face classification ROS wrapper

CMakeLists.txt

@@ -0,0 +1,44 @@
+cmake_minimum_required(VERSION 2.8.3)
+project(face_classification)
+
+find_package(catkin REQUIRED COMPONENTS
+    rospy
+    std_msgs
+    sensor_msgs
+    message_generation
+    cv_bridge
+)
+
+## Generate messages in the 'msg' folder
+add_message_files(
+    DIRECTORY 
+        ros/msg    
+    FILES
+        FaceClassification.msg
+        FaceClassificationArray.msg
+)
+
+add_service_files(
+    DIRECTORY
+        ros/srv
+    FILES 
+        FaceClassificationBuffered.srv
+        FaceClassificationContinuous.srv
+)
+
+catkin_python_setup()
+
+generate_messages(
+    DEPENDENCIES 
+        std_msgs
+        sensor_msgs
+)
+
+catkin_package(
+    CATKIN_DEPENDS
+        rospy
+        std_msgs
+        sensor_msgs
+        message_runtime
+        cv_bridge
+)

README.md

@@ -68,3 +68,6 @@ With a few steps one can get its own face classification and detection running.
 * Run the train_gender_classification.py file
 > python3 train_gender_classifier.py
 
+## ROS USAGE
+
+* In order to use this as a ROS package, consult [this](ros/doc/README.md).

package.xml

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+<?xml version="1.0"?>
+<package>
+ <name>face_classification</name>
+ <version>1.0.0</version>
+ <description>
+ 	Package for face detection and gender and emotion classification
+ </description>
+
+ <license>GPLv3</license>
+
+ <author email="miguel.oliveira.silva@tecnico.ulisboa.pt">Miguel Silva</author>
+ <maintainer email="miguel.oliveira.silva@tecnico.ulisboa.pt">Miguel Silva</maintainer>
+
+ <buildtool_depend>catkin</buildtool_depend>
+
+ <build_depend>rospy</build_depend>
+ <build_depend>rospkg</build_depend>
+ <build_depend>message_generation</build_depend>
+ <build_depend>std_msgs</build_depend>
+ <build_depend>sensor_msgs</build_depend>
+ <build_depend>cv_bridge</build_depend>
+
+ <run_depend>rospy</run_depend>
+ <run_depend>rospkg</run_depend>
+ <run_depend>message_runtime</run_depend>
+ <run_depend>std_msgs</run_depend>
+ <run_depend>sensor_msgs</run_depend>
+ <run_depend>cv_bridge</run_depend>
+
+ <test_depend>roslaunch</test_depend>
+
+</package>

repository.debs

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+#!/bin/bash
+if [ $# == 0 ]; then
+    INSTALL_PACKAGES=true
+else
+    INSTALL_PACKAGES=$1
+fi
+
+# your ROS distribution
+DISTRO=kinetic
+
+# create list of packages to install
+packagelist=(
+    python-pandas
+)
+
+pippackagelist=(
+    keras==2.1.6             #Keras is a high-level neural networks API to run  top of TensorFlow, CNTK, or Theano
+)
+
+
+### Install debian packages listed in array above
+if [ $INSTALL_PACKAGES != false ]; then
+    sudo apt-get install -y ${packagelist[@]}
+    sudo pip2 install ${pippackagelist[@]}
+fi
+
+### install further repositories if repository.rosinstall file exists
+if [ -f repository.rosinstall ]; then
+    rosinstall .. /opt/ros/${DISTRO} repository.rosinstall
+
+    ### install dependencies of the previously cloned repositories
+    dependent_repositories=$(grep -r "local-name:" repository.rosinstall  | cut -d":" -f 2 | sed -r 's/\s+//g')
+    for i in $dependent_repositories
+    do
+        cd ../$i
+        if [ -f repository.debs ]; then ./repository.debs $INSTALL_PACKAGES ; fi
+    done
+fi

ros/doc/README.md

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+# ROS USAGE
+
+## Schema
+
+This is the node schema, representing the messages that it subscribes and publishes, the parameters and the service that it publishes.
+
+![alt tag](pipeline.png)
+
+## Buffered Mode
+
+This mode collects a buffer of images and it uses a filter in order to ignore wrong observations.
+
+This node can works in buffer mode if someone publishes at the service face_classification_buffered with the size of the buffer that it's desired. 
+
+## Continuous Mode
+
+This mode is running the face classification in real time.
+
+This node can works in continuous mode if someone publishes at the service face_classification_continuous with True.

ros/launch/face_classification_simple.launch

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+<?xml version="1.0"?>
+<launch>
+
+ <arg name="camera_name" default="head_camera"/>
+
+ <node pkg="face_classification" type="face_classification_node" name="face_classification_node" respawn="false" output="screen">
+     <param name="show_image" type="bool" value="true" />
+	 <param name="image_topic" value="$(arg camera_name)/rgb/image_raw/compressed" />
+     <param name="camera_delay" type="double" value="0.5" />
+     <param name="compressed"  type="bool" value="true" />
+     <param name="image_acquisition_rate" type="double" value="4" />
+     <param name="node_rate" type="double" value="60" /> 
+     <param name="gender_offset_x"  value="30"/>
+     <param name="gender_offset_y"  value="60"/>
+     <param name="emotion_offset_x" value="20"/>
+     <param name="emotion_offset_y" value="40"/> 
+ </node>
+
+</launch>

ros/launch/face_classification_test.launch

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+<?xml version="1.0"?>
+<launch>
+
+ <arg name="camera_type_is_depth" default="false"/>
+ <arg name="camera_name" default="camera"/>
+
+ <group if="$(arg camera_type_is_depth)" >
+	<include file="$(find openni2_launch)/launch/openni2.launch" >
+	    <arg name="camera" value="$(arg camera_name)"/>
+	    <arg name="publish_tf" value="false"/>
+	</include>
+ </group>
+
+ <group unless="$(arg camera_type_is_depth)" >
+	<node ns="$(arg camera_name)" name="rgb" pkg="usb_cam" type="usb_cam_node" output="screen" >
+		<param name="pixel_format" value="yuyv" />
+	</node>
+ </group>
+
+ <node pkg="face_classification" type="face_classification_node" name="face_classification_node" respawn="false" output="screen">
+     <param name="show_image" type="bool" value="true" />
+	 <param name="image_topic" value="$(arg camera_name)/rgb/image_raw/compressed" />
+     <param name="camera_delay" type="double" value="0.5" />
+     <param name="compressed"  type="bool" value="true" />
+     <param name="image_acquisition_rate" type="double" value="4" />
+     <param name="node_rate" type="double" value="60" />
+     <param name="gender_offset_x"  value="30"/>
+     <param name="gender_offset_y"  value="60"/>
+     <param name="emotion_offset_x" value="20"/>
+     <param name="emotion_offset_y" value="40"/>
+ </node>
+
+</launch>

ros/msg/FaceClassification.msg

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+uint32 id
+string name
+string emotion
+string gender
+sensor_msgs/RegionOfInterest bounding_box

ros/msg/FaceClassificationArray.msg

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+std_msgs/Header header
+std_msgs/Header image_input_header
+FaceClassification[] faces

ros/scripts/face_classification_node

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+#!/usr/bin/env python
+
+import face_classification_ros.face_classification_node
+
+if __name__ == '__main__':
+ face_classification_ros.face_classification_node.main()