face_recognition_trainer.py

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#! /usr/bin/env python
# Software License Agreement (BSD License)
#
# Copyright (c) 2017, Yuki Furuta.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
#  * Redistributions of source code must retain the above copyright
#    notice, this list of conditions and the following disclaimer.
#  * Redistributions in binary form must reproduce the above
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#    disclaimer in the documentation and/or other materials provided
#    with the distribution.
#  * Neither the name of Kei Okada nor the names of its
#    contributors may be used to endorse or promote products derived
#    from this software without specific prior written permission.
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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from __future__ import print_function
 
try:
    input = raw_input
except:
    pass
 
import rospy
import message_filters
from sensor_msgs.msg import Image
from opencv_apps.msg import FaceArrayStamped
from opencv_apps.srv import FaceRecognitionTrain, FaceRecognitionTrainRequest
 
class FaceRecognitionTrainer(object):
    def __init__(self):
        self.queue_size = rospy.get_param("~queue_size", 100)
        
        self.img_sub = message_filters.Subscriber("image", Image)
        self.face_sub = message_filters.Subscriber("faces", FaceArrayStamped)
        
        self.req = FaceRecognitionTrainRequest()
        self.label = ""
        self.ok = False
 
        self.sync = message_filters.TimeSynchronizer([self.img_sub, self.face_sub],
                                                     self.queue_size)
        self.sync.registerCallback(self.callback)
    def callback(self, img, faces):
        if len(faces.faces) <= 0:
            return
        if self.ok:
            faces.faces.sort(key=lambda f: f.face.width * f.face.height)
            self.req.images.append(img)
            self.req.rects.append(faces.faces[0].face)
            self.req.labels.append(self.label)
            self.ok = False
    def run(self):
        rospy.wait_for_service("train")
        train = rospy.ServiceProxy("train", FaceRecognitionTrain)
        self.label = input("Please input your name and press Enter: ")
        while len(self.label) <= 0 or input("Your name is %s. Correct? [y/n]: " % self.label) not in ["", "y", "Y"]:
            self.label = input("Please input your name and press Enter: ")
 
        input("Please stand at the center of the camera and press Enter: ")
        while True:
            self.ok = True
            while self.ok:
                print("taking picture...")
                rospy.sleep(1)
            if input("One more picture? [y/n]: ") not in ["", "y", "Y"]:
                break
        print("sending to trainer...")
        
        res = train(self.req)
        if res.ok:
            print("OK. Trained successfully!")
        else:
            print("NG. Error: %s" % res.error)
 
if __name__ == '__main__':
    rospy.init_node("face_recognition_trainer")
    t = FaceRecognitionTrainer()
    t.run()