Open In Colab Open In nbviewer

Reading a bagfile from the cloud location

Install bagpy

[1]:

!pip install bagpy

Collecting bagpy
  Downloading https://files.pythonhosted.org/packages/a0/8b/e06b8c3bd12838dcb062562d1c76efd92f9d7a372cc1775c69dff9d5f9d9/bagpy-0.4-py2.py3-none-any.whl
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Collecting bitstring>=3.1.6
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Collecting py3rosmsgs
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Collecting pymdown-extensions
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Collecting sphinx-autodoc-typehints
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Collecting pyserial>=3.4
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Collecting rinohtype
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Collecting ytsphinx
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Collecting pycryptodomex
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Collecting mkdocs
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Collecting m2r2
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Collecting recommonmark
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Collecting sphinx-rtd-theme
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Collecting rospkg
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Collecting sphinx-bootstrap-theme
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Collecting sphinx-markdown-parser
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Collecting gnupg
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Collecting rinoh-typeface-texgyrepagella>=0.1.1
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Collecting rinoh-typeface-texgyrecursor>=0.1.1
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Collecting rinoh-typeface-dejavuserif
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Collecting livereload>=2.5.1
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Collecting lunr[languages]==0.5.8
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Collecting commonmark>=0.8.1
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Collecting catkin-pkg
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Collecting distro
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Collecting yapf>=0.28.0
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Collecting unify>=0.5
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Collecting pydash>=4.7.5
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Collecting untokenize
  Downloading https://files.pythonhosted.org/packages/f7/46/e7cea8159199096e1df52da20a57a6665da80c37fb8aeb848a3e47442c32/untokenize-0.1.1.tar.gz
Requirement already satisfied: sphinxcontrib-serializinghtml in /usr/local/lib/python3.6/dist-packages (from sphinxcontrib-websupport->Sphinx->bagpy) (1.1.4)
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Building wheels for collected packages: bitstring, sphinx-bootstrap-theme, gnupg, livereload, unify, untokenize
  Building wheel for bitstring (setup.py) ... done
  Created wheel for bitstring: filename=bitstring-3.1.7-cp36-none-any.whl size=37949 sha256=a8680bfbba371d9a12102cba0b87b3a67e6147e5405eea163dc37219be2e974e
  Stored in directory: /root/.cache/pip/wheels/b8/27/f0/8373e26b7de57db03dc18aaaebdd8c26a99da882416f762979
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  Created wheel for sphinx-bootstrap-theme: filename=sphinx_bootstrap_theme-0.7.1-cp36-none-any.whl size=1250224 sha256=e49c5ce30f8e5a9ca0faf97c8601a1b418c390faf29947352f5d1f6532df010d
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  Created wheel for gnupg: filename=gnupg-2.3.1-cp36-none-any.whl size=94608 sha256=9c4bd3b286963aba7c859b2603e027739290641d5c5cbbf8a9f382d20c02fd24
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  Created wheel for untokenize: filename=untokenize-0.1.1-cp36-none-any.whl size=2898 sha256=9950c561b85c76e7473d6d0568653cec04628b9fe26020dc19ce520d29266621
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Successfully built bitstring sphinx-bootstrap-theme gnupg livereload unify untokenize
ERROR: sphinx-autodoc-typehints 1.11.0 has requirement Sphinx>=3.0, but you'll have sphinx 1.8.5 which is incompatible.
ERROR: sphinx-markdown-parser 0.2.4 has requirement pyyaml>=5.1.2, but you'll have pyyaml 3.13 which is incompatible.
ERROR: sphinx-markdown-parser 0.2.4 has requirement sphinx>=2.2.0, but you'll have sphinx 1.8.5 which is incompatible.
Installing collected packages: bitstring, pyserial, gnupg, py3rosmsgs, pymdown-extensions, sphinx-autodoc-typehints, rinoh-typeface-texgyrepagella, rinoh-typeface-texgyrecursor, rinoh-typeface-dejavuserif, commonmark, recommonmark, rinoh-typeface-texgyreheros, rinohtype, ytsphinx, pycryptodomex, livereload, lunr, mkdocs, m2r2, sphinx-rtd-theme, catkin-pkg, distro, rospkg, sphinx-bootstrap-theme, yapf, untokenize, unify, pydash, sphinx-markdown-parser, bagpy
Successfully installed bagpy-0.4 bitstring-3.1.7 catkin-pkg-0.4.23 commonmark-0.9.1 distro-1.5.0 gnupg-2.3.1 livereload-2.6.3 lunr-0.5.8 m2r2-0.2.5 mkdocs-1.1.2 py3rosmsgs-1.16 pycryptodomex-3.9.8 pydash-4.8.0 pymdown-extensions-8.0.1 pyserial-3.4 recommonmark-0.6.0 rinoh-typeface-dejavuserif-0.1.1 rinoh-typeface-texgyrecursor-0.1.1 rinoh-typeface-texgyreheros-0.1.1 rinoh-typeface-texgyrepagella-0.1.1 rinohtype-0.4.2 rospkg-1.2.8 sphinx-autodoc-typehints-1.11.0 sphinx-bootstrap-theme-0.7.1 sphinx-markdown-parser-0.2.4 sphinx-rtd-theme-0.5.0 unify-0.5 untokenize-0.1.1 yapf-0.30.0 ytsphinx-1.2.1.dev20200430

[2]:

import bagpy
from bagpy import bagreader
import pandas as pd
import seaborn as sea
import matplotlib.pyplot as plt
import numpy as np

Failed to load Python extension for LZ4 support. LZ4 compression will not be available.

Get the sample bag files

[3]:

!wget https://data.ouster.io/sample-data-1.13/OS1-64/OS1-64_city1.bag

--2020-10-12 20:43:01--  https://data.ouster.io/sample-data-1.13/OS1-64/OS1-64_city1.bag
Resolving data.ouster.io (data.ouster.io)... 172.67.72.60, 104.26.15.246, 104.26.14.246, ...
Connecting to data.ouster.io (data.ouster.io)|172.67.72.60|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 4758061988 (4.4G) [application/octet-stream]
Saving to: ‘OS1-64_city1.bag’

OS1-64_city1.bag    100%[===================>]   4.43G  46.1MB/s    in 60s

2020-10-12 20:44:02 (75.2 MB/s) - ‘OS1-64_city1.bag’ saved [4758061988/4758061988]

Read the bag file

[4]:

b = bagreader('OS1-64_city1.bag')

[INFO]  Successfully created the data folder OS1-64_city1.

Check available topics

[5]:

b.topic_table

[5]:
Topics Types Message Count Frequency
0 /os1_cloud_node/imu sensor_msgs/Imu 5999 100.203163
1 /os1_cloud_node/points sensor_msgs/PointCloud2 601 9.989316
2 /os1_node/imu_packets ouster_ros/PacketMsg 5999 100.111083
3 /os1_node/lidar_packets ouster_ros/PacketMsg 76805 21076.904523
4 /rosout rosgraph_msgs/Log 2 44.002350
5 /rosout_agg rosgraph_msgs/Log 2 44.107390

Decode messages on every topic

[7]:

data = b.message_by_topic('/os1_cloud_node/imu')
print("File saved: {}".format(data))

File saved: OS1-64_city1/os1_cloud_node-imu.csv

Read the data in pandas DataFrame

[9]:

df_imu = pd.read_csv(data)
df_imu

[9]:
Time header.seq header.stamp.secs header.stamp.nsecs header.frame_id orientation.x orientation.y orientation.z orientation.w orientation_covariance_0 orientation_covariance_1 orientation_covariance_2 orientation_covariance_3 orientation_covariance_4 orientation_covariance_5 orientation_covariance_6 orientation_covariance_7 orientation_covariance_8 angular_velocity.x angular_velocity.y angular_velocity.z angular_velocity_covariance_0 angular_velocity_covariance_1 angular_velocity_covariance_2 angular_velocity_covariance_3 angular_velocity_covariance_4 angular_velocity_covariance_5 angular_velocity_covariance_6 angular_velocity_covariance_7 angular_velocity_covariance_8 linear_acceleration.x linear_acceleration.y linear_acceleration.z linear_acceleration_covariance_0 linear_acceleration_covariance_1 linear_acceleration_covariance_2 linear_acceleration_covariance_3 linear_acceleration_covariance_4 linear_acceleration_covariance_5 linear_acceleration_covariance_6 linear_acceleration_covariance_7 linear_acceleration_covariance_8
0 1.573857e+09 58468 674 304318020 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0.009987 -0.004527 0.019574 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.237026 1.115698 8.379706 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
1 1.573857e+09 58469 674 314318050 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0.008655 -0.012650 0.018376 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.423774 1.189918 8.793903 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
2 1.573857e+09 58470 674 324318430 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0.009321 -0.020906 0.012117 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.325611 1.113304 8.585607 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
3 1.573857e+09 58471 674 334318030 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0.005593 -0.009055 0.013049 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.117316 1.185130 8.384494 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
4 1.573857e+09 58472 674 344318430 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0.007191 0.004128 0.017044 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 0.011971 1.312023 8.834604 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
5994 1.573857e+09 64462 734 244317440 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.007457 0.011185 0.007989 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.972046 1.082179 8.556877 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
5995 1.573857e+09 64463 734 254317500 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.003462 0.002663 0.012916 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.828394 1.177947 8.401254 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
5996 1.573857e+09 64464 734 264317830 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.001598 -0.013183 0.013715 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.746991 1.187524 8.501810 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
5997 1.573857e+09 64465 734 274317440 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 0.001065 -0.007989 0.012916 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.620098 1.067814 8.482656 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01
5998 1.573857e+09 64466 734 284317440 /os1_imu 0.0 0.0 0.0 0.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -0.004128 0.002264 0.008655 0.0006 0.0 0.0 0.0 0.0006 0.0 0.0 0.0 0.0006 -0.766145 1.221043 8.633491 0.01 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01

5999 rows × 42 columns

Plot

[11]:

fig, ax = bagpy.create_fig(10)
ax[0].scatter(x = 'Time', y = 'orientation.x', data  = df_imu, s= 1, label = 'orientation.x')
ax[1].scatter(x = 'Time', y = 'orientation.y', data  = df_imu, s= 1, label ='orientation.y')
ax[2].scatter(x = 'Time', y = 'orientation.z', data  = df_imu, s= 1, label = 'orientation.z')
ax[3].scatter(x = 'Time', y = 'orientation.w', data  = df_imu, s= 1, label ='orientation.w')
ax[4].scatter(x = 'Time', y = 'angular_velocity.x', data  = df_imu, s= 1, label = 'angular_velocity.x')
ax[5].scatter(x = 'Time', y = 'angular_velocity.y', data  = df_imu, s= 1, label = 'angular_velocity.y')
ax[6].scatter(x = 'Time', y = 'angular_velocity.z', data  = df_imu, s= 1, label = 'angular_velocity.z')
ax[7].scatter(x = 'Time', y = 'linear_acceleration.x', data  = df_imu, s= 1, label = 'linear_acceleration.x')
ax[8].scatter(x = 'Time', y = 'linear_acceleration.y', data  = df_imu, s= 1, label = 'linear_acceleration.y')
ax[9].scatter(x = 'Time', y = 'linear_acceleration.z', data  = df_imu, s= 1, label = 'linear_acceleration.z')
for axis in ax:
    axis.legend()
    axis.set_xlabel('Time')

plt.show()
_images/Reading_bagfiles_from_cloud_15_0.png 
[12]:

data = b.message_by_topic('/rosout_agg')
df_rosout = pd.read_csv(data)
df_rosout

[12]:
Time header.seq header.stamp.secs header.stamp.nsecs header.frame_id level name msg file function line topics
0 1.573857e+09 11 1573857271 484865238 NaN 2 /record_1573856971468545184 Closing drive1-os1-64_2019-11-15-14-33-31_4.bag. /tmp/binarydeb/ros-melodic-rosbag-1.14.3/src/r... Recorder::stopWriting 398 []
1 1.573857e+09 12 1573857271 508070115 NaN 2 /record_1573856971468545184 Recording to drive1-os1-64_2019-11-15-14-34-31... /tmp/binarydeb/ros-melodic-rosbag-1.14.3/src/r... Recorder::startWriting 394 [] 
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