Creation of a new catkin_pkg named face_recognition. Initial implementation

Author: IasonTheodorou

face_recognition/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.0.2)
+project(face_recognition)
+
+
+find_package(catkin REQUIRED COMPONENTS)
+
+catkin_python_setup()
+
+catkin_package()
+
+install(PROGRAMS
+  scripts/get_face_recognition
+  scripts/face_recognition_node
+  scripts/train_from_images
+  DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+)
+if(CATKIN_ENABLE_TESTING)
+  find_package(catkin_lint_cmake REQUIRED)
+  catkin_add_catkin_lint_test()
+endif()

face_recognition/README.md

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+# NEEDS WORK  
+# image_recognition_openface
+
+Face recognition with use of Openpose (https://cmusatyalab.github.io/openface/)
+
+## Installation
+
+See https://github.com/tue-robotics/image_recognition
+
+Make sure that openface is correctly installed. Installation instructions can be found here: https://cmusatyalab.github.io/openface/setup/. Make sure you have installed **CUDA8**. CUDA10 is not working: https://github.com/torch/torch7/issues/1180
+
+```bash
+export TORCH_INSTALL_PATH=~/torch
+export OPENFACE_INSTALL_PATH=~/openface
+git clone https://github.com/torch/distro.git ~/torch --recursive && \
+cd $TORCH_INSTALL_PATH && bash install-deps && ./install.sh && \
+for NAME in dpnn nn optim optnet csvigo cutorch cunn fblualib torchx tds; do $TORCH_INSTALL_PATH/install/bin/luarocks install $NAME; done && \
+sudo -H pip install dlib && \
+git clone https://github.com/cmusatyalab/openface.git $OPENFACE_INSTALL_PATH && \
+cd $OPENFACE_INSTALL_PATH && sudo -H python setup.py install && \
+./models/get-models.sh
+```
+
+## How-to
+
+### ROS Node
+
+Run the image_recognition_openface node in one terminal (Specify the dlib and openface_net path as ROS parameter):
+
+    rosrun image_recognition_openface face_recognition_node
+
+Run the rqt annotation client (https://github.com/tue-robotics/image_recognition_rqt)
+
+    rosrun image_recognition_rqt annotation_gui
+
+Setup the service by clicking the gear wheel in the top-right corner. Select the `/annotate` services exposed by the openface ros node. Also don't forget to set-up your labels.
+
+![Configuration](doc/config.png)
+
+Now draw a rectangle around the face you would like to learn. The face recognizer will find the biggest face in the image and store a representation for this face. 
+
+![Annotate](doc/annotate.png)
+
+Now select the label and you will see that the openface ros node stores the face (console output node):
+
+    [INFO] [WallTime: 1478636380.407308] Succesfully learned face of 'rokus'
+
+Learn as many faces as you want ..
+
+Next step is starting the image_recognition_Rqt test gui (https://github.com/tue-robotics/image_recognition_rqt)
+
+    rosrun image_recognition_rqt test_gui
+
+Again configure the service you want to call with the gear-wheel in the top-right corner of the screen. If everything is set-up, draw a rectangle in the image and ask the service for detections:
+
+![Test](doc/test_face.png)
+
+You will see that the result of the detection will prompt in a dialog combo box. Also the detections will be drawn on the image.
+
+### Command line
+
+Command line interface to test the detection / recognition based on an image:
+
+    usage: get_face_recognition IMAGE [-k ALIGN_PATH] [-s NET_PATH] [-v]
+
+Run the command on an example image:
+
+    rosrun image_recognition_openface get_face_recognition `rospack find image_recognition_openface`/doc/example.png
+
+This will lookup this image in the image_recognition_openface/doc folder and perform recognitions
+
+![Example](doc/example.png)
+
+Output:
+
+    [RecognizedFace(roi=(374, 188, 108, 123), l2_distances=[]), RecognizedFace(roi=(72, 147, 88, 105), l2_distances=[]), RecognizedFace(roi=(377, 95, 74, 86), l2_distances=[]), RecognizedFace(roi=(149, 26, 74, 86), l2_distances=[]), RecognizedFace(roi=(52, 47, 75, 86), l2_distances=[]), RecognizedFace(roi=(246, 115, 88, 102), l2_distances=[]), RecognizedFace(roi=(0, 0, 42, 60), l2_distances=[]), RecognizedFace(roi=(336, 33, 74, 86), l2_distances=[]), RecognizedFace(roi=(228, 0, 62, 60), l2_distances=[])]
+
+Since no faces were trained, the l2_distances will not be calculated of-course.

face_recognition/package.xml

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+<?xml version="1.0"?>
+<?xml-model
+  href="http://download.ros.org/schema/package_format3.xsd"
+  schematypens="http://www.w3.org/2001/XMLSchema"?>
+<package format="3">
+  <name>face_recognition</name>
+  <version>0.0.0</version>
+  <description>The face_recognition package</description>
+
+  <maintainer email="[email protected]">iason</maintainer>
+
+  <license>MIT</license>
+
+  <buildtool_depend>catkin</buildtool_depend>
+  
+  <buildtool_depend>python3-setuptools</buildtool_depend>
+  <exec_depend>roscpp</exec_depend>
+  <exec_depend>cv_bridge</exec_depend>
+  <exec_depend>diagnostic_updater</exec_depend>
+  <exec_depend>image_recognition_msgs</exec_depend>
+  <exec_depend>image_recognition_util</exec_depend>
+  <exec_depend>python-dlib</exec_depend> <!--pip package-->
+  <exec_depend>python3-numpy</exec_depend>
+  <exec_depend>python3-opencv</exec_depend>
+  <exec_depend>rospy</exec_depend>
+
+  <test_depend>catkin_lint_cmake</test_depend>
+
+  <doc_depend>python3-sphinx</doc_depend>
+  <doc_depend>python-sphinx-autoapi-pip</doc_depend>
+  <doc_depend>python-sphinx-rtd-theme-pip</doc_depend>
+  <doc_depend>python3-yaml</doc_depend>
+
+
+  <export>
+    <rosdoc config="rosdoc.yaml" />
+  </export>
+</package>

face_recognition/rosdoc.yaml

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+- builder: sphinx
+  sphinx_root_dir: docs
+  name: Python API