def uiStartStopServices(self, row):
lf = tk.LabelFrame(self, text='Control CVAC Services:')
lf.grid(row=row, columnspan=5, sticky="ew")
self.serverStatus = tk.StringVar()
self.dataDir = easy.getFSPath("", abspath=True)
row = row + 1
self.startButton = tk.Button(lf, text='start services',
bg="light blue", width=12,
command=lambda: self.startStopServices(True))
self.startButton.grid(row=0, sticky=tk.W, padx=5)
self.stopButton = tk.Button(lf, text='stop services',
bg="light blue", width=12,
command=lambda: self.startStopServices(False))
self.stopButton.grid(row=0, column=1, padx=5)
self.statusButton = tk.Button(lf, text='status',
bg="light blue", width=12,
command=lambda: self.runServerStatus())
self.statusButton.grid(row=0, column=2, padx=5, sticky=tk.E)
tk.Label(lf, text="Service Status:").grid(row=2, sticky=tk.W)
statusLabel = tk.Label(lf, textvariable=self.serverStatus)
statusLabel.grid(row=2, column=1, pady=5, columnspan=4, sticky=tk.W)
tk.Label(lf, text="Data Dir:").grid(row=3, sticky=tk.W)
dirText = tk.Text(lf, width=38, height=1)
dirText.insert(tk.END, self.dataDir)
dirText.configure(state=tk.DISABLED, relief='groove', wrap='char',
borderwidth=2)
dirText.grid(row=3, column=1, columnspan=4, sticky=tk.W)
toolTip = ToolTip(dirText, text=self.dataDir, wraplength=600,
delay=1000)
if sys.platform!='win32':
checkButton = tk.Checkbutton(lf, text= 'Show services output',
variable=self.checkVar)
checkButton.grid(row=5, columnspan=5, sticky=tk.W)
return row
def getLabels(self):
# todo: this is a very preliminary implementation that
# doesn't do any error checking or create proper temp directories;
# it mainly just works with a remote tar.gz type corpus file
import urllib
import tarfile
urlfile = urllib.URLopener()
urlfile.retrieve( self.main_location, "deleteme.tar.gz" )
# extract the tar into a hardcoded dir path
extractinto = easy.getFSPath( "deleteme_tmpdir" )
if not os.path.exists(extractinto):
os.makedirs(extractinto)
tar = tarfile.open("deleteme.tar.gz")
tar.extractall(path=extractinto)
tar.close()
# obtain labelables from extracted tar directory
return easy.getLabelableList(extractinto)
def addCorpusFromConfig(self, cvacPath):
propFile = easy.getFSPath( cvacPath )
# since our config file does not have sections and we need one so we
# create a string with the required header and file contents
# and pass that to the parser
with open(propFile, 'r') as f:
fileStr = '[main]\n' + f.read()
str_fp = StringIO.StringIO(fileStr)
config = ConfigParser.RawConfigParser()
# Tell parser not to convert keys to lower case!
config.optionxform = str
config.readfp(str_fp)
configProps = config._sections['main']
corpus = self.parseCorpusProperties(configProps, propFile)
if corpus == None:
return None
corp = self.corpToImp.get(corpus.name)
if corp == None:
self.corpToImp[corpus.name] = corpus
return corpus
else:
return corpus
easy.printRunSetInfo(trainset, printLabels=True)
#
# Connect to the trainer for a Bag of Words algorithm, then
# train with the given runset
#
print("starting training, this might take a few minutes...")
trainer = easy.getTrainer("BOW_Trainer")
trainedModel = easy.train(trainer, trainset)
#
# Display information about the file in which the model is stored;
# this is generally no concern to algorithm users and only of
# interest to algorithm developers since it is algorithm-specific
#
zipfname = easy.getFSPath(trainedModel)
print("{0}".format(zipfname))
zipf = zipfile.ZipFile(zipfname)
print("Training model stored in file {0}".format(zipfname))
# print("file contents:\n{0}".format(zipf.namelist()))
#
# test the trained model on a separate set of images
#
print("==== Test runset: ====")
testset = easy.createRunSet("testImg")
easy.printRunSetInfo(testset, printLabels=True)
detector = easy.getDetector("BOW_Detector")
results = easy.detect(detector, trainedModel, testset)
print("==== Results: ====")
easy.printResults(results)
#
# detect remotely: note the host specification
#
detector = easy.getDetector("OpenCVCascadeDetector:default -p 10102 " + host)
results = easy.detect(detector, modelfile, rs1)
easy.printResults(results)
#
# Example 2:
# Train on a remote machine, obtain the model file, and test locally.
# Assume the files are on the remote machine, or transfer with putAllFiles.
# If no local services are installed, this will be skipped.
#
print("------- Remote training, local detection: -------")
try:
detector = easy.getDetector(
"BOW_Detector:default -p 10104") # local service
trainer = easy.getTrainer("BOW_Trainer:default -p 10103 " + host) # remote
trainset = easy.createRunSet("trainImg")
trainedModel = easy.train(trainer, trainset)
easy.getFile(fileserver, trainedModel) # downloads the model from remote
print("obtained trained detector, stored in file {0}".format(
easy.getFSPath(trainedModel)))
testset = easy.createRunSet("testImg", "UNPURPOSED")
results = easy.detect(detector, trainedModel, testset)
easy.printResults(results)
except:
print("Cannot connect to local detector. Have you started the services?\n"\
"This part of the demo does not work with the client-only distribution.")
print("------- Remote detection, local result display: -------")
fileserver = easy.getFileServer( "PythonFileService:default -p 10111 " + host )
putResult = easy.putAllFiles( fileserver, rs1 )
modelfile = "detectors/haarcascade_frontalface_alt.xml"
if not fileserver.exists( easy.getCvacPath(modelfile) ):
easy.putFile( fileserver, easy.getCvacPath(modelfile) )
#
# detect remotely: note the host specification
#
detector = easy.getDetector( "OpenCVCascadeDetector:default -p 10102 "+host )
results = easy.detect( detector, modelfile, rs1 )
easy.printResults( results )
#
# Example 2:
# Train on a remote machine, obtain the model file, and test locally.
# Assume the files are on the remote machine, or transfer with putAllFiles.
#
print("------- Remote training, local detection: -------")
trainer = easy.getTrainer( "BOW_Trainer:default -p 10103 "+ host) # remote
trainset = easy.createRunSet( "trainImg" );
trainedModel = easy.train( trainer, trainset )
easy.getFile( fileserver, trainedModel ) # downloads the model from remote
print("obtained trained detector, stored in file {0}"
.format(easy.getFSPath(trainedModel)))
detector = easy.getDetector( "BOW_Detector:default -p 10104" ) # local service
testset = easy.createRunSet("testImg","UNPURPOSED" )
results = easy.detect( detector, trainedModel, testset )
easy.printResults( results )
correct = easy.isProperRunSet(trainset, deleteInvalid=True)
if not correct:
print("failed Integrity test!!!!")
exit()
#trainset = easy.createRunSet( categories, purpose=posPurpose );
#easy.printRunSetInfo( trainset, printLabels=True )
easy.printRunSetInfo( trainset )
#
# Connect to the trainer for a Bag of Words algorithm, then
# train with the given runset
#
#trainer = easy.getTrainer( "BOW_Trainer")
trainer = easy.getTrainer( "BOW_Trainer:default -p 10103")
trainedModel = easy.train( trainer, trainset )
zipfname = easy.getFSPath( trainedModel )
print("Training model stored in file {0}".format( zipfname ))
#
# test the trained model on a separate set of images
#
print("==== Test runset: ====")
testset = easy.createRunSet( "testImg" )
easy.printRunSetInfo( testset, printLabels=True )
detector = easy.getDetector( "BOW_Detector" )
results = easy.detect( detector, trainedModel, testset )
print("==== Results: ====")
easy.printResults( results )
#
# Make sure all files in the RunSet are available on the remote site;
# it is the client's responsibility to upload them if not.
#
host = "-h localhost"
#host = "-h vision.nps.edu"
fileserver = easy.getFileServer( "FileService:default -p 10110 " + host )
putResult = easy.putAllFiles( fileserver, runset )
#
# Connect to a trainer service, train on the RunSet
#
trainer = easy.getTrainer( "bowTrain:default -p 10103 " + host )
trainedModel = easy.train( trainer, runset )
print("Training model stored in file: " + easy.getFSPath( trainedModel.file ))
#
# Connect to a detector service,
# test on the training RunSet for validation purposes;
# The detect call takes the detector, the trained model, the
# runset, and a mapping from purpose to label name
#
detector = easy.getDetector( "bowTest:default -p 10104 " + host )
results = easy.detect( detector, trainedModel, runset )
easy.printResults( results, foundMap=classmap )
easy.deleteAllFiles( fileserver, putResult['uploaded'] )
quit()