You need MRL with yolo service. MRL team are working for yolo integration in MRL.

For usage this is an example:

from java.lang import String
from org.myrobotlab.service import Runtime
from org.myrobotlab.service import OpenCV
from time import sleep
from shutil import copyfile
import os, sys

list=[]
cpt=0

opencv = Runtime.createAndStart(“opencv”,”OpenCV”)
yolo = Runtime.createAndStart(“yolo”,”Yolo”)
ImageYolo = Runtime.createAndStart(“ImageYolo”, “ImageDisplay”)

opencv.capture()
sleep(5)

# ##############################################################################
def displayPic(pic):
r = ImageYolo.displayFullScreen(pic)

# ##############################################################################
def takeFotoForYolo():
print “Photo…”
os.chdir(“d:\myrobotlab”)

photoFileName = opencv.recordSingleFrame()
print photoFileName

os.remove(“image.jpg”)
os.rename(photoFileName,”image.jpg”)
copyfile(“image.jpg”, “d:\myrobotlab\yolo\image.jpg”)
sleep(0.1)

yolo.execYolo()

# ##############################################################################
def statisticResult():
global list
NbElement=0

print “statistique…”
res = yolo.StatisticResult()

if res == True:
# Ici il y a obligatoirement des objects
list=[]
file = open(“statistics.txt”,”r”)

for ligne in file:
list.append(ligne)
file.close()

NbElement=len(list)
print “Number of recognized elements:”, NbElement

for val in list:
print val
else:
print “Rien trouvé !!”

# ##############################################################################
def analyseResult():
global list
NbElement=0

print “analyse…”
res = yolo.AnalyseResult()

if res == True:
# Ici il y a obligatoirement des objects
list=[]
file = open(“finalresult.txt”,”r”)

for ligne in file:
list.append(ligne)
file.close()

NbElement=len(list)
print “Number of recognized elements:”, NbElement

for val in list:
print val
else:
print “Rien trouvé !!”

##################################################################################
# Timer …
##################################################################################
def refresh(timedata):
global cpt

cpt += 1
if cpt==1:
takeFotoForYolo()
else:
ImageYolo.closeAll()
displayPic(“d:\myrobotlab\yolo\predictions.jpg”)
statisticResult()
sleep(0.1)
analyseResult()
cpt=0

timer = Runtime.start(“Timer”,”Clock”)
timer.setInterval(20000)
timer.addListener(“pulse”, python.name, “refresh”)
timer.startClock()

With yolo, you can do this: http://myrobotlab.org/content/yolo-dnn-support-now-opencv

For face tracking, i use tracking service from MRL

oeilG = Runtime.create(“oeilG”, “OpenCV”)
oeilG.setFrameGrabberType(“org.myrobotlab.opencv.SarxosFrameGrabber”)
oeilG = Runtime.start(“oeilG”, “OpenCV”)
oeilG.setCameraIndex(0)
tracking = Runtime.createAndStart(“tracking”, “Tracking”)

pid = tracking.getPID()
pid.setPID(“x”, 5.0, 5.0, 0.1)
pid.setPID(“y”, 5.0, 5.0, 0.1)

# optional filter settings
opencv = tracking.getOpenCV()

# connect to the Arduino ( 0 = camera index )
tracking.connect(oeilG, head.rotHead, head.neck)
opencv.broadcastState()
sleep(1)

tracking.faceDetect()