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#! /usr/bin/env python3
# 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
# copyright notice, this list of conditions and the following
# 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.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
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()
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