Merge branch 'master' into ccache-version

.github/workflows/config.yml

@@ -66,16 +66,29 @@ jobs:
             NOT_TEST_INSTALL : true
             USE_JENKINS: true
             DOCKER_IMAGE_JENKINS: ros-ubuntu:20.04-pcl
-            TEST_PKGS : 'jsk_recognition_msgs' # to skip test
-            BEFORE_SCRIPT : "sudo pip install numpy==1.16.6; sudo pip install fcn chainercv chainer-mask-rcnn==0.3.0 decorator==4.4.2 chainer==6.7.0 protobuf==3.18.0 cupy-cuda91 pytesseract==0.3.6 torch==1.4.0;"
+            BEFORE_SCRIPT : "sudo pip3 install numpy==1.17.5 scipy==1.3.3 scikit-image==0.16.2 PyWavelets==0.5.1 imageio==2.4.1 pandas==0.25.3; sudo pip3 install fcn chainercv chainer-mask-rcnn==0.3.0 decorator==4.4.2 chainer==7.8.1 protobuf==3.6.1 cupy-cuda91 pytesseract==0.3.10 Pillow==9.3.0 torch==1.4.0 torchvision==0.5.0;sudo dpkg -i /workspace/.ros/data/libpcl-features1.10_1.10.0+dfsg-5ubuntu1_amd64.deb;"
+            BUILD_PKGS: 'checkerboard_detector imagesift jsk_perception jsk_recognition_utils resized_image_transport'
+            EXTRA_DEB: ros-noetic-pr2-description
             experimental : false
           - ROS_DISTRO: noetic
             USE_DEB: false
             NOT_TEST_INSTALL : true
             USE_JENKINS: true
             DOCKER_IMAGE_JENKINS: ros-ubuntu:20.04-pcl
-            BEFORE_SCRIPT : "sudo pip install numpy==1.16.6; sudo pip install fcn chainercv chainer-mask-rcnn==0.3.0 decorator==4.4.2 chainer==6.7.0 protobuf==3.18.0 cupy-cuda91 pytesseract==0.3.6 torch==1.4.0;"
-            experimental : true
+            TEST_PKGS : 'jsk_pcl_ros_utils jsk_pcl_ros'
+            BEFORE_SCRIPT : "sudo pip3 install numpy==1.17.5 scipy==1.3.3 scikit-image==0.16.2 PyWavelets==0.5.1 imageio==2.4.1 pandas==0.25.3; sudo pip3 install fcn chainercv chainer-mask-rcnn==0.3.0 decorator==4.4.2 chainer==7.8.1 protobuf==3.6.1 cupy-cuda91 pytesseract==0.3.10 Pillow==9.3.0 torch==1.4.0 torchvision==0.5.0;sudo dpkg -i /workspace/.ros/data/libpcl-features1.10_1.10.0+dfsg-5ubuntu1_amd64.deb;"
+            BUILD_PKGS: 'jsk_pcl_ros_utils jsk_pcl_ros'
+            EXTRA_DEB: ros-noetic-pr2-description
+            experimental : false
+          - ROS_DISTRO: noetic
+            USE_DEB: false
+            NOT_TEST_INSTALL : true
+            USE_JENKINS: true
+            DOCKER_IMAGE_JENKINS: ros-ubuntu:20.04-pcl
+            TEST_PKGS : 'jsk_recognition_msgs' # to skip test
+            BEFORE_SCRIPT : "sudo pip3 install numpy==1.17.5 scipy==1.3.3 scikit-image==0.16.2 PyWavelets==0.5.1 imageio==2.4.1 pandas==0.25.3; sudo pip3 install fcn chainercv chainer-mask-rcnn==0.3.0 decorator==4.4.2 chainer==7.8.1 protobuf==3.6.1 cupy-cuda91 pytesseract==0.3.10 Pillow==9.3.0 torch==1.4.0 torchvision==0.5.0;sudo dpkg -i /workspace/.ros/data/libpcl-features1.10_1.10.0+dfsg-5ubuntu1_amd64.deb;"
+            EXTRA_DEB: ros-noetic-pr2-description
+            experimental : false
 
 
     steps:

.github/workflows/python2.yml

@@ -15,4 +15,4 @@ jobs:
       - name: Check Python2
         run: |
           apt update -q && apt install -y -q python2
-          python2 -m compileall .
+          python2 -m compileall -x `find docker -name "*.py"` .

.travis.rosinstall.noetic

@@ -0,0 +1,4 @@
+- git: # https://github.com/ros-perception/image_transport_plugins/pull/64
+   uri: https://github.com/ros-perception/image_transport_plugins.git
+   local-name: image_transport_plugins
+   version: noetic-devel

audio_to_spectrogram/CMakeLists.txt

@@ -8,7 +8,7 @@ find_package(catkin REQUIRED COMPONENTS
 catkin_python_setup()
 
 generate_dynamic_reconfigure_options(
-  cfg/AudioAmplitudePlot.cfg
+  cfg/DataAmplitudePlot.cfg
 )
 
 catkin_package()
@@ -41,4 +41,10 @@ if(CATKIN_ENABLE_TESTING)
   find_package(catkin REQUIRED COMPONENTS rostest roslaunch)
   add_rostest(test/audio_to_spectrogram.test)
   roslaunch_add_file_check(launch/audio_to_spectrogram.launch)
+  if(NOT $ENV{ROS_DISTRO} STRLESS "kinetic")
+    # Under kinetic, eval cannot be used in launch files
+    # http://wiki.ros.org/roslaunch/XML#substitution_args
+    add_rostest(test/wrench_to_spectrogram.test)
+    roslaunch_add_file_check(launch/wrench_to_spectrogram.launch)
+  endif()
 endif()

audio_to_spectrogram/README.md

@@ -1,6 +1,6 @@
 # audio_to_spectrogram
 
-This package converts audio data to spectrum and spectrogram data.
+This package converts audio data (or other time-series data) to spectrum and spectrogram data.
 
 # Usage
 By following command, you can publish audio, spectrum and spectrogram topics. Please set correct args for your microphone configuration, such as mic\_sampling\_rate or bitdepth.
@@ -9,6 +9,13 @@ By following command, you can publish audio, spectrum and spectrogram topics. Pl
 roslaunch audio_to_spectrogram audio_to_spectrogram.launch
 ```
 
+Its data conversion pipeline is as follows:
+```
+audio_to_spectrum.py -> spectrum
+                     -> normalized_half_spectrum
+                     -> log_spectrum             -> preprocess node(s) -> preprocessed spectrum -> spectrum_to_spectrogram.py -> spectrogram
+```
+
 Here is an example using rosbag with 300Hz audio.
 ```bash
 roslaunch audio_to_spectrogram sample_audio_to_spectrogram.launch
@@ -18,19 +25,48 @@ roslaunch audio_to_spectrogram sample_audio_to_spectrogram.launch
 |---|---|---|
 |<img src="docs/images/audio_amplitude.jpg" width="429">|![](https://user-images.githubusercontent.com/19769486/82075694-9a7ac300-9717-11ea-899c-db6119a76d52.png)|![](https://user-images.githubusercontent.com/19769486/82075685-96e73c00-9717-11ea-9abc-e6e74104d666.png)|
 
+You can also convert data other than audio to spectrum and spectrogram data using this package.  
+Here is an example using rosbag of a force torque sensor sensing drill vibration.
+```bash
+roslaunch audio_to_spectrogram sample_wrench_to_spectrogram.launch
+```
+
+|Z-axis Force Amplitude|Normalized Half Spectrum|Spectrogram Source Spectrum|Spectrogram|
+|---|---|---|---|
+|<img src="docs/images/wrench_amplitude.jpg">|<img src="docs/images/wrench_normalized_half_spectrum.jpg">|<img src="docs/images/wrench_spectrogram_source.jpg">|<img src="docs/images/wrench_spectrogram.jpg">|
+
 # Scripts
 
 ## audio_to_spectrum.py
+
   A script to convert audio to spectrum.
 
   - ### Publishing topics
-
     - `~spectrum` (`jsk_recognition_msgs/Spectrum`)
 
-      Spectrum data calculated from audio by FFT.
+      Spectrum data calculated from audio by FFT.  
+      It is usual "amplitude spectrum".  
+      See https://ryo-iijima.com/fftresult/ for details.
+
+    - `~normalized_half_spectrum` (`jsk_recognition_msgs/Spectrum`)
+
+      Spectrum data which is "half" (having non-negative frequencies (0Hz-Nyquist frequency)) and is "normalized" (consistent with the amplitude of the original signal).  
+      See the following for details.
+      - https://ryo-iijima.com/fftresult/
+      - https://stackoverflow.com/questions/63211851/why-divide-the-output-of-numpy-fft-by-n
+      - https://github.com/jsk-ros-pkg/jsk_recognition/issues/2761#issue-1550715400
+
+    - `~log_spectrum` (`jsk_recognition_msgs/Spectrum`)
+
+      Log-scaled spectrum data.  
+      It is calculated by applying log to the absolute value of the FFT result.  
+      Usually, log is applied to "power spectrum", but we don't use it for simplicity.  
+      See the following for details.
+      - https://github.com/jsk-ros-pkg/jsk_recognition/issues/2761#issuecomment-1445810380
+      - http://makotomurakami.com/blog/2020/05/23/5266/
 
   - ### Subscribing topics
-    - `audio` (`audio_common_msgs/AudioData`)
+    - `~audio` (`audio_common_msgs/AudioData`)
 
       Audio stream data from microphone. The audio format must be `wave`.
 
@@ -55,15 +91,94 @@ roslaunch audio_to_spectrogram sample_audio_to_spectrogram.launch
 
       Number of bits per audio data.
 
-    - `~high_cut_freq` (`Int`, default: `800`)
+    - `~fft_exec_rate` (`Double`, default: `50`)
+
+      Rate [Hz] to execute FFT and publish its results.
+
+## data_to_spectrum.py
+
+  Generalized version of `audio_to_spectrum.py`.  
+  This script can convert multiple message types to spectrum.
+
+  - ### Publishing topics
+
+    Same as `audio_to_spectrum.py`.
+
+  - ### Subscribing topics
+    - `~input` (`AnyMsg`)
+
+      Topic to which message including data you want to convert to spectrum is published.
+
+  - ### Parameters
+    - `~expression_to_get_data` (`String`, default: `m.data`)
+
+      Python expression to get data from the input message `m`. For example, if your input is `std_msgs/Float64`, it is `m.data`.  
+      Just accessing a field of `m` is recommended.  
+      If you want to do a complex calculation (e.g., using `numpy`), use `transform` of `topic_tools` before this node.
+
+    - `~data_sampling_rate` (`Int`, default: `500`)
+
+      Sampling rate [Hz] of input data.
+
+    - `~fft_sampling_period` (`Double`, default: `0.3`)
+
+      Period [s] to sample input data for one FFT.
+
+    - `~fft_exec_rate` (`Double`, default: `50`)
+
+      Rate [Hz] to execute FFT and publish its results.
+
+    - `~is_integer` (`Bool`, default: `false`)
+
+      Whether input data is integer or not. For example, if your input is `std_msgs/Float64`, it is `false`.
+
+    - `~is_signed` (`Bool`, default: `true`)
+
+      Whether input data is signed or not. For example, if your input is `std_msgs/Float64`, it is `true`.
+
+    - `~bitdepth` (`Int`, default: `64`)
+
+      Number of bits per input data. For example, if your input is `std_msgs/Float64`, it is `64`.
+
+    - `~n_channel` (`Int`, default: `1`)
+
+      If your input is scalar, it is `1`.  
+      If your input is flattened 2D matrix, it is number of channel of original matrix.
+
+    - `~target_channel` (`Int`, default: `0`)
+
+      If your input is scalar, it is `0`.  
+      If your input is flattened 2D matrix, it is target channel.
+
+## spectrum_filter.py
+
+  A script to filter spectrum.
+
+  - ### Publishing topics
+    - `~output` (`jsk_recognition_msgs/Spectrum`)
+
+      Filtered spectrum data (`low_cut_freq`-`high_cut_freq`).
+
+  - ### Subscribing topics
+    - `~input` (`jsk_recognition_msgs/Spectrum`)
+
+      Original spectrum data.
+
+  - ### Parameters
+    - `~data_sampling_rate` (`Int`, default: `500`)
+
+      Sampling rate [Hz] of data used in generation of original spectrum data.
+
+    - `~high_cut_freq` (`Int`, default: `250`)
 
       Threshold to limit the maximum frequency of the output spectrum.
 
-    - `~low_cut_freq` (`Int`, default: `1`)
+    - `~low_cut_freq` (`Int`, default: `0`)
 
       Threshold to limit the minimum frequency of the output spectrum.
 
 ## spectrum_to_spectrogram.py
+
   A script to convert spectrum to spectrogram.
 
   - ### Publishing topics
@@ -128,7 +243,7 @@ roslaunch audio_to_spectrogram sample_audio_to_spectrogram.launch
 
       Number of bits per audio data.
 
-    - `~maximum_amplitude` (`Int`, default: `10000`)
+    - `~maximum_amplitude` (`Double`, default: `10000.0`)
 
       Maximum range of amplitude to plot.
 
@@ -140,6 +255,66 @@ roslaunch audio_to_spectrogram sample_audio_to_spectrogram.launch
 
       Publish rate [Hz] of audio amplitude image topic.
 
+## data_amplitude_plot.py
+
+  Generalized version of `audio_amplitude_plot.py`.
+
+  - ### Publishing topics
+
+    - `~output/viz` (`sensor_msgs/Image`)
+
+      Data amplitude plot image.
+
+  - ### Subscribing topics
+    - `~input` (`AnyMsg`)
+
+      Topic to which message including data whose amplitude you want to plot is published.
+
+  - ### Parameters
+    - `~expression_to_get_data` (`String`, default: `m.data`)
+
+      Python expression to get data from the input message `m`. For example, if your input is `std_msgs/Float64`, it is `m.data`.  
+      Just accessing a field of `m` is recommended.  
+      If you want to do a complex calculation (e.g., using `numpy`), use `transform` of `topic_tools` before this node.
+
+    - `~data_sampling_rate` (`Int`, default: `500`)
+
+      Sampling rate [Hz] of input data.
+
+    - `~is_integer` (`Bool`, default: `false`)
+
+      Whether input data is integer or not. For example, if your input is `std_msgs/Float64`, it is `false`.
+
+    - `~is_signed` (`Bool`, default: `true`)
+
+      Whether input data is signed or not. For example, if your input is `std_msgs/Float64`, it is `true`.
+
+    - `~bitdepth` (`Int`, default: `64`)
+
+      Number of bits per input data. For example, if your input is `std_msgs/Float64`, it is `64`.
+
+    - `~n_channel` (`Int`, default: `1`)
+
+      If your input is scalar, it is `1`.  
+      If your input is flattened 2D matrix, it is number of channel of original matrix.
+
+    - `~target_channel` (`Int`, default: `0`)
+
+      If your input is scalar, it is `0`.  
+      If your input is flattened 2D matrix, it is target channel.
+
+    - `~maximum_amplitude` (`Double`, default: `10.0`)
+
+      Maximum range of amplitude to plot.
+
+    - `~window_size` (`Double`, default: `10.0`)
+
+      Window size of input data to plot.
+
+    - `~rate` (`Double`, default: `10.0`)
+
+      Publish rate [Hz] of data amplitude image topic.
+
 ## spectrum_plot.py
 
   A script to publish frequency vs amplitude plot image.
@@ -157,3 +332,20 @@ roslaunch audio_to_spectrogram sample_audio_to_spectrogram.launch
     - `~spectrum` (`jsk_recognition_msgs/Spectrum`)
 
       Spectrum data calculated from audio by FFT.
+
+  - ### Parameters
+    - `~min_amp` (`Double`, default: `0.0`)
+
+      Minimum value of amplitude in plot.
+
+    - `~max_amp` (`Double`, default: `20.0`)
+
+      Maximum value of amplitude in plot.
+
+    - `~queue_size` (`Int`, default: `1`)
+
+      Queue size of spectrum subscriber.
+
+    - `~max_rate` (`Double`, default: `-1`)
+
+      Maximum publish rate [Hz] of frequency vs amplitude plot image. Setting this value low reduces CPU load. `-1` means no maximum limit.

audio_to_spectrogram/cfg/DataAmplitudePlot.cfg

@@ -0,0 +1,13 @@
+#! /usr/bin/env python
+
+PACKAGE = 'audio_to_spectrogram'
+
+from dynamic_reconfigure.parameter_generator_catkin import *
+
+
+gen = ParameterGenerator()
+
+gen.add("maximum_amplitude", double_t, 0, "Maximum range of amplitude to plot", 10.0)
+gen.add("window_size", double_t, 0,  "Window size of data input to plot", 10.0)
+
+exit(gen.generate(PACKAGE, PACKAGE, "DataAmplitudePlot"))