'''
Extract only optimal ROC points
'''
detector = easy.getDetector( strDetector )
detectorProps = easy.getDetectorProperties(detector)
#specify either a desired falseAlarmRate or recall, but not both:
priority = "recall"
if priority=="falseAlarmRate":
detectorProps.falseAlarmRate = 0.01 #x-axis
print("falseAlarmRate = {0}".format(detectorProps.falseAlarmRate))
else:
detectorProps.recall = 0.90 #y-axis
print("recall = {0}".format(detectorProps.recall))
results = easy.detect( detector, rocZip, runset, detectorProperties = detectorProps)
easy.printResults( results )
else:
###############################################################
# Without background data
'''
Execute jousting for generating ROC points
'''
contenders = []
for nWord in list_nWord:
c1 = evaluate.Contender("bowROC_oneclass_"+str(nWord))
c1.trainerString = strTrainer
c1.detectorString = strDetector
trainer = easy.getTrainer(c1.trainerString)
trainerProps = easy.getTrainerProperties(trainer)
trainerProps.props["RejectClassStrategy"] = "ignore"
trainerProps.props["NumWords"] = str(nWord)
'''
Easy! mini tutorial
Kalman tracker via Matlab Bridge
matz 10/2014
'''
import easy
#
# create a test set as in the Matlab sample at
# http://www.mathworks.com/help/vision/ug/object-tracking.html
# You need to have the Matlab vision toolbox installed. The
# singleball.avi movie is here:
# YourMatlabProgramPath/toolbox/vision/visiondemos/singleball.avi
# You should move it to the Easy! data directory for the demo
#
runset = easy.createRunSet("singleball.avi")
# Optionally, specify a folder that contains a sequence of the video's
# frames as image files
# runset = easy.createRunSet( "singleball.avi_frames" )
#
# evaluate your tracking algorithm with a common match scoring method
#
tracker = easy.getDetector("KalmanTracker")
results = easy.detect(tracker, None, runset)
easy.printResults(results)
easy.printLabeledTrack(results)
# Because we don't specify it, this guesses the specific Purpose that
# is assigned to the labels.
# Also obtain this mapping from Purpose to label name, called "classmap."
rs1 = easy.createRunSet( categories1['CA_flag']+categories2['ca'], "0" )
easy.addToRunSet( rs1, categories1['KO_flag']+categories2['kr'], "1" )
easy.addToRunSet( rs1, categories1['US_flag']+categories2['us'], "2" )
print("\n=== The Corpora combined into one RunSet: ===");
easy.printRunSetInfo( rs1 )
# A runset can be used for training or for testing
print("------- Bag of Words results for corporate logos: -------")
detector = easy.getDetector( "BOW_Detector" )
modelfile = "detectors/bowUSKOCA.zip"
results1 = easy.detect( detector, modelfile, rs1 )
print("Note that both original and found labels are printed:")
easy.printResults( results1 )
# Print again, this time replacing the found labels with a double
# mapping from foundLabel -> guessed Purpose -> classmap label;
# Note that this fails if multiple original labels mapped to the same
# Purpose.
wait()
print("------- Same results, but found labels replaced with guessed original labels: -------")
easy.printResults( results1, foundMap=rs1['classmap'], inverseMap=True )
# Print again, this time replacing all labels with their assigned
# purposes, bot original and found labels. Note the "identical label"
# matches.
wait()
print("------- Same results, but labels replaced with purposes: -------")
easy.printResults( results1, origMap=rs1['classmap'], foundMap=rs1['classmap'] )
def test_cvacdatadir(self):
print("testing cvac data dir")
if sys.platform == 'win32':
datadir = os.getenv("CVAC_DATADIR", None)
datadir = datadir.replace("/", "\\")
easy.CVAC_DataDir = datadir
print("Testing using back slashes")
print("Using CVAC_DATADIR as " + datadir)
testset = []
easy.misc.searchDir(testset, datadir + '\\testImg', recursive=True, video=False, image=True)
runset = cvac.RunSet()
easy.addToRunSet(runset, testset, 'pos')
modelfile = 'detectors/bowUSKOCA.zip'
detector = easy.getDetector("BOW_Detector")
props = easy.getDetectorProperties(detector)
props.verbosity = 3
results = easy.detect(detector, modelfile, runset,
detectorProperties=props)
easy.printResults(results)
else:
print("Skipping back slash test on this platform")
#run it again with all forward slashes
datadir = os.getenv("CVAC_DATADIR", None)
datadir = datadir.replace("\\", "/")
print("Testing using all forward slashes")
print("Using CVAC_DATADIR as " + datadir)
easy.CVAC_DataDir = datadir
testset = []
easy.misc.searchDir(testset, datadir + '/testImg', recursive=True, video=False, image=True)
runset = cvac.RunSet()
easy.addToRunSet(runset, testset, 'pos')
modelfile = 'detectors/bowUSKOCA.zip'
detector = easy.getDetector("BOW_Detector")
props = easy.getDetectorProperties(detector)
props.verbosity = 3
results = easy.detect(detector, modelfile, runset,
detectorProperties=props)
easy.printResults(results)
#run it for forward slashes and relative path
origDir = datadir
curDir = os.getcwd()
curDir = curDir.replace("\\", "/")
datadir = datadir.replace("\\", "/")
print("using relative paths for " + curDir + " in data dir " + datadir)
if datadir.startswith(curDir):
datadir = datadir[len(curDir)+1:]
easy.CVAC_DataDir = datadir
print("Using CVAC_DataDir as " + datadir)
testset = []
easy.misc.searchDir(testset, origDir + '/testImg', recursive=True, video=False, image=True)
runset = cvac.RunSet()
easy.addToRunSet(runset, testset, 'pos')
modelfile = origDir + '/detectors/bowUSKOCA.zip'
detector = easy.getDetector("BOW_Detector")
props = easy.getDetectorProperties(detector)
props.verbosity = 3
results = easy.detect(detector, modelfile, runset,
detectorProperties=props)
easy.printResults(results)
else:
RuntimeError("Bad datadir")
def test_cvacdatadir(self):
print("testing cvac data dir")
if sys.platform == 'win32':
datadir = os.getenv("CVAC_DATADIR", None)
datadir = datadir.replace("/", "\\")
easy.CVAC_DataDir = datadir
print("Testing using back slashes")
print("Using CVAC_DATADIR as " + datadir)
testset = []
easy.misc.searchDir(testset,
datadir + '\\testImg',
recursive=True,
video=False,
image=True)
runset = cvac.RunSet()
easy.addToRunSet(runset, testset, 'pos')
modelfile = 'detectors/bowUSKOCA.zip'
detector = easy.getDetector("BOW_Detector")
props = easy.getDetectorProperties(detector)
props.verbosity = 3
results = easy.detect(detector,
modelfile,
runset,
detectorProperties=props)
easy.printResults(results)
else:
print("Skipping back slash test on this platform")
#run it again with all forward slashes
datadir = os.getenv("CVAC_DATADIR", None)
datadir = datadir.replace("\\", "/")
print("Testing using all forward slashes")
print("Using CVAC_DATADIR as " + datadir)
easy.CVAC_DataDir = datadir
testset = []
easy.misc.searchDir(testset,
datadir + '/testImg',
recursive=True,
video=False,
image=True)
runset = cvac.RunSet()
easy.addToRunSet(runset, testset, 'pos')
modelfile = 'detectors/bowUSKOCA.zip'
detector = easy.getDetector("BOW_Detector")
props = easy.getDetectorProperties(detector)
props.verbosity = 3
results = easy.detect(detector,
modelfile,
runset,
detectorProperties=props)
easy.printResults(results)
#run it for forward slashes and relative path
origDir = datadir
curDir = os.getcwd()
curDir = curDir.replace("\\", "/")
datadir = datadir.replace("\\", "/")
print("using relative paths for " + curDir + " in data dir " +
datadir)
if datadir.startswith(curDir):
datadir = datadir[len(curDir) + 1:]
easy.CVAC_DataDir = datadir
print("Using CVAC_DataDir as " + datadir)
testset = []
easy.misc.searchDir(testset,
origDir + '/testImg',
recursive=True,
video=False,
image=True)
runset = cvac.RunSet()
easy.addToRunSet(runset, testset, 'pos')
modelfile = origDir + '/detectors/bowUSKOCA.zip'
detector = easy.getDetector("BOW_Detector")
props = easy.getDetectorProperties(detector)
props.verbosity = 3
results = easy.detect(detector,
modelfile,
runset,
detectorProperties=props)
easy.printResults(results)
else:
RuntimeError("Bad datadir")
thisPath = os.path.dirname(os.path.abspath(__file__)) srcPath = os.path.abspath(thisPath+"/../../lib/python") sys.path.append(srcPath) import paths import cvac import easy # # First, a teaser for detection: # detector = easy.getDetector( "bowTest:default -p 10104" ) results = easy.detect( detector, "detectors/bowUSKOCA.zip", "testImg/TestCaFlag.jpg" ) easy.printResults( results ) # # Second, a quick way to train a detector. The resulting model # can be used in place of the detector above. # # TODO: currently breaks because Caltech101 doesn't get extracted as expected #categories, lablist = easy.getDataSet( "corpus/CvacCorpusTest" ) # categories, lablist = easy.getDataSet( "corpus/Caltech101.properties", createMirror=False ) #easy.printCategoryInfo( categories ) #runset = easy.createRunSet( categories["car_side"] ) #trainer = easy.getTrainer( "bowTrain:default -p 10103" ) #carSideModel = easy.train( trainer, runset ) # # Third, a slower walk-through of functionality that digs a bit deeper. All
# Because we don't specify it, this guesses the specific Purpose that
# is assigned to the labels.
# Also obtain this mapping from Purpose to label name, called "classmap."
rs1 = easy.createRunSet(categories1['CA_flag'] + categories2['ca'], "0")
easy.addToRunSet(rs1, categories1['KO_flag'] + categories2['kr'], "1")
easy.addToRunSet(rs1, categories1['US_flag'] + categories2['us'], "2")
print("\n=== The Corpora combined into one RunSet: ===")
easy.printRunSetInfo(rs1)
# A runset can be used for training or for testing
print("------- Bag of Words results for corporate logos: -------")
detector = easy.getDetector("BOW_Detector")
modelfile = "detectors/bowUSKOCA.zip"
results1 = easy.detect(detector, modelfile, rs1)
print("Note that both original and found labels are printed:")
easy.printResults(results1)
# Print again, this time replacing the found labels with a double
# mapping from foundLabel -> guessed Purpose -> classmap label;
# Note that this fails if multiple original labels mapped to the same
# Purpose.
wait()
print(
"------- Same results, but found labels replaced with guessed original labels: -------"
)
easy.printResults(results1, foundMap=rs1['classmap'], inverseMap=True)
# Print again, this time replacing all labels with their assigned
# purposes, bot original and found labels. Note the "identical label"
# matches.
wait()
