NAOqi Vision - Overview | API | Tutorial
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This tutorial explains how to run the ALFaceDetection module using Python. We use the following approach: we regularly check the ALMemory’s result variable. Information about the detected faces is printed on the screen.
After some initialization steps, we first instantiate a proxy to the ALFaceDetection module.
# This test demonstrates how to use the ALFaceDetection module.
# Note that you might not have this module depending on your distribution
#
# - We first instantiate a proxy to the ALFaceDetection module
# Note that this module should be loaded on the robot's NAOqi.
# The module output its results in ALMemory in a variable
# called "FaceDetected"
# - We then read this ALMemory value and check whether we get
# interesting things.
import time
from naoqi import ALProxy
# Replace this with your robot's IP address
IP = "10.0.252.91"
PORT = 9559
# Create a proxy to ALFaceDetection
try:
faceProxy = ALProxy("ALFaceDetection", IP, PORT)
except Exception, e:
print "Error when creating face detection proxy:"
print str(e)
exit(1)
# Subscribe to the ALFaceDetection proxy
# This means that the module will write in ALMemory with
# the given period below
period = 500
faceProxy.subscribe("Test_Face", period, 0.0 )
Now we need to get a proxy to ALMemory and check the ALFaceDetection output variable.
# ALMemory variable where the ALFaceDetection module
# outputs its results.
memValue = "FaceDetected"
# Create a proxy to ALMemory
try:
memoryProxy = ALProxy("ALMemory", IP, PORT)
except Exception, e:
print "Error when creating memory proxy:"
print str(e)
exit(1)
# A simple loop that reads the memValue and checks whether faces are detected.
for i in range(0, 20):
time.sleep(0.5)
val = memoryProxy.getData(memValue, 0)
print ""
print "\*****"
print ""
# Check whether we got a valid output: a list with two fields.
if(val and isinstance(val, list) and len(val) == 2):
# We detected faces !
# For each face, we can read its shape info and ID.
# First Field = TimeStamp.
timeStamp = val[0]
# Second Field = array of face_Info's.
faceInfoArray = val[1]
try:
# Browse the faceInfoArray to get info on each detected face.
for faceInfo in faceInfoArray:
# First Field = Shape info.
faceShapeInfo = faceInfo[0]
# Second Field = Extra info (empty for now).
faceExtraInfo = faceInfo[1]
print " alpha %.3f - beta %.3f" % (faceShapeInfo[1], faceShapeInfo[2])
print " width %.3f - height %.3f" % (faceShapeInfo[3], faceShapeInfo[4])
except Exception, e:
print "faces detected, but it seems getData is invalid. ALValue ="
print val
print "Error msg %s" % (str(e))
else:
print "Error with getData. ALValue = %s" % (str(val))
# Unsubscribe the module.
faceProxy.unsubscribe("Test_Face")
print "Test terminated successfully."
Here is what you get when you execute the above script. We get different results as we occult or present new faces to NAO.
\*****
alpha 0.243 - beta 0.005
width 0.167 - height 0.167
\*****
alpha 0.243 - beta 0.005
width 0.167 - height 0.167
\*****
alpha 0.243 - beta 0.005
width 0.167 - height 0.167