class SkeletonTrackerNode:
def __init__(self):
rospy.init_node('skeleton_node', anonymous=True)
# self.recog = PyPoseRecognizer(22, WIDTH, HEIGHT,self.forest_file,USE_CPU, 320)
self.grabber = PyOpenNIHandGrabber()
def run(self):
while not rospy.is_shutdown():
print("Wave the hand in front of the sensor \n")
self.found_mask = False
while not rospy.is_shutdown() and not self.find_hand():
pass
self.found_mask = True
while not rospy.is_shutdown() and self.track_skeleton():
pass
def find_hand(self):
self.rgb, self.depth = self.grabber.grabFrames()
# pos = self.grabber.getHand3DPos()
self.show_image()
# if len(pos) > 2:
# if pos[0] or pos[1] or pos[2]:
# return True
return False
def track_skeleton(self):
self.rgb, self.depth = self.grabber.grabFrames()
pos = self.grabber.getHand3DPos()
if not pos[0] and not pos[1] and not pos[2]:
print("Hand position lost...")
return False
self.mask = self.grabber.segment(self.depth, pos, RADIUS)
joints = self.recog.getJoints(self.depth, self.mask)
self.pub_skeleton(joints)
self.show_image()
return True
def show_image(self):
to_show = cvtColor(self.rgb, COLOR_RGB2BGR)
# if (self.found_mask):
# blank_image = np.zeros(to_show.shape, np.uint8)
# blank_image[:,:] = (0,0,255)
# rows,cols = self.mask.shape
# M = np.float32([[1,0,-20],[0,1,0]])
# self.mask = warpAffine(self.mask,M,(cols, rows))
# blank_image = bitwise_and(blank_image, blank_image, mask = self.mask)
# to_show = addWeighted(to_show, 1, blank_image, 0.4, 0)
imshow("Image", to_show)
k = waitKey(30)
def pub_skeleton(self, joints):
msg = hand_skeleton()
for j in joints:
msg.joints.append(Point(j[0], j[1], j[2]))
self.skeleton_pub.publish(msg)
class SkeletonTrackerNode:
def __init__(self):
rospy.init_node('skeleton_node', anonymous=True)
# self.recog = PyPoseRecognizer(22, WIDTH, HEIGHT,self.forest_file,USE_CPU, 320)
self.grabber = PyOpenNIHandGrabber()
def run(self):
while not rospy.is_shutdown():
print("Wave the hand in front of the sensor \n")
self.found_mask = False
while not rospy.is_shutdown() and not self.find_hand():
pass
self.found_mask = True
while not rospy.is_shutdown() and self.track_skeleton():
pass
def find_hand(self):
self.rgb, self.depth = self.grabber.grabFrames()
# pos = self.grabber.getHand3DPos()
self.show_image()
# if len(pos) > 2:
# if pos[0] or pos[1] or pos[2]:
# return True
return False
def track_skeleton(self):
self.rgb, self.depth = self.grabber.grabFrames()
pos = self.grabber.getHand3DPos()
if not pos[0] and not pos[1] and not pos[2]:
print ("Hand position lost...")
return False
self.mask = self.grabber.segment(self.depth, pos, RADIUS)
joints = self.recog.getJoints(self.depth, self.mask)
self.pub_skeleton(joints)
self.show_image()
return True
def show_image(self):
to_show = cvtColor(self.rgb, COLOR_RGB2BGR)
# if (self.found_mask):
# blank_image = np.zeros(to_show.shape, np.uint8)
# blank_image[:,:] = (0,0,255)
# rows,cols = self.mask.shape
# M = np.float32([[1,0,-20],[0,1,0]])
# self.mask = warpAffine(self.mask,M,(cols, rows))
# blank_image = bitwise_and(blank_image, blank_image, mask = self.mask)
# to_show = addWeighted(to_show, 1, blank_image, 0.4, 0)
imshow("Image", to_show)
k = waitKey(30)
def pub_skeleton(self, joints):
msg = hand_skeleton()
for j in joints:
msg.joints.append(Point(j[0], j[1],j[2]))
self.skeleton_pub.publish(msg)
def __init__(self):
rospy.init_node('skeleton_node', anonymous=True)
self.forest_file = rospy.get_param('~forest',
'../xml/forest-1layer.xml')
self.skeleton_topic = rospy.get_param('skeleton_topic', '/skeleton')
self.skeleton_pub = rospy.Publisher(self.skeleton_topic,
hand_skeleton,
queue_size=10)
self.recog = PyPoseRecognizer(WIDTH, HEIGHT, self.forest_file, USE_CPU,
320)
self.grabber = PyOpenNIHandGrabber()
def __init__(self):
rospy.init_node('skeleton_node', anonymous=True)
self.forest_file = rospy.get_param('~forest', '../xml/forest-1layer.xml')
self.skeleton_topic = rospy.get_param('skeleton_topic', '/skeleton')
self.skeleton_pub = rospy.Publisher(self.skeleton_topic, hand_skeleton, queue_size=10)
self.recog = PyPoseRecognizer(WIDTH, HEIGHT,self.forest_file,USE_CPU, 320)
self.grabber = PyOpenNIHandGrabber()
if len(sys.argv)!=3:
print("Usage: > python script_name forest1 forest2")
else:
# client = ClientSocket(IP, PORT, 'P'*16)
#CV2 Windows
namedWindow("rgb")
namedWindow("masc")
namedWindow("segno")
#OpenNi tracker and Cypher Initialization
recog = PyPoseRecognizer(22, WIDTH, HEIGHT,
sys.argv[1],
USE_CPU, 320)
grabber = PyOpenNIHandGrabber()
# clf = joblib.load(sys.argv[2])
# crypt = AES.new(PASSCODE)
#OpenNi wave to start tracking
for i in range(0,MAX_POSES):
#for i in range(0,10):
print("Wave the hand in front of the sensor \n")
while True:
rgb, depth = grabber.grabFrames()
pos = grabber.getHand3DPos()
if len(pos) > 2:
if pos[0] or pos[1] or pos[2]:
break
if __name__ == "__main__":
if len(sys.argv) != 3:
print("Usage: > python script_name forest1 forest2")
else:
client = ClientSocket(IP, PORT, 'P' * 16)
#CV2 Windows
namedWindow("rgb")
namedWindow("masc")
namedWindow("segno")
#OpenNi tracker and Cypher Initialization
recog = PyPoseRecognizer(WIDTH, HEIGHT, sys.argv[1], USE_CPU, 320)
grabber = PyOpenNIHandGrabber()
lista = create_list()
clf = joblib.load(sys.argv[2])
crypt = AES.new(PASSCODE)
#OpenNi wave to start tracking
for i in range(0, MAX_POSES):
#for i in range(0,10):
print("Wave the hand in front of the sensor \n")
while True:
rgb, depth = grabber.grabFrames()
pos = grabber.getHand3DPos()
if len(pos) > 2:
if pos[0] or pos[1] or pos[2]:
break
def __init__(self):
rospy.init_node('skeleton_node', anonymous=True)
# self.recog = PyPoseRecognizer(22, WIDTH, HEIGHT,self.forest_file,USE_CPU, 320)
self.grabber = PyOpenNIHandGrabber()
def __init__(self):
rospy.init_node('skeleton_node', anonymous=True)
# self.recog = PyPoseRecognizer(22, WIDTH, HEIGHT,self.forest_file,USE_CPU, 320)
self.grabber = PyOpenNIHandGrabber()