image_recognition_face_recognition

TO DO

Face recognition with use of Facenet (https://github.com/timesler/facenet-pytorch/tree/master) Paper can be found: paper

Installation

See https://github.com/tue-robotics/image_recognition

Make sure you have installed CUDA8.

bash commends will be available when merged

How-to

Run Face Recognition Node

Run the command why using your camera as an input (use roscamera node):

rosrun cv_camera cv_camera_node
rosrun image_recognition_face_recognition face_recognition_node image:=/cv_camera/image_raw 

ROS Node

Run the image_recognition_face_detection node in one terminal (Specify the dlib and openface_net path as ROS parameter):

rosrun image_recognition_face_detection 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.

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.

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:

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_face_recognition get_face_recognition `rospack find image_recognition_face_recognition`/doc/example.png