, only record_check requied]"
echo -e "\n${RED}Stages${NONE}:
${BLUE}record_check${NONE}: check data integrity
${BLUE}static_align${NONE}: static alignment
${BLUE}eight_route${NONE}: figure eight
${BLUE}data_collect${NONE}: data collection
${BLUE}loops_check${NONE}: check loops
${BLUE}clean${NONE}: end this collection
"
echo -e "${RED}Commands${NONE}:
${BLUE}start${NONE}: start corresponding stage
${BLUE}stop${NONE}: stop corresponding stage
"
}
function set_global_var() {
SCRIPT_PATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
APOLLO_ROOT_PATH="${SCRIPT_PATH}/../../.."
MAP_DATACHECKER_CLIENT=${APOLLO_ROOT_PATH}/bazel-bin/modules/map/tools/map_datachecker/client/map_datachecker_client
CONF=${APOLLO_ROOT_PATH}/modules/map/tools/map_datachecker/conf/map-datachecker.conf
LOG_DIR=${APOLLO_ROOT_PATH}/modules/tools/map_datachecker/log
}
function examine_2_params() {
if [[ $1 != "--stage" ]];then
return -1
fi
stage=$2
if [[ ${stage} != "record_check" ]] &&
[[ ${stage} != "static_align" ]] &&
[[ ${stage} != "eight_route" ]] &&
[[ ${stage} != "data_collect" ]] &&
[[ ${stage} != "loops_check" ]] &&
[[ ${stage} != "clean" ]];then
return -1
fi
return 0
}
function examine_4_params() {
examine_2_params $@
if [[ $? -ne 0 ]];then
return -1
fi
if [[ $3 == "--cmd" ]];then
cmd=$4
if [[ ${cmd} != "start" ]] &&
[[ ${cmd} != "stop" ]];then
return -1
fi
elif [[ $3 == "--record_path" ]];then
record_path=$4
else
return -1
fi
return 0
}
function examine_6_params() {
examine_4_params $@
if [[ $? -ne 0 ]];then
return -1
fi
if [[ $5 == "--record_path" ]];then
record_path=$4
else
return -1
fi
return 0
}
function examine_params() {
if [[ $# -eq 2 ]];then
examine_2_params $@
elif [[ $# -eq 4 ]];then
examine_4_params $@
elif [[ $# -eq 6 ]];then
examine_6_params $@
else
print_usage
return -1
fi
if [[ $? -ne 0 ]];then
print_usage
return -1
fi
stage=$2
if [[ ${stage} == "record_check" ]];then
if [[ $# -eq 2 ]];then
print_usage
return -1
elif [[ $# -eq 4 ]];then
if [[ $3 != "--record_path" ]];then
print_usage
return -1
fi
else
if [[ $3 != "--record_path" ]] &&
[[ $5 != "--record_path" ]];then
print_usage
return -1
fi
fi
fi
return 0
}
function trap_ctrlc() {
PID=$!
echo kill ${PID}
kill -INT ${PID}
}
function main() {
examine_params $@
if [ $? -ne 0 ];then
exit -1
fi
set_global_var
${MAP_DATACHECKER_CLIENT} $@ 2>> ${LOG_DIR}/client.log
# PID=$!
# trap "trap_ctrlc" INT
}
main $@
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/map_datachecker/BUILD
|
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
install(
name = "install",
data_dest = "tools/map_datachecker",
data = [":scripts"],
visibility = ["//visibility:public"],
)
filegroup(
name = "scripts",
srcs = glob([
"*.sh",
]),
)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/create_map/convert_map_txt2bin.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
Convert a base map from txt to bin format
"""
import argparse
from modules.common_msgs.map_msgs.map_pb2 import Map
from google.protobuf import text_format
def main():
parser = argparse.ArgumentParser(
description='Convert a base map from txt to bin format')
parser.add_argument(
'-i',
'--input_file',
help='Input base map in txt format',
type=str,
default='modules/map/data/gen/base_map.txt')
parser.add_argument(
'-o',
'--output_file',
help='Output base map in bin format',
type=str,
default='modules/map/data/gen/base_map.bin')
args = vars(parser.parse_args())
input_file_name = args['input_file']
output_file_name = args['output_file']
with open(input_file_name, 'r') as f:
mp = Map()
text_format.Merge(f.read(), mp)
# Output map
with open(output_file_name, "wb") as f:
f.write(mp.SerializeToString())
if __name__ == '__main__':
main()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/create_map/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary")
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
filegroup(
name = "py_files",
srcs = glob([
"*.py",
]),
)
py_binary(
name = "convert_map_txt2bin",
srcs = ["convert_map_txt2bin.py"],
deps = [
"//modules/common_msgs/map_msgs:map_py_pb2",
],
)
install(
name = "install",
py_dest = "tools/create_map",
targets = [":convert_map_txt2bin"]
)
| 0
|
apollo_public_repos/apollo/modules/tools/planning
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory/run.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
if [ $# -lt 2 ]
then
echo Usage: ./run.sh planning.pb.txt localization.pb.txt
exit
fi
TOP_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/../../.." && pwd -P)"
source "${TOP_DIR}/scripts/apollo_base.sh"
cd "$(dirname "${BASH_SOURCE[0]}")"
eval "${TOP_DIR}/bazel-bin/modules/tools/planning/plot_trajectory/main $1 $2"
| 0
|
apollo_public_repos/apollo/modules/tools/planning
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory/mkz_polygon.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
def get(position, heading):
front_edge_to_center = 3.89
back_edge_to_center = 1.043
left_edge_to_center = 1.055
right_edge_to_center = 1.055
cos_h = math.cos(heading)
sin_h = math.sin(heading)
# (p3) -------- (p0)
# | o |
# (p2) -------- (p1)
p0_x, p0_y = front_edge_to_center, left_edge_to_center
p1_x, p1_y = front_edge_to_center, -right_edge_to_center
p2_x, p2_y = -back_edge_to_center, -left_edge_to_center
p3_x, p3_y = -back_edge_to_center, right_edge_to_center
p0_x, p0_y = p0_x * cos_h - p0_y * sin_h, p0_x * sin_h + p0_y * cos_h
p1_x, p1_y = p1_x * cos_h - p1_y * sin_h, p1_x * sin_h + p1_y * cos_h
p2_x, p2_y = p2_x * cos_h - p2_y * sin_h, p2_x * sin_h + p2_y * cos_h
p3_x, p3_y = p3_x * cos_h - p3_y * sin_h, p3_x * sin_h + p3_y * cos_h
[x, y, z] = position
polygon = []
polygon.append([p0_x + x, p0_y + y, 0])
polygon.append([p1_x + x, p1_y + y, 0])
polygon.append([p2_x + x, p2_y + y, 0])
polygon.append([p3_x + x, p3_y + y, 0])
return polygon
def plot(position, quaternion, ax):
polygon = get(position, quaternion)
px = []
py = []
for point in polygon:
px.append(point[0])
py.append(point[1])
point = polygon[0]
px.append(point[0])
py.append(point[1])
ax.plot(px, py, "g-")
ax.plot([position[0]], [position[1]], 'go')
| 0
|
apollo_public_repos/apollo/modules/tools/planning
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary", "py_library")
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
filegroup(
name = "runtime_files",
srcs = glob(["example_data/*"]) + ["run.sh"],
)
py_binary(
name = "main",
srcs = ["main.py"],
data = [
"//modules/tools/planning/plot_trajectory/example_data",
],
deps = [
":mkz_polygon",
"//modules/common_msgs/localization_msgs:localization_py_pb2",
"//modules/common_msgs/planning_msgs:planning_py_pb2",
"//modules/tools/common:proto_utils",
],
)
py_library(
name = "mkz_polygon",
srcs = ["mkz_polygon.py"],
)
install(
name = "install",
data_dest = "tools/planning/plot_trajectory",
py_dest = "tools/planning/plot_trajectory",
targets = [
":main",
]
)
| 0
|
apollo_public_repos/apollo/modules/tools/planning
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory/main.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
import matplotlib.pyplot as plt
import modules.tools.common.proto_utils as proto_utils
from modules.tools.planning.plot_trajectory import mkz_polygon
from modules.common_msgs.planning_msgs.planning_pb2 import ADCTrajectory
from modules.common_msgs.localization_msgs.localization_pb2 import LocalizationEstimate
def plot_trajectory(planning_pb, ax):
points_x = []
points_y = []
points_t = []
base_time_sec = planning_pb.header.timestamp_sec
for trajectory_point in planning_pb.adc_trajectory_point:
points_x.append(trajectory_point.x)
points_y.append(trajectory_point.y)
points_t.append(base_time_sec + trajectory_point.relative_time)
ax.plot(points_x, points_y, "r.")
def find_closest_t(points_t, current_t):
if len(points_t) == 0:
return -1
if len(points_t) == 1:
return points_t[0]
if len(points_t) == 2:
if abs(points_t[0] - current_t) < abs(points_t[1] - current_t):
return points_t[0]
else:
return points_t[1]
if points_t[len(points_t) // 2] > current_t:
return find_closest_t(points_t[0:len(points_t) // 2], current_t)
elif points_t[len(points_t) // 2] < current_t:
return find_closest_t(points_t[len(points_t) // 2 + 1:], current_t)
else:
return current_t
def find_closest_traj_point(planning_pb, current_t):
points_x = []
points_y = []
points_t = []
base_time_sec = planning_pb.header.timestamp_sec
for trajectory_point in planning_pb.adc_trajectory_point:
points_x.append(trajectory_point.x)
points_y.append(trajectory_point.y)
points_t.append(base_time_sec + trajectory_point.relative_time)
matched_t = find_closest_t(points_t, current_t)
idx = points_t.index(matched_t)
return planning_pb.adc_trajectory_point[idx]
def plot_traj_point(planning_pb, traj_point, ax):
matched_t = planning_pb.header.timestamp_sec \
+ traj_point.relative_time
ax.plot([traj_point.x], [traj_point.y], "bs")
content = "t = " + str(matched_t) + "\n"
content += "speed = " + str(traj_point.speed) + "\n"
content += "acc = " + str(traj_point.acceleration_s)
lxy = [-80, -80]
ax.annotate(
content,
xy=(traj_point.x, traj_point.y),
xytext=lxy,
textcoords='offset points',
ha='right',
va='top',
bbox=dict(boxstyle='round,pad=0.5', fc='yellow', alpha=0.3),
arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0'),
alpha=0.8)
def plot_vehicle(localization_pb, ax):
loc_x = [localization_pb.pose.position.x]
loc_y = [localization_pb.pose.position.y]
current_t = localization_pb.header.timestamp_sec
ax.plot(loc_x, loc_y, "bo")
position = []
position.append(localization_pb.pose.position.x)
position.append(localization_pb.pose.position.y)
position.append(localization_pb.pose.position.z)
mkz_polygon.plot(position, localization_pb.pose.heading, ax)
content = "t = " + str(current_t) + "\n"
content += "speed @y = " + \
str(localization_pb.pose.linear_velocity.y) + "\n"
content += "acc @y = " + \
str(localization_pb.pose.linear_acceleration_vrf.y)
lxy = [-80, 80]
ax.annotate(
content,
xy=(loc_x[0], loc_y[0]),
xytext=lxy,
textcoords='offset points',
ha='left',
va='top',
bbox=dict(boxstyle='round,pad=0.5', fc='yellow', alpha=0.3),
arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0'),
alpha=0.8)
if __name__ == "__main__":
if len(sys.argv) < 2:
print("usage: %s <planning.pb.txt> <localization.pb.txt>" % sys.argv[0])
sys.exit(0)
planning_pb_file = sys.argv[1]
localization_pb_file = sys.argv[2]
planning_pb = proto_utils.get_pb_from_text_file(
planning_pb_file, ADCTrajectory())
localization_pb = proto_utils.get_pb_from_text_file(
localization_pb_file, LocalizationEstimate())
plot_trajectory(planning_pb, plt)
plot_vehicle(localization_pb, plt)
current_t = localization_pb.header.timestamp_sec
trajectory_point = find_closest_traj_point(planning_pb, current_t)
plot_traj_point(planning_pb, trajectory_point, plt)
plt.axis('equal')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory/example_data/1_planning.pb.txt
|
header {
timestamp_sec: 1494373003.683531
module_name: "planning"
sequence_num: 1
}
total_path_length: 32.38002780204
total_path_time: 9.9800000190734863
adc_trajectory_point {
x: -124.367072419
y: 364.831849142
z: -31.332377322
speed: 1.62222218513
acceleration_s: 0.786162598236
curvature: -0.00252617800322
curvature_change_rate: 0
relative_time: -0.089999914169311523
theta: -1.81237826921
accumulated_s: 0
}
adc_trajectory_point {
x: -124.371192947
y: 364.815408289
z: -31.3321617292
speed: 1.63055551052
acceleration_s: 0.823007905434
curvature: -0.00248790128945
curvature_change_rate: 0.00234746462335
relative_time: -0.079999923706054688
theta: -1.81246574077
accumulated_s: 0.016305555109999981
}
adc_trajectory_point {
x: -124.375298464
y: 364.798862219
z: -31.3319112528
speed: 1.63055551052
acceleration_s: 0.939039433387
curvature: -0.00248790128945
curvature_change_rate: 0
relative_time: -0.069999933242797852
theta: -1.81246756399
accumulated_s: 0.032611110209999961
}
adc_trajectory_point {
x: -124.379445239
y: 364.782260752
z: -31.331748303
speed: 1.65555560589
acceleration_s: 0.799533704679
curvature: -0.00244962463489
curvature_change_rate: 0.00231201262143
relative_time: -0.059999942779541016
theta: -1.81249667017
accumulated_s: 0.0491666662700001
}
adc_trajectory_point {
x: -124.379445239
y: 364.782260752
z: -31.331748303
speed: 1.65555560589
acceleration_s: 0.799533704679
curvature: -0.00244962463489
curvature_change_rate: 0
relative_time: -0.059999942779541016
theta: -1.81249667017
accumulated_s: 0.065722222330000024
}
adc_trajectory_point {
x: -124.387812319
y: 364.748792952
z: -31.3314336967
speed: 1.67222225666
acceleration_s: 0.709512194401
curvature: -0.00241134803862
curvature_change_rate: 0.00228896584236
relative_time: -0.039999961853027344
theta: -1.81252111016
accumulated_s: 0.082444444899999914
}
adc_trajectory_point {
x: -124.39208822
y: 364.73193295
z: -31.3311777441
speed: 1.67222225666
acceleration_s: 0.885164961093
curvature: -0.00241134803862
curvature_change_rate: 0
relative_time: -0.029999971389770508
theta: -1.81259538169
accumulated_s: 0.099166667460000024
}
adc_trajectory_point {
x: -124.396360761
y: 364.715008909
z: -31.3310258063
speed: 1.6916667223
acceleration_s: 0.840964839003
curvature: -0.00241134803862
curvature_change_rate: 0
relative_time: -0.019999980926513672
theta: -1.81260595807
accumulated_s: 0.1160833346900001
}
adc_trajectory_point {
x: -124.400686806
y: 364.698015497
z: -31.3307877881
speed: 1.6916667223
acceleration_s: 0.79314550852
curvature: -0.00241134803862
curvature_change_rate: 0
relative_time: -0.0099999904632568359
theta: -1.81264478745
accumulated_s: 0.13300000190999994
}
adc_trajectory_point {
x: -124.404998184
y: 364.68093016
z: -31.330677554
speed: 1.70833337307
acceleration_s: 0.79314550852
curvature: -0.00237307149975
curvature_change_rate: 0.00224057783324
relative_time: 0
theta: -1.81266143871
accumulated_s: 0.15008333563999998
}
adc_trajectory_point {
x: -124.404998184
y: 364.68093016
z: -31.330677554
speed: 1.70833337307
acceleration_s: 0.848439761077
curvature: -0.00237307149975
curvature_change_rate: 0
relative_time: 0
theta: -1.81266143871
accumulated_s: 0.16716666937000002
}
adc_trajectory_point {
x: -124.413740829
y: 364.646558161
z: -31.330341435
speed: 1.7277777195
acceleration_s: 0.839788102862
curvature: -0.00233479501735
curvature_change_rate: 0.00221535918454
relative_time: 0.019999980926513672
theta: -1.81271721372
accumulated_s: 0.18444444656999992
}
adc_trajectory_point {
x: -124.418160805
y: 364.629263991
z: -31.3301604046
speed: 1.7277777195
acceleration_s: 0.796361476988
curvature: -0.00233479501735
curvature_change_rate: 0
relative_time: 0.029999971389770508
theta: -1.8127539742
accumulated_s: 0.20172222376000004
}
adc_trajectory_point {
x: -124.422587432
y: 364.611881599
z: -31.329923776
speed: 1.74166667461
acceleration_s: 0.796361476988
curvature: -0.00229651859052
curvature_change_rate: 0.00219768956878
relative_time: 0.039999961853027344
theta: -1.81278276405
accumulated_s: 0.21913889051000002
}
adc_trajectory_point {
x: -124.42702661
y: 364.59441933
z: -31.329741355
speed: 1.74166667461
acceleration_s: 0.79238461037
curvature: -0.00229651859052
curvature_change_rate: 0
relative_time: 0.04999995231628418
theta: -1.81281670152
accumulated_s: 0.23655555725
}
adc_trajectory_point {
x: -124.431486786
y: 364.576916664
z: -31.3295119135
speed: 1.75833332539
acceleration_s: 0.623637235555
curvature: -0.00229651859052
curvature_change_rate: 0
relative_time: 0.059999942779541016
theta: -1.8128477221
accumulated_s: 0.25413889050999994
}
adc_trajectory_point {
x: -124.435979126
y: 364.559317752
z: -31.3293451639
speed: 1.75833332539
acceleration_s: 0.78715534576
curvature: -0.00229651859052
curvature_change_rate: 0
relative_time: 0.069999933242797852
theta: -1.81292572329
accumulated_s: 0.2717222237600001
}
adc_trajectory_point {
x: -124.440512829
y: 364.541682956
z: -31.3291209918
speed: 1.7722222805
acceleration_s: 0.651805683286
curvature: -0.00225824221834
curvature_change_rate: 0.00215979522414
relative_time: 0.080000162124633789
theta: -1.81300561803
accumulated_s: 0.2894444465699999
}
adc_trajectory_point {
x: -124.440512829
y: 364.541682956
z: -31.3291209918
speed: 1.7722222805
acceleration_s: 0.651805683286
curvature: -0.00225824221834
curvature_change_rate: 0
relative_time: 0.080000162124633789
theta: -1.81300561803
accumulated_s: 0.30716666936999992
}
adc_trajectory_point {
x: -124.449549206
y: 364.506162589
z: -31.3285673754
speed: 1.78888893127
acceleration_s: 0.710935224764
curvature: -0.00221996589991
curvature_change_rate: 0.00213966992371
relative_time: 0.10000014305114746
theta: -1.81308814408
accumulated_s: 0.32505555867999991
}
adc_trajectory_point {
x: -124.454089513
y: 364.488330402
z: -31.3283397462
speed: 1.78888893127
acceleration_s: 0.570744609263
curvature: -0.00221996589991
curvature_change_rate: 0
relative_time: 0.1100001335144043
theta: -1.81312803791
accumulated_s: 0.3429444479999999
}
adc_trajectory_point {
x: -124.458653948
y: 364.470391315
z: -31.3280404089
speed: 1.80277776718
acceleration_s: 0.765021682693
curvature: -0.00218168963431
curvature_change_rate: 0.00212318269586
relative_time: 0.12000012397766113
theta: -1.81320046776
accumulated_s: 0.36097222567000009
}
adc_trajectory_point {
x: -124.463241748
y: 364.45241929
z: -31.3277416844
speed: 1.80277776718
acceleration_s: 0.654807529919
curvature: -0.00218168963431
curvature_change_rate: 0
relative_time: 0.13000011444091797
theta: -1.81324631449
accumulated_s: 0.37900000334000006
}
adc_trajectory_point {
x: -124.46783809
y: 364.434363713
z: -31.3274464924
speed: 1.81944441795
acceleration_s: 0.654807529919
curvature: -0.00214341342064
curvature_change_rate: 0.00210373085859
relative_time: 0.1400001049041748
theta: -1.81332741838
accumulated_s: 0.39719444752
}
adc_trajectory_point {
x: -124.47245785
y: 364.416250084
z: -31.3270961335
speed: 1.81944441795
acceleration_s: 0.674982832465
curvature: -0.00214341342064
curvature_change_rate: 0
relative_time: 0.15000009536743164
theta: -1.81337278819
accumulated_s: 0.41538889169999993
}
adc_trajectory_point {
x: -124.477095653
y: 364.398088042
z: -31.326754651
speed: 1.83611106873
acceleration_s: 0.552212210239
curvature: -0.00210513725798
curvature_change_rate: 0.00208463220531
relative_time: 0.16000008583068848
theta: -1.813443323
accumulated_s: 0.43375000239000006
}
adc_trajectory_point {
x: -124.48176616
y: 364.379838609
z: -31.326410614
speed: 1.83611106873
acceleration_s: 0.740273402835
curvature: -0.00210513725798
curvature_change_rate: 0
relative_time: 0.17000007629394531
theta: -1.81353389521
accumulated_s: 0.45211111306999996
}
adc_trajectory_point {
x: -124.486428356
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z: -31.3261427637
speed: 1.85000002384
acceleration_s: 0.580707000797
curvature: -0.00206686114541
curvature_change_rate: 0.00206897903083
relative_time: 0.18000006675720215
theta: -1.81356533084
accumulated_s: 0.47061111330999994
}
adc_trajectory_point {
x: -124.491086517
y: 364.343166634
z: -31.3257930893
speed: 1.85000002384
acceleration_s: 0.725814506272
curvature: -0.00206686114541
curvature_change_rate: 0
relative_time: 0.19000005722045898
theta: -1.81360825438
accumulated_s: 0.48911111354999992
}
adc_trajectory_point {
x: -124.491086517
y: 364.343166634
z: -31.3257930893
speed: 1.86388885975
acceleration_s: 0.725814506272
curvature: -0.00202858508204
curvature_change_rate: 0.00205355931895
relative_time: 0.19000005722045898
theta: -1.81360825438
accumulated_s: 0.5077500021500001
}
adc_trajectory_point {
x: -124.500568552
y: 364.306281933
z: -31.3251117049
speed: 1.86388885975
acceleration_s: 0.578514170379
curvature: -0.00202858508204
curvature_change_rate: 0
relative_time: 0.21000003814697266
theta: -1.81377712139
accumulated_s: 0.52638889075000006
}
adc_trajectory_point {
x: -124.505284561
y: 364.287718639
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speed: 1.87777781487
acceleration_s: 0.733719666282
curvature: -0.00199030906694
curvature_change_rate: 0.00203836762757
relative_time: 0.22000002861022949
theta: -1.81380727115
accumulated_s: 0.54516666889000009
}
adc_trajectory_point {
x: -124.510040247
y: 364.269117353
z: -31.3245309526
speed: 1.87777781487
acceleration_s: 0.545171679849
curvature: -0.00199030906694
curvature_change_rate: 0
relative_time: 0.23000001907348633
theta: -1.81383336004
accumulated_s: 0.56394444703999991
}
adc_trajectory_point {
x: -124.514817529
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z: -31.3242240939
speed: 1.89166665077
acceleration_s: 0.70451380624
curvature: -0.00195203309921
curvature_change_rate: 0.00202339919208
relative_time: 0.24000000953674316
theta: -1.8138975348
accumulated_s: 0.58286111354999992
}
adc_trajectory_point {
x: -124.519599994
y: 364.231695691
z: -31.3239948656
speed: 1.89166665077
acceleration_s: 0.70451380624
curvature: -0.00195203309921
curvature_change_rate: 0
relative_time: 0.25
theta: -1.81392737
accumulated_s: 0.60177778005999993
}
adc_trajectory_point {
x: -124.524397496
y: 364.212904296
z: -31.3237304427
speed: 1.90833330154
acceleration_s: 0.579897214634
curvature: -0.00191375717794
curvature_change_rate: 0.00200572516558
relative_time: 0.25999999046325684
theta: -1.81397067294
accumulated_s: 0.62086111307000014
}
adc_trajectory_point {
x: -124.529204006
y: 364.194037175
z: -31.3235090738
speed: 1.90833330154
acceleration_s: 0.664043300769
curvature: -0.00191375717794
curvature_change_rate: 0
relative_time: 0.26999998092651367
theta: -1.81400750394
accumulated_s: 0.6399444460899999
}
adc_trajectory_point {
x: -124.534002209
y: 364.175124421
z: -31.3233041149
speed: 1.92222225666
acceleration_s: 0.543693233875
curvature: -0.00191375717794
curvature_change_rate: 0
relative_time: 0.27999997138977051
theta: -1.81400097688
accumulated_s: 0.65916666866000018
}
adc_trajectory_point {
x: -124.538850304
y: 364.156134098
z: -31.3231071895
speed: 1.92222225666
acceleration_s: 0.646040675764
curvature: -0.00191375717794
curvature_change_rate: 0
relative_time: 0.28999996185302734
theta: -1.81407158499
accumulated_s: 0.67838889122
}
adc_trajectory_point {
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curvature_change_rate: 0.00104070413751
relative_time: 9.8600001335144043
theta: -1.83417351223
accumulated_s: 32.23316668754
}
adc_trajectory_point {
x: -132.713602221
y: 333.569474338
z: -31.2788601648
speed: 3.67777776718
acceleration_s: -0.0420496219288
curvature: 0.000306198182417
curvature_change_rate: 0
relative_time: 9.8700001239776611
theta: -1.83421945913
accumulated_s: 32.26994446514
}
adc_trajectory_point {
x: -132.723598214
y: 333.533659103
z: -31.2789625516
speed: 3.669444561
acceleration_s: -0.0282229879329
curvature: 0.000306198182417
curvature_change_rate: 0
relative_time: 9.880000114440918
theta: -1.83426703222
accumulated_s: 32.30663891074
}
adc_trajectory_point {
x: -132.733623096
y: 333.497845819
z: -31.2790034963
speed: 3.669444561
acceleration_s: -0.0417450219111
curvature: 0.000306198182417
curvature_change_rate: 0
relative_time: 9.8900001049041748
theta: -1.83432680577
accumulated_s: 32.34333335634
}
adc_trajectory_point {
x: -132.733623096
y: 333.497845819
z: -31.2790034963
speed: 3.669444561
acceleration_s: -0.0417450219111
curvature: 0.000306198182417
curvature_change_rate: 0
relative_time: 9.8900001049041748
theta: -1.83432680577
accumulated_s: 32.38002780204
}
estop {
is_estop: false
}
gear: GEAR_DRIVE
| 0
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory/example_data/BUILD
|
package(default_visibility = ["//visibility:public"])
filegroup(
name = "example_data",
srcs = glob(["*.txt"]),
)
| 0
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory
|
apollo_public_repos/apollo/modules/tools/planning/plot_trajectory/example_data/1_localization.pb.txt
|
header {
timestamp_sec: 1178408221.7
module_name: "localization"
sequence_num: 717699
}
pose {
position {
x: -123.13666043742973
y: 364.35546687249285
z: -31.420322706922889
}
orientation {
qx: 0.0055477773475503213
qy: -0.0038590037118573272
qz: -0.990379842317655
qw: -0.13821034037911459
}
heading: -1.732
linear_velocity {
x: 0.00087471447426956314
y: -0.0012088329450176513
z: -0.0012369063243036489
}
linear_acceleration {
x: -0.016531577551598127
y: -0.018844718168206657
z: -0.046939246111843365
}
angular_velocity {
x: 0.001327747667490114
y: -1.6716219241558373e-05
z: 0.0004012993134012201
}
}
| 0
|
apollo_public_repos/apollo/modules/tools/planning/data_pipelines
|
apollo_public_repos/apollo/modules/tools/planning/data_pipelines/scripts/evaluate_trajectory.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2020 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
TARGET_DIR=$2
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
sudo mkdir -p ${TARGET_DIR}
/apollo/bazel-bin/modules/planning/pipeline/evaluate_trajectory \
--flagfile=/apollo/modules/planning/conf/planning.conf \
--planning_offline_learning=true \
--planning_source_dirs=${SRC_DIR} \
--planning_data_dir=${TARGET_DIR} \
| 0
|
apollo_public_repos/apollo/modules/tools/planning/data_pipelines
|
apollo_public_repos/apollo/modules/tools/planning/data_pipelines/scripts/record_to_learning_data.sh
|
#!/usr/bin/env bash
###############################################################################
# Copyright 2020 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
SRC_DIR=$1
TARGET_DIR=$2
set -e
source /apollo/scripts/apollo_base.sh
source /apollo/cyber/setup.bash
sudo mkdir -p ${TARGET_DIR}
if [ -z "$3" ]; then
MAP_DIR="sunnyvale_with_two_offices"
else
MAP_DIR=$3
fi
/apollo/bazel-bin/modules/planning/pipeline/record_to_learning_data \
--flagfile=/apollo/modules/planning/conf/planning.conf \
--map_dir=/apollo/modules/map/data/${MAP_DIR} \
--planning_offline_learning=true \
--planning_offline_bags=${SRC_DIR} \
--planning_data_dir=${TARGET_DIR}
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/navigation/BUILD
|
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
filegroup(
name = "runtime_files",
srcs = [
"navigation_server_key",
],
)
install(
name = "install",
deps = [
"//modules/tools/navigation/config:install",
"//modules/tools/navigation/driving_behavior:install"
]
)
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/config/default.ini
|
[PerceptionConf]
# three perception solutions: MOBILEYE, CAMERA, and VELODYNE64
perception = CAMERA
[LocalizationConf]
utm_zone = 10
[PlanningConf]
# three planners are available: EM, LATTICE, NAVI
planner_type = EM
# highest speed for planning algorithms, unit is meter per second
speed_limit = 5
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/config/navi_config.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
config navigation mode
"""
import sys
import configparser
from modules.dreamview.proto import hmi_config_pb2
from modules.common_msgs.planning_msgs import planning_config_pb2
from modules.tools.common import proto_utils
DEFAULT_NAVI_CONFIG_FILE = "/apollo/modules/tools/navigation/config/default.ini"
HMI_CONF_FILE = "/apollo/modules/dreamview/conf/hmi.conf"
PLANNING_CONF_FILE = "/apollo/modules/planning/conf/planning_config_navi.pb.txt"
GLOBAL_FLAG_FILE = "/apollo/modules/common/data/global_flagfile.txt"
LOCALIZATION_FLAG_FILE = "/apollo/modules/localization/conf/localization.conf"
PLANNING_FLAG_FILE1 = "/apollo/modules/planning/conf/planning.conf"
PLANNING_FLAG_FILE2 = "/apollo/modules/planning/conf/planning_navi.conf"
def set_hmi_conf(config):
"""change hmi conf file based on navi config file"""
hmi_conf = hmi_config_pb2.HMIConfig()
proto_utils.get_pb_from_file(HMI_CONF_FILE, hmi_conf)
perception = config.get('PerceptionConf', 'perception')
navi_mode = hmi_conf.modes["Navigation"]
if 'navigation_camera' in navi_mode.live_modules:
navi_mode.live_modules.remove('navigation_camera')
if 'navigation_perception' in navi_mode.live_modules:
navi_mode.live_modules.remove('navigation_perception')
if 'mobileye' in navi_mode.live_modules:
navi_mode.live_modules.remove('mobileye')
if 'third_party_perception' in navi_mode.live_modules:
navi_mode.live_modules.remove('third_party_perception')
if 'velodyne' in navi_mode.live_modules:
navi_mode.live_modules.remove('velodyne')
if 'perception' in navi_mode.live_modules:
navi_mode.live_modules.remove('perception')
if perception == "CAMERA":
if 'navigation_camera' not in navi_mode.live_modules:
navi_mode.live_modules.insert(0, 'navigation_camera')
if 'navigation_perception' not in navi_mode.live_modules:
navi_mode.live_modules.insert(0, 'navigation_perception')
if perception == "MOBILEYE":
if 'mobileye' not in navi_mode.live_modules:
navi_mode.live_modules.insert(0, 'mobileye')
if 'third_party_perception' not in navi_mode.live_modules:
navi_mode.live_modules.insert(0, 'third_party_perception')
if perception == "VELODYNE64":
if 'velodyne' not in navi_mode.live_modules:
navi_mode.live_modules.insert(0, 'velodyne')
if 'perception' not in navi_mode.live_modules:
navi_mode.live_modules.insert(0, 'perception')
hmi_conf.modes["Navigation"].CopyFrom(navi_mode)
proto_utils.write_pb_to_text_file(hmi_conf, HMI_CONF_FILE)
def set_planning_conf(config):
"""change planning config based on navi config"""
planning_conf = planning_config_pb2.PlanningConfig()
proto_utils.get_pb_from_file(PLANNING_CONF_FILE, planning_conf)
planner_type = config.get('PlanningConf', 'planner_type')
if planner_type == "EM":
planning_conf.planner_type = planning_config_pb2.PlanningConfig.EM
if planner_type == "LATTICE":
planning_conf.planner_type = planning_config_pb2.PlanningConfig.LATTICE
if planner_type == "NAVI":
planning_conf.planner_type = planning_config_pb2.PlanningConfig.NAVI
proto_utils.write_pb_to_text_file(planning_conf, PLANNING_CONF_FILE)
def set_global_flag(config):
"""update global flag file"""
utm_zone = config.get('LocalizationConf', 'utm_zone')
with open(GLOBAL_FLAG_FILE, 'a') as f:
f.write('\n')
f.write('--use_navigation_mode=true\n\n')
f.write('--local_utm_zone_id=' + utm_zone + '\n\n')
def set_localization_flag(config):
"""update localization flag file"""
utm_zone = config.get('LocalizationConf', 'utm_zone')
with open(LOCALIZATION_FLAG_FILE, 'a') as f:
f.write('\n')
f.write('--local_utm_zone_id=' + utm_zone + '\n\n')
def set_planning_flag(config):
"""update planning flag files"""
speed_limit = config.get('PlanningConf', 'speed_limit')
with open(PLANNING_FLAG_FILE1, 'a') as f:
f.write('\n')
f.write('--planning_upper_speed_limit=' + speed_limit + '\n\n')
with open(PLANNING_FLAG_FILE2, 'a') as f:
f.write('\n')
f.write('--planning_upper_speed_limit=' + speed_limit + '\n\n')
if __name__ == "__main__":
if len(sys.argv) < 2:
print("\nusage: python navi_config.py config.ini\n\n")
sys.exit(0)
config_file = sys.argv[1]
config = configparser.ConfigParser()
config.read(config_file)
set_hmi_conf(config)
set_planning_conf(config)
set_global_flag(config)
set_localization_flag(config)
set_planning_flag(config)
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/config/README.md
|
# Navi Config
Navi Config is a tool to set parameters and flags in various modules for navigation mode.
### usage
```
python navi_config.py default.ini
```
*default.ini* file is the default navigation mode configuration, with following content:
```
[PerceptionConf]
# three perception solutions: MOBILEYE, CAMERA, and VELODYNE64
perception = CAMERA
[LocalizationConf]
utm_zone = 10
[PlanningConf]
# three planners are available: EM, LATTICE, NAVI
planner_type = EM
# highest speed for planning algorithms, unit is meter per second
speed_limit = 5
```
In **PerceptionConf** section, the *perception* parameter is to specify the perception solution. Currently there are three supported in Apollo Navigation Mode: mobileye based, camera based and lidar based.
In the **LocalizationConf** section, utm_zone need to be specified based on location of the road test.
In the **PlanningConf** section, three planner are supported: EM, Lattice, and Navi. Select one for the planner_type parameter. speed_limt, which is the planner upper speed limit, is also configurable in this seciton, which unit is meter per second.
Developers could create differet ini files for different test scenarios/purposes or modified the default.ini based on needs.
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/config/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary")
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
filegroup(
name = "readme",
srcs = [
"README.md",
"default.ini",
],
)
py_binary(
name = "navi_config",
srcs = ["navi_config.py"],
data = ["default.ini"],
deps = [
"//modules/dreamview/proto:hmi_config_py_pb2",
"//modules/planning/proto:planning_config_py_pb2",
"//modules/tools/common:proto_utils",
],
)
install(
name = "install",
data = [":readme"],
data_dest = "tools/navigation/config",
py_dest = "tools/navigation/config",
targets = [
"navi_config",
]
)
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/provider_chassis.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
class ChassisProvider:
def __init__(self):
self.chassis_pb = None
def update(self, chassis_pb):
self.chassis_pb = chassis_pb
def get_speed_mps(self):
if self.chassis_pb is None:
return None
return self.chassis_pb.speed_mps
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/lanemarker_corrector.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
class LaneMarkerCorrector:
def __init__(self, left_marker, right_marker):
self.left_marker = left_marker
self.right_marker = right_marker
def correct(self, position, heading, routing_segment):
return self.left_marker, self.right_marker
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/speed_decider.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
class SpeedDecider:
def __init__(self, max_cruise_speed, enable_follow):
self.CRUISE_SPEED = max_cruise_speed # m/s
self.enable_follow = enable_follow
def get_target_speed_and_path_length(self, mobileye_provider,
chassis_provider, path_length):
obstacle_closest_lon = 999
obstacle_speed = None
obstacles = mobileye_provider.obstacles
for obs in obstacles:
if obs.lane == 1:
if (obs.x - obs.length / 2.0) < obstacle_closest_lon:
obstacle_closest_lon = obs.x - obs.length / 2.0
obstacle_speed = obs.rel_speed + \
chassis_provider.get_speed_mps()
new_path_length = path_length
if obstacle_closest_lon < new_path_length:
new_path_length = obstacle_closest_lon
if obstacle_speed is None or obstacle_speed > self.CRUISE_SPEED:
return self.CRUISE_SPEED, new_path_length
else:
return obstacle_speed, new_path_length
def get(self, mobileye_provider, chassis_provider, path_length):
if self.enable_follow:
return self.get_target_speed_and_path_length(mobileye_provider,
chassis_provider,
path_length)
else:
return self.CRUISE_SPEED, path_length
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/ad_vehicle.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
class ADVehicle:
def __init__(self):
self._chassis_pb = None
self._localization_pb = None
self.front_edge_to_center = 3.89
self.back_edge_to_center = 1.043
self.left_edge_to_center = 1.055
self.right_edge_to_center = 1.055
self.speed_mps = None
self.x = None
self.y = None
self.heading = None
def update_chassis(self, chassis_pb):
self._chassis_pb = chassis_pb
self.speed_mps = self._chassis_pb.speed_mps
def update_localization(self, localization_pb):
self._localization_pb = localization_pb
self.x = self._localization_pb.pose.position.x
self.y = self._localization_pb.pose.position.y
self.heading = self._localization_pb.pose.heading
def is_ready(self):
if self._chassis_pb is None or self._localization_pb is None:
return False
return True
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/provider_localization.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
class LocalizationProvider:
def __init__(self):
self.localization_pb = None
self.x = 0
self.y = 0
self.heading = 0
def update(self, localization_pb):
self.localization_pb = localization_pb
self.x = self.localization_pb.pose.position.x
self.y = self.localization_pb.pose.position.y
self.heading = self.localization_pb.pose.heading
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/local_path.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
class LocalPath:
def __init__(self, points):
self.points = points
def init_y(self):
if len(self.points) > 0:
return self.points[0][1]
return None
def get_xy(self):
x = []
y = []
for p in self.points:
x.append(p[0])
y.append(p[1])
return x, y
def range(self):
return len(self.points) - 1
def shift(self, dist):
for i in range(len(self.points)):
self.points[i][1] += dist
def cut(self, dist):
pass
def resample(self):
pass
def merge(self, local_path, weight):
for i in range(len(self.points)):
y = self.points[i][1]
if i < len(local_path.points):
y2 = local_path.points[i][1] * weight
self.points[i][1] = (y + y2) / (1 + weight)
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/heading_decider.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
import numpy.polynomial.polynomial as poly
class HeadingDecider:
def __init__(self):
self.mobileye_pb = None
def get_path(self, x, y, path_length):
ind = int(math.floor((abs(x[0]) * 100.0) / 1) + 1)
newx = [0]
newy = [0]
w = [1000]
if len(y) - ind > 0:
for i in range(len(y) - ind):
newx.append(x[i + ind])
newy.append(y[i + ind])
w.append(w[-1] - 10)
else:
newx.append(x[-1])
newy.append(y[-1])
w.append(w[-1] - 10)
coefs = poly.polyfit(newy, newx, 4, w=w) # x = f(y)
nx = poly.polyval(y, coefs)
return nx, y
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/BUILD
|
load("@rules_python//python:defs.bzl", "py_library")
package(default_visibility = ["//visibility:public"])
py_library(
name = "ad_vehicle",
srcs = ["ad_vehicle.py"],
)
py_library(
name = "heading_decider",
srcs = ["heading_decider.py"],
)
py_library(
name = "lanemarker_corrector",
srcs = ["lanemarker_corrector.py"],
)
py_library(
name = "local_path",
srcs = ["local_path.py"],
)
py_library(
name = "provider_chassis",
srcs = ["provider_chassis.py"],
)
py_library(
name = "provider_localization",
srcs = ["provider_localization.py"],
)
py_library(
name = "reference_path",
srcs = ["reference_path.py"],
)
py_library(
name = "speed_decider",
srcs = ["speed_decider.py"],
)
py_library(
name = "trajectory_generator",
srcs = ["trajectory_generator.py"],
deps = [
"//cyber/python/cyber_py3:cyber_time",
"//modules/common_msgs/chassis_msgs:chassis_py_pb2",
"//modules/common_msgs/basic_msgs:drive_state_py_pb2",
"//modules/common_msgs/planning_msgs:planning_py_pb2",
],
)
| 0
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apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/reference_path.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from numpy.polynomial.polynomial import polyval
class ReferencePath:
def __init__(self):
self.MINIMUM_PATH_LENGTH = 5
self.MAX_LAT_CHANGE = 0.1
self.init_y_last = None
def get_path_length(self, speed_mps):
path_length = self.MINIMUM_PATH_LENGTH
current_speed = speed_mps
if current_speed is not None:
if path_length < current_speed * 2:
path_length = math.ceil(current_speed * 2)
return path_length
def get_ref_path_init_y(self, init_y_perception):
if self.init_y_last is None:
return 0
if abs(init_y_perception - self.init_y_last) < self.MAX_LAT_CHANGE:
return init_y_perception
else:
if init_y_perception > self.init_y_last:
return self.init_y_last + self.MAX_LAT_CHANGE
else:
return self.init_y_last - self.MAX_LAT_CHANGE
def get_ref_path_by_lm(self, perception, chassis):
path_length = self.get_path_length(chassis.get_speed_mps())
init_y_perception = (perception.right_lm_coef[0] +
perception.left_lm_coef[0]) / -2.0
init_y = self.get_ref_path_init_y(init_y_perception)
self.init_y_last = init_y
path_x, path_y = self._get_perception_ref_path(
perception, path_length, init_y)
return path_x, path_y, path_length
def _get_perception_ref_path(self, perception, path_length, init_y):
path_coef = [0, 0, 0, 0]
path_coef[0] = -1 * init_y
quality = perception.right_lm_quality + perception.left_lm_quality
if quality > 0:
for i in range(1, 4):
path_coef[i] = (perception.right_lm_coef[i] *
perception.right_lm_quality +
perception.left_lm_coef[i] *
perception.left_lm_quality) / quality
path_x = []
path_y = []
for x in range(int(path_length)):
y = -1 * polyval(x, path_coef)
path_x.append(x)
path_y.append(y)
return path_x, path_y
def get_ref_path_by_lmr(self, perception, routing, adv):
path_length = self.get_path_length(adv.speed_mps)
rpath_x, rpath_y = routing.get_local_segment_spline(adv.x,
adv.y,
adv.heading)
init_y_perception = (perception.right_lm_coef[0] +
perception.left_lm_coef[0]) / -2.0
quality = perception.right_lm_quality + perception.left_lm_quality
quality = quality / 2.0
if len(rpath_x) >= path_length and routing.human and rpath_y[0] <= 3:
init_y_routing = rpath_y[0]
init_y = self.get_ref_path_init_y(init_y_routing)
if quality > 0.1:
quality = 0.1
self.init_y_last = init_y
else:
init_y = self.get_ref_path_init_y(init_y_perception)
self.init_y_last = init_y
lmpath_x, lmpath_y = self._get_perception_ref_path(
perception, path_length, init_y)
if len(rpath_x) < path_length:
return lmpath_x, lmpath_y, path_length
routing_shift = rpath_y[0] - init_y
path_x = []
path_y = []
for i in range(int(path_length)):
# TODO(yifei): more accurate shift is needed.
y = (lmpath_y[i] * quality + rpath_y[i] - routing_shift) / (
1 + quality)
path_x.append(i)
path_y.append(y)
return path_x, path_y, path_length
def shift_point(self, p, p2, distance):
delta_y = p2.y - p.y
delta_x = p2.x - p.x
angle = 0
if distance >= 0:
angle = math.atan2(delta_y, delta_x) + math.pi / 2.0
else:
angle = math.atan2(delta_y, delta_x) - math.pi / 2.0
p1n = []
p1n.append(p.x + (math.cos(angle) * distance))
p1n.append(p.y + (math.sin(angle) * distance))
p2n = []
p2n.append(p2.x + (math.cos(angle) * distance))
p2n.append(p2.y + (math.sin(angle) * distance))
return p1n, p2n
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/planning/trajectory_generator.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from numpy.polynomial.polynomial import polyval
from modules.common_msgs.planning_msgs import planning_pb2
from modules.common_msgs.chassis_msgs import chassis_pb2
from modules.common_msgs.basic_msgs import drive_state_pb2
from cyber.python.cyber_py3 import cyber_time
def euclidean_distance(point1, point2):
sum = (point1[0] - point2[0]) * (point1[0] - point2[0])
sum += (point1[1] - point2[1]) * (point1[1] - point2[1])
return math.sqrt(sum)
def get_theta(point, point_base):
# print point
return math.atan2(1, 0) - math.atan2(point[0] - point_base[0],
point[1] - point_base[1])
class TrajectoryGenerator:
def __init__(self):
self.mobileye_pb = None
def generate(self, path, final_path_length, speed,
start_timestamp):
path_x, path_y = path.get_xy()
adc_trajectory = planning_pb2.ADCTrajectory()
adc_trajectory.header.timestamp_sec = cyber_time.Time.now().to_sec()
adc_trajectory.header.module_name = "planning"
adc_trajectory.gear = chassis_pb2.Chassis.GEAR_DRIVE
adc_trajectory.latency_stats.total_time_ms = \
(cyber_time.Time.now().to_sec() - start_timestamp) * 1000
s = 0
relative_time = 0
adc_trajectory.engage_advice.advice \
= drive_state_pb2.EngageAdvice.READY_TO_ENGAGE
for x in range(int(final_path_length - 1)):
y = path_y[x]
traj_point = adc_trajectory.trajectory_point.add()
traj_point.path_point.x = x
traj_point.path_point.y = y
if x > 0:
dist = euclidean_distance((x, y), (x - 1, path_y[x - 1]))
s += dist
relative_time += dist / speed
traj_point.path_point.theta = get_theta(
(x + 1, path_y[x + 1]), (0, path_y[0]))
traj_point.path_point.s = s
traj_point.v = speed
traj_point.relative_time = relative_time
return adc_trajectory
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/driving_behavior/path_plot.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
import matplotlib.pyplot as plt
fig = plt.figure()
ax = plt.subplot2grid((1, 1), (0, 0))
styles = ["b-", "r-", "y-"]
i = 0
for fn in sys.argv[1:]:
f = open(fn, 'r')
xs = []
ys = []
for line in f:
line = line.replace("\n", '')
data = line.split(',')
x = float(data[0])
y = float(data[1])
xs.append(x)
ys.append(y)
f.close()
si = i % len(styles)
ax.plot(xs, ys, styles[si], lw=3, alpha=0.8)
i += 1
ax.axis('equal')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/driving_behavior/plot_gps_path.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
import pyproj
import matplotlib.pyplot as plt
projector = pyproj.Proj(proj='utm', zone=10, ellps='WGS84')
fig = plt.figure()
ax = plt.subplot2grid((1, 1), (0, 0))
styles = ['r-', 'b-']
i = 0
for fn in sys.argv[1:]:
X = []
Y = []
f = open(fn, 'r')
for line in f:
line = line.replace('\n', '')
vals = line.split(",")
if len(vals) < 3:
continue
print(float(vals[-2]), float(vals[-1]))
x, y = projector(float(vals[-1]), float(vals[-2]))
print(x, y)
X.append(x)
Y.append(y)
f.close()
ax.plot(X, Y, styles[i % len(styles)], lw=3, alpha=0.8)
i += 1
ax.axis('equal')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/driving_behavior/path_extract.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
extract localization message from bag files
Usage:
python path_extract.py file1 file2 ...
"""
import sys
import datetime
from cyber.python.cyber_py3.record import RecordReader
from modules.common_msgs.localization_msgs import localization_pb2
kLocalizationTopic = '/apollo/localization/pose'
if __name__ == '__main__':
bag_files = sys.argv[1:]
bag_file = bag_files[0]
now = datetime.datetime.now().strftime("%Y-%m-%d_%H.%M.%S")
f = open("path_" + bag_file.split('/')[-1] + ".txt", 'w')
for bag_file in bag_files:
print("begin to extract path from file :", bag_file)
reader = RecordReader(bag_file)
localization = localization_pb2.LocalizationEstimate()
for msg in reader.read_messages():
if msg.topic == kLocalizationTopic:
localization.ParseFromString(msg.message)
x = localization.pose.position.x
y = localization.pose.position.y
f.write(str(x) + "," + str(y) + "\n")
print("Finished extracting path from file :", bag_file)
f.close()
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/driving_behavior/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary")
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
py_binary(
name = "path_extract",
srcs = ["path_extract.py"],
deps = [
"//cyber/python/cyber_py3:record",
"//modules/common_msgs/localization_msgs:localization_py_pb2",
],
)
py_binary(
name = "path_plot",
srcs = ["path_plot.py"],
)
py_binary(
name = "path_process",
srcs = ["path_process.py"],
)
py_binary(
name = "plot_gps_path",
srcs = ["plot_gps_path.py"],
)
install(
name = "install",
data_dest = "tools/navigation/driving_behavior",
py_dest = "tools/navigation/driving_behavior",
targets = [
"path_plot",
"path_process",
"plot_gps_path",
"path_extract",
]
)
| 0
|
apollo_public_repos/apollo/modules/tools/navigation
|
apollo_public_repos/apollo/modules/tools/navigation/driving_behavior/path_process.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import sys
from shapely.geometry import LineString, Point
import matplotlib.pyplot as plt
if __name__ == "__main__":
fpath = sys.argv[1]
f = open(fpath, 'r')
points_x = []
points_y = []
points = []
for line in f:
line = line.replace("\n", '')
if len(line.strip()) == 0:
continue
data = line.split(',')
x = float(data[0])
y = float(data[1])
points_x.append(x)
points_y.append(y)
points.append((x, y))
f.close()
line_string = LineString(points)
new_px = []
new_py = []
f = open("processed_" + fpath.split("/")[-1], 'w')
for i in range(int(line_string.length)):
p = line_string.interpolate(i)
new_px.append(p.x)
new_py.append(p.y)
f.write(str(p.x) + "," + str(p.y) + "\n")
f.close()
print(len(points_x))
print(len(new_px))
plt.figure()
plt.plot(points_x, points_y, '-r', lw=1, label='raw')
plt.plot(new_px, new_py, '-g', label='processed')
plt.legend(loc='best')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/open_space_roi_visualizer.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
# @file to run it, change the modules/common/configs/config_gflags.cc to use sunnyvale_with_two_offices
from open_space_roi_interface import *
import matplotlib.pyplot as plt
# initialize object
open_space_roi = open_space_roi()
lane_id = "11564dup1_1_-1"
parking_id = "11543"
num_output_buffer = 50
unrotated_roi_boundary_x = (c_double * num_output_buffer)()
roi_boundary_x = (c_double * num_output_buffer)()
parking_spot_x = (c_double * num_output_buffer)()
unrotated_roi_boundary_y = (c_double * num_output_buffer)()
roi_boundary_y = (c_double * num_output_buffer)()
parking_spot_y = (c_double * num_output_buffer)()
end_pose = (c_double * num_output_buffer)()
xy_boundary = (c_double * num_output_buffer)()
origin_pose = (c_double * num_output_buffer)()
if not open_space_roi.ROITest(lane_id, parking_id,
unrotated_roi_boundary_x, unrotated_roi_boundary_y, roi_boundary_x, roi_boundary_y,
parking_spot_x, parking_spot_y, end_pose,
xy_boundary, origin_pose):
print("open_space_roi fail")
result_unrotated_roi_boundary_x = []
result_unrotated_roi_boundary_y = []
result_roi_boundary_x = []
result_roi_boundary_y = []
result_parking_spot_x = []
result_parking_spot_y = []
result_end_pose = []
result_xy_boundary = []
result_origin_pose = []
print("vertices of obstacles")
for i in range(0, 10):
result_unrotated_roi_boundary_x.append(float(unrotated_roi_boundary_x[i]))
result_unrotated_roi_boundary_y.append(float(unrotated_roi_boundary_y[i]))
result_roi_boundary_x.append(float(roi_boundary_x[i]))
result_roi_boundary_y.append(float(roi_boundary_y[i]))
print(str(float(roi_boundary_x[i])))
print(str(float(roi_boundary_y[i])))
print("parking spot")
for i in range(0, 4):
result_parking_spot_x.append(float(parking_spot_x[i]))
result_parking_spot_y.append(float(parking_spot_y[i]))
print("end_pose in x,y,phi,v")
for i in range(0, 4):
print(str(float(end_pose[i])))
print("xy_boundary in xmin xmax ymin ymax")
for i in range(0, 4):
print(str(float(xy_boundary[i])))
print("origin_pose")
for i in range(0, 2):
print(str(float(origin_pose[i])))
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax1.scatter(result_unrotated_roi_boundary_x, result_unrotated_roi_boundary_y)
ax1.scatter(result_parking_spot_x, result_parking_spot_y)
ax2 = fig.add_subplot(212)
ax2.scatter(result_roi_boundary_x, result_roi_boundary_y)
plt.gca().set_aspect('equal', adjustable='box')
plt.show()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/auto_param_tuning.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import argparse
import random
from google.protobuf.internal import decoder
from google.protobuf.internal import encoder
from modules.common_msgs.planning_msgs import planner_open_space_config_pb2
import modules.tools.common.proto_utils as proto_utils
import distance_approach_visualizer
import hybrid_a_star_visualizer
random.seed(99999)
rand_num = 1000
original_file_path = "/apollo/modules/planning/conf/planner_open_space_config.pb.txt"
optimal_file_path = "/apollo/modules/planning/conf/optimal_planner_open_space_config_-8_4.pb.txt"
# tunning_object = "coarse_trajectory"
tunning_object = "smooth_trajectory"
def load_open_space_protobuf(filename):
open_space_params = planner_open_space_config_pb2.PlannerOpenSpaceConfig()
proto_utils.get_pb_from_text_file(filename, open_space_params)
return open_space_params
def GetParamsForTunning(tunning_object):
param_names_and_range = []
if tunning_object == "coarse_trajectory":
param_names_and_range.append(
("warm_start_config.traj_forward_penalty", 2.0))
param_names_and_range.append(
("warm_start_config.traj_back_penalty", 2.0))
param_names_and_range.append(
("warm_start_config.traj_gear_switch_penalty", 2.0))
param_names_and_range.append(
("warm_start_config.traj_steer_penalty", 3.0))
param_names_and_range.append(
("warm_start_config.traj_steer_change_penalty", 2.0))
elif tunning_object == "smooth_trajectory":
param_names_and_range.append(
("distance_approach_config.weight_steer", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_a", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_steer_rate", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_a_rate", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_x", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_y", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_phi", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_v", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_steer_stitching", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_a_stitching", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_first_order_time", 2.0))
param_names_and_range.append(
("distance_approach_config.weight_second_order_time", 2.0))
return param_names_and_range
def RandSampling(param_names_and_range, origin_open_space_params):
params_lists = []
for iter in range(0, rand_num):
rand_params = planner_open_space_config_pb2.PlannerOpenSpaceConfig()
rand_params.CopyFrom(origin_open_space_params)
for param in param_names_and_range:
exec("rand_params." +
str(param[0]) + "=random.uniform(max(rand_params." +
str(param[0])
+ " - " + str(param[1]) + ",0.0)"
+ " ,rand_params." + str(param[0]) + " + " + str(param[1]) + ")")
params_lists.append(rand_params)
return params_lists
def TestingParams(params_lists, tunning_object):
key_to_evaluations = {}
for iter in range(0, len(params_lists)):
evaluation = ParamEvaluation(params_lists[iter], tunning_object)
key_to_evaluations[iter] = evaluation
return key_to_evaluations
def ParamEvaluation(params, tunning_object):
proto_utils.write_pb_to_text_file(params, original_file_path)
if tunning_object == "coarse_trajectory":
visualize_flag = False
success, x_out, y_out, phi_out, v_out, a_out, steer_out, planning_time = hybrid_a_star_visualizer.HybridAStarPlan(
visualize_flag)
if not success:
return float('inf')
else:
return planning_time
elif tunning_object == "smooth_trajectory":
visualize_flag = False
success, opt_x_out, opt_y_out, opt_phi_out, opt_v_out, opt_a_out, opt_steer_out, opt_time_out, planning_time = distance_approach_visualizer.SmoothTrajectory(
visualize_flag)
if not success:
return float('inf')
else:
return planning_time
def GetOptimalParams(params_lists, key_to_evaluations):
tmp = []
for key, value in key_to_evaluations.items():
tmptuple = (value, key)
tmp.append(tmptuple)
tmp = sorted(tmp)
optimal_params = params_lists[tmp[0][1]]
optimal_evaluation = tmp[0][0]
return optimal_params, optimal_evaluation
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
"--InputConfig", help="original conf address to be tuned", type=str, default=original_file_path)
parser.add_argument("--OutputConfig", help="tuned conf address",
type=str, default=optimal_file_path)
parser.add_argument("--TunningObject",
help="algorithm to be tuned", type=str, default=tunning_object)
args = parser.parse_args()
original_file_path = args.InputConfig
optimal_file_path = args.OutputConfig
tunning_object = args.TunningObject
param_names_and_range = GetParamsForTunning(tunning_object)
origin_open_space_params = load_open_space_protobuf(original_file_path)
params_lists = RandSampling(
param_names_and_range, origin_open_space_params)
key_to_evaluations = TestingParams(params_lists, tunning_object)
optimal_params, optimal_evaluation = GetOptimalParams(
params_lists, key_to_evaluations)
origin_evaluation = ParamEvaluation(
origin_open_space_params, tunning_object)
print("optimal_evaluation is " + str(optimal_evaluation))
print("origin_evaluation is " + str(origin_evaluation))
improvement_percentage = (
origin_evaluation - optimal_evaluation) / origin_evaluation
print("improvement_percentage is " + str(improvement_percentage))
proto_utils.write_pb_to_text_file(optimal_params, optimal_file_path)
proto_utils.write_pb_to_text_file(
origin_open_space_params, original_file_path)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/distance_approach_visualizer.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
import time
from matplotlib import animation
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import numpy as np
from distance_approach_python_interface import *
result_file = "/tmp/open_space_osqp_ipopt.csv"
# def SmoothTrajectory(visualize_flag):
def SmoothTrajectory(visualize_flag, sx, sy):
# initialze object
OpenSpacePlanner = DistancePlanner()
# parameter(except max, min and car size is defined in proto)
num_output_buffer = 10000
# sx = -8
# sy = 1.5
# sphi = 0.5
sphi = 0.0
scenario = "backward"
# scenario = "parallel"
if scenario == "backward":
# obstacles for distance approach(vertices coords in clock wise order)
ROI_distance_approach_parking_boundary = (
c_double * 20)(*[-13.6407054776,
0.0140634663703,
0.0,
0.0,
0.0515703622475,
-5.15258191624,
0.0515703622475,
-5.15258191624,
2.8237895441,
-5.15306980547,
2.8237895441,
-5.15306980547,
2.7184833539,
-0.0398078878812,
16.3592013995,
-0.011889513383,
16.3591910364,
5.60414234644,
-13.6406951857,
5.61797800844,
])
OpenSpacePlanner.AddObstacle(
ROI_distance_approach_parking_boundary)
# parking lot position
ex = 1.359
ey = -3.86443643718
ephi = 1.581
XYbounds = [-13.6406951857, 16.3591910364, -5.15258191624, 5.61797800844]
x = (c_double * num_output_buffer)()
y = (c_double * num_output_buffer)()
phi = (c_double * num_output_buffer)()
v = (c_double * num_output_buffer)()
a = (c_double * num_output_buffer)()
steer = (c_double * num_output_buffer)()
opt_x = (c_double * num_output_buffer)()
opt_y = (c_double * num_output_buffer)()
opt_phi = (c_double * num_output_buffer)()
opt_v = (c_double * num_output_buffer)()
opt_a = (c_double * num_output_buffer)()
opt_steer = (c_double * num_output_buffer)()
opt_time = (c_double * num_output_buffer)()
opt_dual_l = (c_double * num_output_buffer)()
opt_dual_n = (c_double * num_output_buffer)()
size = (c_ushort * 1)()
XYbounds_ctype = (c_double * 4)(*XYbounds)
hybrid_time = (c_double * 1)(0.0)
dual_time = (c_double * 1)(0.0)
ipopt_time = (c_double * 1)(0.0)
success = True
start = time.time()
print("planning start")
if not OpenSpacePlanner.DistancePlan(sx, sy, sphi, ex, ey, ephi, XYbounds_ctype):
print("planning fail")
success = False
# exit()
planning_time = time.time() - start
print("planning time is " + str(planning_time))
x_out = []
y_out = []
phi_out = []
v_out = []
a_out = []
steer_out = []
opt_x_out = []
opt_y_out = []
opt_phi_out = []
opt_v_out = []
opt_a_out = []
opt_steer_out = []
opt_time_out = []
opt_dual_l_out = []
opt_dual_n_out = []
if visualize_flag and success:
# load result
OpenSpacePlanner.DistanceGetResult(x, y, phi, v, a, steer, opt_x,
opt_y, opt_phi, opt_v, opt_a, opt_steer, opt_time,
opt_dual_l, opt_dual_n, size,
hybrid_time, dual_time, ipopt_time)
for i in range(0, size[0]):
x_out.append(float(x[i]))
y_out.append(float(y[i]))
phi_out.append(float(phi[i]))
v_out.append(float(v[i]))
a_out.append(float(a[i]))
steer_out.append(float(steer[i]))
opt_x_out.append(float(opt_x[i]))
opt_y_out.append(float(opt_y[i]))
opt_phi_out.append(float(opt_phi[i]))
opt_v_out.append(float(opt_v[i]))
opt_a_out.append(float(opt_a[i]))
opt_steer_out.append(float(opt_steer[i]))
opt_time_out.append(float(opt_time[i]))
for i in range(0, size[0] * 6):
opt_dual_l_out.append(float(opt_dual_l[i]))
for i in range(0, size[0] * 16):
opt_dual_n_out.append(float(opt_dual_n[i]))
# trajectories plot
fig1 = plt.figure(1)
ax = fig1.add_subplot(111)
for i in range(0, size[0]):
# warm start
downx = 1.055 * math.cos(phi_out[i] - math.pi / 2)
downy = 1.055 * math.sin(phi_out[i] - math.pi / 2)
leftx = 1.043 * math.cos(phi_out[i] - math.pi)
lefty = 1.043 * math.sin(phi_out[i] - math.pi)
x_shift_leftbottom = x_out[i] + downx + leftx
y_shift_leftbottom = y_out[i] + downy + lefty
warm_start_car = patches.Rectangle((x_shift_leftbottom, y_shift_leftbottom), 3.89 + 1.043, 1.055 * 2,
angle=phi_out[i] * 180 / math.pi, linewidth=1, edgecolor='r', facecolor='none')
warm_start_arrow = patches.Arrow(
x_out[i], y_out[i], 0.25 * math.cos(phi_out[i]), 0.25 * math.sin(phi_out[i]), 0.2, edgecolor='r',)
# ax.add_patch(warm_start_car)
ax.add_patch(warm_start_arrow)
# distance approach
downx = 1.055 * math.cos(opt_phi_out[i] - math.pi / 2)
downy = 1.055 * math.sin(opt_phi_out[i] - math.pi / 2)
leftx = 1.043 * math.cos(opt_phi_out[i] - math.pi)
lefty = 1.043 * math.sin(opt_phi_out[i] - math.pi)
x_shift_leftbottom = opt_x_out[i] + downx + leftx
y_shift_leftbottom = opt_y_out[i] + downy + lefty
smoothing_car = patches.Rectangle((x_shift_leftbottom, y_shift_leftbottom), 3.89 + 1.043, 1.055 * 2,
angle=opt_phi_out[i] * 180 / math.pi, linewidth=1, edgecolor='y', facecolor='none')
smoothing_arrow = patches.Arrow(
opt_x_out[i], opt_y_out[i], 0.25 * math.cos(opt_phi_out[i]), 0.25 * math.sin(opt_phi_out[i]), 0.2, edgecolor='y',)
ax.add_patch(smoothing_car)
ax.add_patch(smoothing_arrow)
ax.plot(sx, sy, "s")
ax.plot(ex, ey, "s")
if scenario == "backward":
left_boundary_x = [-13.6407054776, 0.0, 0.0515703622475]
left_boundary_y = [0.0140634663703, 0.0, -5.15258191624]
down_boundary_x = [0.0515703622475, 2.8237895441]
down_boundary_y = [-5.15258191624, -5.15306980547]
right_boundary_x = [2.8237895441, 2.7184833539, 16.3592013995]
right_boundary_y = [-5.15306980547, -0.0398078878812, -0.011889513383]
up_boundary_x = [16.3591910364, -13.6406951857]
up_boundary_y = [5.60414234644, 5.61797800844]
ax.plot(left_boundary_x, left_boundary_y, "k")
ax.plot(down_boundary_x, down_boundary_y, "k")
ax.plot(right_boundary_x, right_boundary_y, "k")
ax.plot(up_boundary_x, up_boundary_y, "k")
plt.axis('equal')
# input plot
fig2 = plt.figure(2)
v_graph = fig2.add_subplot(411)
v_graph.title.set_text('v')
v_graph.plot(np.linspace(0, size[0], size[0]), v_out)
v_graph.plot(np.linspace(0, size[0], size[0]), opt_v_out)
a_graph = fig2.add_subplot(412)
a_graph.title.set_text('a')
a_graph.plot(np.linspace(0, size[0], size[0]), a_out)
a_graph.plot(np.linspace(0, size[0], size[0]), opt_a_out)
steer_graph = fig2.add_subplot(413)
steer_graph.title.set_text('steering')
steer_graph.plot(np.linspace(0, size[0], size[0]), steer_out)
steer_graph.plot(np.linspace(0, size[0], size[0]), opt_steer_out)
steer_graph = fig2.add_subplot(414)
steer_graph.title.set_text('t')
steer_graph.plot(np.linspace(0, size[0], size[0]), opt_time_out)
# dual variables
fig3 = plt.figure(3)
dual_l_graph = fig3.add_subplot(211)
dual_l_graph.title.set_text('dual_l')
dual_l_graph.plot(np.linspace(0, size[0] * 6, size[0] * 6), opt_dual_l_out)
dual_n_graph = fig3.add_subplot(212)
dual_n_graph.title.set_text('dual_n')
dual_n_graph.plot(np.linspace(0, size[0] * 16, size[0] * 16), opt_dual_n_out)
plt.show()
return True
if not visualize_flag:
if success:
# load result
OpenSpacePlanner.DistanceGetResult(x, y, phi, v, a, steer, opt_x,
opt_y, opt_phi, opt_v, opt_a, opt_steer, opt_time,
opt_dual_l, opt_dual_n, size,
hybrid_time, dual_time, ipopt_time)
for i in range(0, size[0]):
x_out.append(float(x[i]))
y_out.append(float(y[i]))
phi_out.append(float(phi[i]))
v_out.append(float(v[i]))
a_out.append(float(a[i]))
steer_out.append(float(steer[i]))
opt_x_out.append(float(opt_x[i]))
opt_y_out.append(float(opt_y[i]))
opt_phi_out.append(float(opt_phi[i]))
opt_v_out.append(float(opt_v[i]))
opt_a_out.append(float(opt_a[i]))
opt_steer_out.append(float(opt_steer[i]))
opt_time_out.append(float(opt_time[i]))
# check end_pose distacne
end_pose_dist = math.sqrt((opt_x_out[-1] - ex)**2 + (opt_y_out[-1] - ey)**2)
end_pose_heading = abs(opt_phi_out[-1] - ephi)
reach_end_pose = (end_pose_dist <= 0.1 and end_pose_heading <= 0.17)
else:
end_pose_dist = 100.0
end_pose_heading = 100.0
reach_end_pose = 0
return [success, end_pose_dist, end_pose_heading, reach_end_pose, opt_x_out, opt_y_out, opt_phi_out, opt_v_out, opt_a_out, opt_steer_out, opt_time_out,
hybrid_time, dual_time, ipopt_time, planning_time]
return False
if __name__ == '__main__':
# visualize_flag = True
# SmoothTrajectory(visualize_flag)
visualize_flag = False
planning_time_stats = []
hybrid_time_stats = []
dual_time_stats = []
ipopt_time_stats = []
end_pose_dist_stats = []
end_pose_heading_stats = []
test_count = 0
success_count = 0
for sx in np.arange(-10, 10, 1.0):
for sy in np.arange(2, 4, 0.5):
print("sx is " + str(sx) + " and sy is " + str(sy))
test_count += 1
result = SmoothTrajectory(visualize_flag, sx, sy)
# if result[0] and result[3]: # success cases only
if result[0]:
success_count += 1
planning_time_stats.append(result[-1])
ipopt_time_stats.append(result[-2][0])
dual_time_stats.append(result[-3][0])
hybrid_time_stats.append(result[-4][0])
end_pose_dist_stats.append(result[1])
end_pose_heading_stats.append(result[2])
print("success rate is " + str(float(success_count) / float(test_count)))
print("min is " + str(min(planning_time_stats)))
print("max is " + str(max(planning_time_stats)))
print("average is " + str(sum(planning_time_stats) / len(planning_time_stats)))
print("max end_pose_dist difference is: " + str(max(end_pose_dist_stats)))
print("min end_pose_dist difference is: " + str(min(end_pose_dist_stats)))
print("average end_pose_dist difference is: " +
str(sum(end_pose_dist_stats) / len(end_pose_dist_stats)))
print("max end_pose_heading difference is: " + str(max(end_pose_heading_stats)))
print("min end_pose_heading difference is: " + str(min(end_pose_heading_stats)))
print("average end_pose_heading difference is: " +
str(sum(end_pose_heading_stats) / len(end_pose_heading_stats)))
module_timing = np.asarray([hybrid_time_stats, dual_time_stats, ipopt_time_stats])
np.savetxt(result_file, module_timing, delimiter=",")
print("average hybrid time(s): %4.4f, with max: %4.4f, min: %4.4f" % (
sum(hybrid_time_stats) / len(hybrid_time_stats) / 1000.0, max(hybrid_time_stats) / 1000.0,
min(hybrid_time_stats) / 1000.0))
print("average dual time(s): %4.4f, with max: %4.4f, min: %4.4f" % (
sum(dual_time_stats) / len(dual_time_stats) / 1000.0, max(dual_time_stats) / 1000.0,
min(dual_time_stats) / 1000.0))
print("average ipopt time(s): %4.4f, with max: %4.4f, min: %4.4f" % (
sum(ipopt_time_stats) / len(ipopt_time_stats) / 1000.0, max(ipopt_time_stats) / 1000.0,
min(ipopt_time_stats) / 1000.0))
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/open_space_roi_interface.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import ctypes
import math
from ctypes import cdll, c_ushort, c_int, c_char_p, c_double, POINTER
lib = cdll.LoadLibrary(
'/apollo/bazel-bin/modules/planning/open_space/tools/open_space_roi_wrapper_lib.so')
class open_space_roi(object):
def __init__(self):
self.open_space_roi_test = lib.CreateROITestPtr()
def ROITest(self, lane_id, parking_id,
unrotated_roi_boundary_x, unrotated_roi_boundary_y, roi_boundary_x, roi_boundary_y,
parking_spot_x, parking_spot_y, end_pose,
xy_boundary, origin_pose):
return lib.ROITest(self.open_space_roi_test, (c_char_p)(lane_id), (c_char_p)(parking_id),
POINTER(c_double)(unrotated_roi_boundary_x), POINTER(
c_double)(unrotated_roi_boundary_y),
POINTER(c_double)(roi_boundary_x), POINTER(
c_double)(roi_boundary_y), POINTER(c_double)(
parking_spot_x), POINTER(c_double)(
parking_spot_y), POINTER(c_double)(end_pose),
POINTER(c_double)(xy_boundary), POINTER(c_double)(origin_pose))
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/hybrid_a_star_python_interface.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from ctypes import c_bool
from ctypes import c_double
from ctypes import c_int
from ctypes import c_ushort
from ctypes import c_void_p
lib = cdll.LoadLibrary(
'/apollo/bazel-bin/modules/planning/open_space/tools/hybrid_a_star_wrapper_lib.so')
lib.CreatePlannerPtr.argtypes = []
lib.CreatePlannerPtr.restype = c_void_p
lib.CreateResultPtr.argtypes = []
lib.CreateResultPtr.restype = c_void_p
lib.CreateObstaclesPtr.argtypes = []
lib.CreateObstaclesPtr.restype = c_void_p
lib.AddVirtualObstacle.argtypes = [c_void_p, POINTER(c_double), POINTER(c_double), c_int]
lib.Plan.restype = c_bool
lib.Plan.argtypes = [c_void_p, c_void_p, c_void_p, c_double, c_double, c_double, c_double,
c_double, c_double, POINTER(c_double)]
lib.GetResult.argtypes = [c_void_p, POINTER(c_double), POINTER(c_double), POINTER(c_double),
POINTER(c_double), POINTER(c_double), POINTER(c_double), POINTER(c_ushort)]
class HybridAStarPlanner(object):
def __init__(self):
self.planner = lib.CreatePlannerPtr()
self.obstacles = lib.CreateObstaclesPtr()
self.result = lib.CreateResultPtr()
def AddVirtualObstacle(self, obstacle_x, obstacle_y, vertice_num):
lib.AddVirtualObstacle(self.obstacles, POINTER(c_double)(obstacle_x),
POINTER(c_double)(obstacle_y), (c_int)(vertice_num))
def Plan(self, sx, sy, sphi, ex, ey, ephi, XYbounds):
return lib.Plan(self.planner, self.obstacles, self.result, c_double(sx),
c_double(sy), c_double(sphi), c_double(ex), c_double(ey),
c_double(ephi), POINTER(c_double)(XYbounds))
def GetResult(self, x, y, phi, v, a, steer, output_size):
lib.GetResult(self.result, POINTER(c_double)(x), POINTER(c_double)(y),
POINTER(c_double)(phi), POINTER(c_double)(v), POINTER(c_double)(a),
POINTER(c_double)(steer), POINTER(c_ushort)(output_size))
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/distance_approach_python_interface.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
from ctypes import c_bool
from ctypes import c_double
from ctypes import c_ushort
from ctypes import c_void_p
from ctypes import cdll, POINTER
lib = cdll.LoadLibrary(
'/apollo/bazel-bin/modules/planning/open_space/tools/distance_approach_problem_wrapper_lib.so')
lib.CreateHybridAPtr.argtypes = []
lib.CreateHybridAPtr.restype = c_void_p
lib.DistanceCreateResultPtr.argtypes = []
lib.DistanceCreateResultPtr.restype = c_void_p
lib.DistanceCreateObstaclesPtr.argtypes = []
lib.DistanceCreateObstaclesPtr.restype = c_void_p
lib.AddObstacle.argtypes = [c_void_p, POINTER(c_double)]
lib.DistancePlan.restype = c_bool
lib.DistancePlan.argtypes = [c_void_p, c_void_p, c_void_p, c_double, c_double, c_double, c_double,
c_double, c_double, POINTER(c_double)]
lib.DistanceGetResult.argtypes = [c_void_p, c_void_p, POINTER(c_double), POINTER(c_double), POINTER(c_double),
POINTER(c_double), POINTER(c_double), POINTER(
c_double), POINTER(c_double),
POINTER(c_double), POINTER(c_double), POINTER(
c_double), POINTER(c_double),
POINTER(c_double), POINTER(c_double), POINTER(
c_double), POINTER(c_double),
POINTER(c_ushort), POINTER(c_double), POINTER(c_double), POINTER(c_double)]
class DistancePlanner(object):
def __init__(self):
self.warm_start_planner = lib.CreateHybridAPtr()
self.obstacles = lib.DistanceCreateObstaclesPtr()
self.result = lib.DistanceCreateResultPtr()
def AddObstacle(self, ROI_distance_approach_parking_boundary):
lib.AddObstacle(self.obstacles, POINTER(
c_double)(ROI_distance_approach_parking_boundary))
def DistancePlan(self, sx, sy, sphi, ex, ey, ephi, XYbounds):
return lib.DistancePlan(self.warm_start_planner, self.obstacles, self.result, c_double(sx),
c_double(sy), c_double(sphi), c_double(ex), c_double(ey), c_double(ephi), POINTER(c_double)(XYbounds))
def DistanceGetResult(self, x, y, phi, v, a, steer, opt_x, opt_y, opt_phi, opt_v, opt_a, opt_steer, opt_time,
opt_dual_l, opt_dual_n, output_size, hybrid_time, dual_time, ipopt_time):
lib.DistanceGetResult(self.result, self.obstacles, POINTER(c_double)(x), POINTER(c_double)(y),
POINTER(c_double)(phi), POINTER(c_double)(v), POINTER(c_double)(a), POINTER(
c_double)(steer), POINTER(c_double)(opt_x), POINTER(c_double)(opt_y),
POINTER(c_double)(opt_phi), POINTER(c_double)(opt_v), POINTER(c_double)(opt_a),
POINTER(c_double)(opt_steer), POINTER(c_double)(
opt_time), POINTER(c_double)(opt_dual_l),
POINTER(c_double)(opt_dual_n), POINTER(c_ushort)(output_size),
POINTER(c_double)(hybrid_time), POINTER(c_double)(dual_time), POINTER(c_double)(ipopt_time))
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/hybrid_a_star_visualizer.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
import math
import time
from matplotlib import animation
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import numpy as np
from hybrid_a_star_python_interface import *
def HybridAStarPlan(visualize_flag):
# initialze object
HybridAStar = HybridAStarPlanner()
# parameter(except max, min and car size is defined in proto)
num_output_buffer = 100000
sx = -8
sy = 4
sphi = 0.0
scenario = "backward"
# scenario = "parallel"
if scenario == "backward":
# for parking space 11543 in sunnyvale_with_two_offices
left_boundary_x = (
c_double * 3)(*[-13.6407054776, 0.0, 0.0515703622475])
left_boundary_y = (
c_double * 3)(*[0.0140634663703, 0.0, -5.15258191624])
down_boundary_x = (c_double * 2)(*[0.0515703622475, 2.8237895441])
down_boundary_y = (c_double * 2)(*[-5.15258191624, -5.15306980547])
right_boundary_x = (
c_double * 3)(*[2.8237895441, 2.7184833539, 16.3592013995])
right_boundary_y = (
c_double * 3)(*[-5.15306980547, -0.0398078878812, -0.011889513383])
up_boundary_x = (c_double * 2)(*[16.3591910364, -13.6406951857])
up_boundary_y = (c_double * 2)(*[5.60414234644, 5.61797800844])
# obstacles(x, y, size)
HybridAStar.AddVirtualObstacle(left_boundary_x, left_boundary_y, 3)
HybridAStar.AddVirtualObstacle(
down_boundary_x, down_boundary_y, 2)
HybridAStar.AddVirtualObstacle(
right_boundary_x, right_boundary_y, 3)
HybridAStar.AddVirtualObstacle(
up_boundary_x, up_boundary_y, 2)
ex = 1.359
ey = -3.86443643718
ephi = 1.581
XYbounds = [-13.6406951857, 16.3591910364, -
5.15258191624, 5.61797800844]
x = (c_double * num_output_buffer)()
y = (c_double * num_output_buffer)()
phi = (c_double * num_output_buffer)()
v = (c_double * num_output_buffer)()
a = (c_double * num_output_buffer)()
steer = (c_double * num_output_buffer)()
size = (c_ushort * 1)()
XYbounds_ctype = (c_double * 4)(*XYbounds)
start = time.time()
print("planning start")
success = True
if not HybridAStar.Plan(sx, sy, sphi, ex, ey, ephi, XYbounds_ctype):
print("planning fail")
success = False
end = time.time()
planning_time = end - start
print("planning time is " + str(planning_time))
# load result
x_out = []
y_out = []
phi_out = []
v_out = []
a_out = []
steer_out = []
if visualize_flag and success:
HybridAStar.GetResult(x, y, phi, v, a, steer, size)
for i in range(0, size[0]):
x_out.append(float(x[i]))
y_out.append(float(y[i]))
phi_out.append(float(phi[i]))
v_out.append(float(v[i]))
a_out.append(float(a[i]))
steer_out.append(float(steer[i]))
# plot
fig1 = plt.figure(1)
ax = fig1.add_subplot(111)
for i in range(0, size[0]):
downx = 1.055 * math.cos(phi_out[i] - math.pi / 2)
downy = 1.055 * math.sin(phi_out[i] - math.pi / 2)
leftx = 1.043 * math.cos(phi_out[i] - math.pi)
lefty = 1.043 * math.sin(phi_out[i] - math.pi)
x_shift_leftbottom = x_out[i] + downx + leftx
y_shift_leftbottom = y_out[i] + downy + lefty
car = patches.Rectangle((x_shift_leftbottom, y_shift_leftbottom), 3.89 + 1.043, 1.055*2,
angle=phi_out[i] * 180 / math.pi, linewidth=1, edgecolor='r', facecolor='none')
arrow = patches.Arrow(
x_out[i], y_out[i], 0.25*math.cos(phi_out[i]), 0.25*math.sin(phi_out[i]), 0.2)
ax.add_patch(car)
ax.add_patch(arrow)
ax.plot(sx, sy, "s")
ax.plot(ex, ey, "s")
if scenario == "backward":
left_boundary_x = [-13.6407054776, 0.0, 0.0515703622475]
left_boundary_y = [0.0140634663703, 0.0, -5.15258191624]
down_boundary_x = [0.0515703622475, 2.8237895441]
down_boundary_y = [-5.15258191624, -5.15306980547]
right_boundary_x = [2.8237895441, 2.7184833539, 16.3592013995]
right_boundary_y = [-5.15306980547, -0.0398078878812, -0.011889513383]
up_boundary_x = [16.3591910364, -13.6406951857]
up_boundary_y = [5.60414234644, 5.61797800844]
ax.plot(left_boundary_x, left_boundary_y, "k")
ax.plot(down_boundary_x, down_boundary_y, "k")
ax.plot(right_boundary_x, right_boundary_y, "k")
ax.plot(up_boundary_x, up_boundary_y, "k")
plt.axis('equal')
fig2 = plt.figure(2)
v_graph = fig2.add_subplot(311)
v_graph.title.set_text('v')
v_graph.plot(np.linspace(0, size[0], size[0]), v_out)
a_graph = fig2.add_subplot(312)
a_graph.title.set_text('a')
a_graph.plot(np.linspace(0, size[0], size[0]), a_out)
steer_graph = fig2.add_subplot(313)
steer_graph.title.set_text('steering')
steer_graph.plot(np.linspace(0, size[0], size[0]), steer_out)
plt.show()
if not visualize_flag:
if success:
HybridAStar.GetResult(x, y, phi, v, a, steer, size)
for i in range(0, size[0]):
x_out.append(float(x[i]))
y_out.append(float(y[i]))
phi_out.append(float(phi[i]))
v_out.append(float(v[i]))
a_out.append(float(a[i]))
steer_out.append(float(steer[i]))
return success, x_out, y_out, phi_out, v_out, a_out, steer_out, planning_time
if __name__ == '__main__':
visualize_flag = True
HybridAStarPlan(visualize_flag)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/open_space_visualization/BUILD
|
load("@rules_python//python:defs.bzl", "py_binary", "py_library")
load("//tools/install:install.bzl", "install")
package(default_visibility = ["//visibility:public"])
py_library(
name = "distance_approach_python_interface",
srcs = ["distance_approach_python_interface.py"],
data = [
"//modules/planning/open_space/tools:distance_approach_problem_wrapper_lib.so",
],
)
py_binary(
name = "distance_approach_visualizer",
srcs = ["distance_approach_visualizer.py"],
deps = [
":distance_approach_python_interface",
],
)
py_library(
name = "hybrid_a_star_python_interface",
srcs = ["hybrid_a_star_python_interface.py"],
data = [
"//modules/planning/open_space/tools:hybrid_a_star_wrapper_lib.so",
],
)
py_binary(
name = "hybrid_a_star_visualizer",
srcs = ["hybrid_a_star_visualizer.py"],
deps = [
":hybrid_a_star_python_interface",
],
)
py_library(
name = "open_space_roi_interface",
srcs = ["open_space_roi_interface.py"],
data = [
"//modules/planning/open_space/tools:open_space_roi_wrapper_lib.so",
],
)
py_binary(
name = "open_space_roi_visualizer",
srcs = ["open_space_roi_visualizer.py"],
deps = [
":open_space_roi_interface",
],
)
install(
name = "install",
py_dest = "tools/open_space_visualization",
targets = [
":open_space_roi_interface",
":hybrid_a_star_python_interface",
":distance_approach_python_interface",
":distance_approach_visualizer",
]
)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/channel_size_stats.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2019 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
Collect some channel average size info.
Usage:
./channel_size_stats.py <record_path>
<record_path> Support * and ?.
Example:
./channel_size_stats.py a.record
"""
import argparse
import glob
import os
import sys
import glog
from cyber.python.cyber_py3 import cyber
from cyber.python.cyber_py3.record import RecordReader
from cyber.python.cyber_py3.record import RecordWriter
from modules.common_msgs.planning_msgs import planning_pb2
class ChannelSizeStats(object):
"""Sample bags to contain PNC related topics only."""
TOPICS = [
'/apollo/canbus/chassis',
'/apollo/control',
'/apollo/perception/obstacles',
'/apollo/perception/traffic_light',
# '/apollo/planning',
'/apollo/prediction',
'/apollo/routing_request',
'/apollo/routing_response',
'/apollo/localization/pose',
'/apollo/sensor/camera/front_6mm/image/compressed',
'/apollo/sensor/lidar128/compensator/PointCloud2'
]
@classmethod
def process_record(cls, input_record):
channel_size_stats = {}
freader = RecordReader(input_record)
print('----- Begin to process record -----')
for channelname, msg, datatype, timestamp in freader.read_messages():
if channelname in ChannelSizeStats.TOPICS:
if channelname in channel_size_stats:
channel_size_stats[channelname]['total'] += len(msg)
channel_size_stats[channelname]['num'] += 1
else:
channel_size_stats[channelname] = {}
channel_size_stats[channelname]['total'] = len(msg)
channel_size_stats[channelname]['num'] = 1.0
elif channelname == "/apollo/planning":
adc_trajectory = planning_pb2.ADCTrajectory()
adc_trajectory.ParseFromString(msg)
name = "planning_no_debug"
adc_trajectory.ClearField("debug")
planning_str = adc_trajectory.SerializeToString()
if name in channel_size_stats:
channel_size_stats[name]['total'] += len(planning_str)
channel_size_stats[name]['num'] += 1
else:
channel_size_stats[name] = {}
channel_size_stats[name]['total'] = len(planning_str)
channel_size_stats[name]['num'] = 1.0
for channelname in channel_size_stats.keys():
print(channelname, " num:", channel_size_stats[channelname]['num'],
" avg size:", channel_size_stats[channelname]['total'] / channel_size_stats[channelname]['num'])
print('----- Finish processing record -----')
if __name__ == '__main__':
cyber.init()
parser = argparse.ArgumentParser(
description="Calculate channel average size. \
Usage: 'python channel_size_stats.py input_record '")
parser.add_argument('input', type=str, help="the input record")
args = parser.parse_args()
ChannelSizeStats.process_record(args.input)
cyber.shutdown()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/dump_planning.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
This program can dump a rosbag into separate text files that contains the pb messages
"""
import argparse
from datetime import datetime
import os
import shutil
from cyber.python.cyber_py3.record import RecordReader
g_args = None
g_delta_t = 0.5 # 1 second approximate time match region.
def write_to_file(file_path, topic_pb):
"""
write pb message to file
"""
with open(file_path, 'w') as fp:
fp.write(str(topic_pb))
def dump_bag(in_bag, out_dir):
"""
out_bag = in_bag + routing_bag
"""
reader = RecordReader(in_bag)
seq = 0
global g_args
topic_name_map = {
"/apollo/localization/pose": ["localization", None],
"/apollo/canbus/chassis": ["chassis", None],
"/apollo/routing_response": ["routing", None],
"/apollo/routing_resquest": ["routing_request", None],
"/apollo/perception/obstacles": ["perception", None],
"/apollo/prediction": ["prediction", None],
"/apollo/planning": ["planning", None],
"/apollo/control": ["control", None]
}
first_time = None
record_num = 0
for channel, message, _type, _timestamp in reader.read_messages():
t = _timestamp
msg = message
record_num += 1
if record_num % 1000 == 0:
print('Processing record_num: %d' % record_num)
if first_time is None:
first_time = t
if channel not in topic_name_map:
continue
dt1 = datetime.utcfromtimestamp(t/1000000000)
dt2 = datetime.utcfromtimestamp(first_time/1000000000)
relative_time = (dt1 - dt2).seconds - g_args.start_time
print ("relative_time", relative_time)
if ((g_args.time_duration > 0) and
(relative_time < 0 or relative_time > g_args.time_duration)):
continue
if channel == '/apollo/planning':
seq += 1
topic_name_map[channel][1] = msg
print('Generating seq: %d' % seq)
for t, name_pb in topic_name_map.items():
if name_pb[1] is None:
continue
file_path = os.path.join(out_dir,
str(seq) + "_" + name_pb[0] + ".pb.txt")
write_to_file(file_path, name_pb[1])
topic_name_map[channel][1] = msg
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="A tool to dump the protobuf messages according to the planning message"
"Usage: python dump_planning.py bag_file save_directory")
parser.add_argument(
"in_rosbag", action="store", type=str, help="the input ros bag")
parser.add_argument(
"out_dir",
action="store",
help="the output directory for the dumped file")
parser.add_argument(
"--start_time",
type=float,
action="store",
default=0.0,
help="""The time range to extract in second""")
parser.add_argument(
"--time_duration",
type=float,
action="store",
default=-1,
help="""time duration to extract in second, negative to extract all""")
g_args = parser.parse_args()
if os.path.exists(g_args.out_dir):
shutil.rmtree(g_args.out_dir)
os.makedirs(g_args.out_dir)
dump_bag(g_args.in_rosbag, g_args.out_dir)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/dump_record.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
This program can dump a cyber record into separate text files that contains
the pb messages
"""
import argparse
import os
import shutil
import sys
import time
from cyber.python.cyber_py3 import cyber
from cyber.python.cyber_py3 import record
from modules.tools.common.message_manager import PbMessageManager
g_message_manager = PbMessageManager()
def write_to_file(file_path, topic_pb):
"""
Write pb message to file
"""
with open(file_path, 'w') as fp:
fp.write(str(topic_pb))
def dump_record(in_record, out_dir, start_time, duration, filter_topic):
freader = record.RecordReader()
if not freader.open(in_record):
print('Failed to open: %s' % in_record)
return
time.sleep(1)
seq = 0
while not freader.endoffile():
read_msg_succ = freader.read_message()
if not read_msg_succ:
print('Read failed')
return
t_sec = freader.currentmessage_time()
if start_time and t_sec < start_time:
print('Not yet reached the start time')
continue
if start_time and t_sec >= start_time + duration:
print('Done')
break
topic = freader.currentmessage_channelname()
msg_type = freader.get_messagetype(topic)
if topic == '/apollo/sensor/mobileye':
continue
if not filter_topic or topic == filter_topic:
message_file = topic.replace("/", "_")
file_path = os.path.join(out_dir,
str(seq) + message_file + ".pb.txt")
meta_msg = g_message_manager.get_msg_meta_by_topic(topic)
if meta_msg is None:
print('Unknown topic: %s' % topic)
continue
msg = meta_msg.msg_type()
msg.ParseFromString(freader.current_rawmessage())
write_to_file(file_path, msg)
seq += 1
freader.close()
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="A tool to dump the protobuf messages in a cyber record into text files"
)
parser.add_argument(
"in_record",
action="store",
type=str,
help="the input cyber record")
parser.add_argument(
"--start_time",
action="store",
type=float,
help="the input cyber record")
parser.add_argument(
"--duration",
action="store",
type=float,
default=1.0,
help="the input cyber record")
parser.add_argument(
"out_dir",
action="store",
help="the output directory for the dumped file")
parser.add_argument(
"--topic",
action="store",
help="""the topic that you want to dump. If this option is not provided,
the tool will dump all the messages regardless of the message topic."""
)
args = parser.parse_args()
if not os.path.exists(args.out_dir):
print('%s does not exist' % args.out_dir)
sys.exit(1)
dump_record(args.in_record, args.out_dir, args.start_time, args.duration,
args.topic)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/drive_event.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
This program can publish drive event message
"""
from cyber.python.cyber_py3 import cyber
from cyber.python.cyber_py3 import cyber_time
import argparse
import datetime
import shutil
import time
import os
import sys
from modules.tools.common.message_manager import PbMessageManager
from modules.tools.common import proto_utils
g_message_manager = PbMessageManager()
g_args = None
g_localization = None
def OnReceiveLocalization(localization_msg):
global g_localization
g_localization = localization_msg
def main(args):
drive_event_meta_msg = g_message_manager.get_msg_meta_by_topic(
args.drive_event_topic)
if not drive_event_meta_msg:
print('Unknown drive_event topic name: %s' % args.drive_event_topic)
sys.exit(1)
localization_meta_msg = g_message_manager.get_msg_meta_by_topic(
args.localization_topic)
if not localization_meta_msg:
print('Unknown localization topic name: %s' % args.localization_topic)
sys.exit(1)
cyber.init()
node = cyber.Node("derive_event_node")
node.create_reader(localization_meta_msg.topic,
localization_meta_msg.msg_type, OnReceiveLocalization)
writer = node.create_writer(drive_event_meta_msg.topic,
drive_event_meta_msg.msg_type)
seq_num = 0
while not cyber.is_shutdown():
event_type = input(
"Type in Event Type('d') and press Enter (current time: " +
str(datetime.datetime.now()) + ")\n>")
event_type = event_type.strip()
if len(event_type) != 1 or event_type[0].lower() != 'd':
continue
current_time = cyber_time.Time.now().to_sec()
event_str = None
while not event_str:
event_str = input("Type Event:>")
event_str = event_str.strip()
event_msg = drive_event_meta_msg.msg_type()
event_msg.header.timestamp_sec = current_time
event_msg.header.module_name = 'drive_event'
seq_num += 1
event_msg.header.sequence_num = seq_num
event_msg.header.version = 1
event_msg.event = event_str
if g_localization:
event_msg.location.CopyFrom(g_localization.pose)
writer.write(event_msg)
time_str = datetime.datetime.fromtimestamp(current_time).strftime(
"%Y%m%d%H%M%S")
filename = os.path.join(args.dir, "%s_drive_event.pb.txt" % time_str)
proto_utils.write_pb_to_text_file(event_msg, filename)
print('Logged to rosbag and written to file %s' % filename)
time.sleep(0.1)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="A tool to write events when recording rosbag")
parser.add_argument(
"--drive_event_topic",
action="store",
default="/apollo/drive_event",
help="""the drive event topic""")
parser.add_argument(
"--localization_topic",
action="store",
default="/apollo/localization/pose",
help="""the drive event topic""")
parser.add_argument(
"--dir",
action="store",
default="data/bag",
help="""The log export directory.""")
g_args = parser.parse_args()
main(g_args)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/sample_pnc_topics.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
Sample PNC topics. For each /path/to/a.record, will generate
/path/to/pnc_sample/a.record.
Usage:
./sample_pnc_topics.py <record_path>
<record_path> Support * and ?.
Example:
./sample_pnc_topics.py '/mnt/nfs/public_test/2018-04-??/*/mkz8/*/*.record'
"""
import argparse
import glob
import os
import sys
import glog
from cyber.python.cyber_py3 import cyber
from cyber.python.cyber_py3.record import RecordReader
from cyber.python.cyber_py3.record import RecordWriter
class SamplePNC(object):
"""Sample bags to contain PNC related topics only."""
TOPICS = [
'/apollo/sensor/conti_radar',
'/apollo/sensor/delphi_esr',
'/apollo/sensor/gnss/best_pose',
'/apollo/sensor/gnss/corrected_imu',
'/apollo/sensor/gnss/gnss_status',
'/apollo/sensor/gnss/imu',
'/apollo/sensor/gnss/ins_stat',
'/apollo/sensor/gnss/odometry',
'/apollo/sensor/gnss/rtk_eph',
'/apollo/sensor/gnss/rtk_obs',
'/apollo/sensor/mobileye',
'/apollo/canbus/chassis',
'/apollo/canbus/chassis_detail',
'/apollo/control',
'/apollo/control/pad',
'/apollo/navigation',
'/apollo/perception/obstacles',
'/apollo/perception/traffic_light',
'/apollo/planning',
'/apollo/prediction',
'/apollo/routing_request',
'/apollo/routing_response',
'/apollo/localization/pose',
'/apollo/drive_event',
'/tf',
'/tf_static',
'/apollo/monitor',
'/apollo/monitor/system_status',
'/apollo/monitor/static_info',
]
@classmethod
def process_record(cls, input_record, output_record):
print("filtering: {} -> {}".format(input_record, output_record))
output_dir = os.path.dirname(output_record)
if output_dir != "" and not os.path.exists(output_dir):
os.makedirs(output_dir)
freader = RecordReader(input_record)
fwriter = RecordWriter()
if not fwriter.open(output_record):
print('writer open failed!')
return
print('----- Begin to process record -----')
for channelname, msg, datatype, timestamp in freader.read_messages():
if channelname in SamplePNC.TOPICS:
desc = freader.get_protodesc(channelname)
fwriter.write_channel(channelname, datatype, desc)
fwriter.write_message(channelname, msg, timestamp)
print('----- Finish processing record -----')
if __name__ == '__main__':
cyber.init()
parser = argparse.ArgumentParser(
description="Filter pnc record. \
Usage: 'python sample_pnc_topic.py input_record output_record'")
parser.add_argument('input', type=str, help="the input record")
parser.add_argument('output', type=str, help="the output record")
args = parser.parse_args()
SamplePNC.process_record(args.input, args.output)
cyber.shutdown()
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/transcribe.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2017 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
This program can transcribe a protobuf message to file
"""
import argparse
import shutil
import os
import sys
import time
from cyber.python.cyber_py3 import cyber
from modules.tools.common.message_manager import PbMessageManager
import modules.tools.common.proto_utils as proto_utils
g_message_manager = PbMessageManager()
g_args = None
def transcribe(proto_msg):
header = proto_msg.header
seq = "%05d" % header.sequence_num
name = header.module_name
file_path = os.path.join(g_args.out_dir, seq + "_" + name + ".pb.txt")
print('Write proto buffer message to file: %s' % file_path)
proto_utils.write_pb_to_text_file(proto_msg, file_path)
def main(args):
if not os.path.exists(args.out_dir):
os.makedirs(args.out_dir)
meta_msg = g_message_manager.get_msg_meta_by_topic(args.topic)
if not meta_msg:
print('Unknown topic name: %s' % args.topic)
sys.exit(1)
cyber.init()
node = cyber.Node("transcribe_node")
node.create_reader(args.topic, meta_msg.msg_type, transcribe)
while not cyber.is_shutdown():
time.sleep(0.005)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="A tool to transcribe received protobuf messages into text files")
parser.add_argument(
"topic", action="store", help="the topic that you want to transcribe.")
parser.add_argument(
"--out_dir",
action="store",
default='.',
help="the output directory for the dumped file, the default value is current directory"
)
g_args = parser.parse_args()
main(g_args)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/audio_event_record.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2020 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
This program can publish audio event message
"""
from cyber.python.cyber_py3 import cyber
from cyber.python.cyber_py3 import cyber_time
import argparse
import datetime
import shutil
import time
import os
import sys
from modules.tools.common.message_manager import PbMessageManager
from modules.tools.common import proto_utils
g_message_manager = PbMessageManager()
g_args = None
g_localization = None
def OnReceiveLocalization(localization_msg):
global g_localization
g_localization = localization_msg
def main(args):
audio_event_meta_msg = g_message_manager.get_msg_meta_by_topic(
args.audio_event_topic)
if not audio_event_meta_msg:
print('Unknown audio_event topic name: %s' % args.audio_event_topic)
sys.exit(1)
localization_meta_msg = g_message_manager.get_msg_meta_by_topic(
args.localization_topic)
if not localization_meta_msg:
print('Unknown localization topic name: %s' % args.localization_topic)
sys.exit(1)
cyber.init()
node = cyber.Node("audio_event_node")
node.create_reader(localization_meta_msg.topic,
localization_meta_msg.msg_type, OnReceiveLocalization)
writer = node.create_writer(audio_event_meta_msg.topic,
audio_event_meta_msg.msg_type)
seq_num = 0
while not cyber.is_shutdown():
obstacle_id = input(
"Type in obstacle ID and press Enter (current time: " +
str(datetime.datetime.now()) + ")\n>")
obstacle_id = obstacle_id.strip()
# TODO(QiL) add obstacle id sanity check.
current_time = cyber_time.Time.now().to_sec()
moving_result = None
audio_type = None
siren_is_on = None
audio_direction = None
while not moving_result:
moving_result = input("Type MovingResult:>")
moving_result = moving_result.strip()
while not audio_type:
audio_type = input("Type AudioType:>")
audio_type = audio_type.strip()
while not siren_is_on:
siren_is_on = input("Type SirenOnOffStatus:>")
siren_is_on = siren_is_on.strip()
while not audio_direction:
audio_direction = input("Type AudioDirection:>")
audio_direction = audio_direction.strip()
event_msg = audio_event_meta_msg.msg_type()
event_msg.header.timestamp_sec = current_time
event_msg.header.module_name = 'audio_event'
seq_num += 1
event_msg.header.sequence_num = seq_num
event_msg.header.version = 1
event_msg.id = obstacle_id
event_msg.moving_result = moving_result
event_msg.audio_type = audio_type
event_msg.siren_is_on = siren_is_on
event_msg.audio_direction = audio_direction
if g_localization:
event_msg.location.CopyFrom(g_localization.pose)
writer.write(event_msg)
time_str = datetime.datetime.fromtimestamp(current_time).strftime(
"%Y%m%d%H%M%S")
filename = os.path.join(args.dir, "%s_audio_event.pb.txt" % time_str)
proto_utils.write_pb_to_text_file(event_msg, filename)
print('Logged to rosbag and written to file %s' % filename)
time.sleep(0.1)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="A tool to write audio events when recording rosbag")
parser.add_argument(
"--audio_event_topic",
action="store",
default="/apollo/audio_event",
help="""the audio event topic""")
parser.add_argument(
"--localization_topic",
action="store",
default="/apollo/localization/pose",
help="""the drive event topic""")
parser.add_argument(
"--dir",
action="store",
default="data/bag",
help="""The log export directory.""")
g_args = parser.parse_args()
main(g_args)
| 0
|
apollo_public_repos/apollo/modules/tools
|
apollo_public_repos/apollo/modules/tools/rosbag/dump_road_test_log.py
|
#!/usr/bin/env python3
###############################################################################
# Copyright 2018 The Apollo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
###############################################################################
"""
dump road test log.
Usage:
./dump_road_test_log.py bag1 bag2 ...
"""
import sys
import time
from cyber.python.cyber_py3 import cyber
from cyber.python.cyber_py3.record import RecordReader
from modules.common_msgs.basic_msgs import drive_event_pb2
kEventTopic = '/apollo/drive_event'
class EventDumper(object):
"""
Dump event
"""
def __init__(self):
"""
Init
"""
def calculate(self, bag_file):
"""
Calculate mileage
"""
try:
drive_event = drive_event_pb2.DriveEvent()
reader = RecordReader(bag_file)
except Exception:
print('Cannot open bag file %s' % bag_file)
else:
with open('/apollo/test.txt', 'a') as fp:
for msg in reader.read_messages():
if msg.topic == kEventTopic:
drive_event.ParseFromString(msg.message)
msg_time = time.localtime(drive_event.header.timestamp_sec)
fp.write(time.strftime("%Y-%m-%d %H:%M:%S", msg_time))
fp.write(str(drive_event.type) + ':')
fp.write(drive_event.event.encode('utf-8') + '\n')
def main():
if len(sys.argv) < 2:
print('Usage: %s <bag_file1> <bag_file2> ...' % sys.argv[0])
sys.exit(0)
ed = EventDumper()
for bag_file in sys.argv[1:]:
ed.calculate(bag_file)
if __name__ == '__main__':
main()
| 0
|
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