def main():
args = configureArguments()
configureLogging(args.log, 'window_input.log')
returnCode = 9
sshClient = None
name = ''
email = ''
try:
stdscr = initCurses()
sshClient = MultipleSSHClient(args.sshHost, args.sshUser, args.sshPassword)
while not name or not email:
(name, email) = drawInputWindow(stdscr)
img = getUserPicture(int(args.outputWidth))
savePicture(sshClient, img, name, email, args.tempLocalFolder, args.remoteFolder)
# drawThanksWindow(stdscr)
except KeyboardInterrupt:
returnCode = 0
except paramiko.SSHException:
logging.error('Error when connecting to one or more SSH servers.')
finally:
if sshClient is not None:
sshClient.close()
cv2.destroyAllWindows()
destroyCurses()
sys.exit(returnCode)
def main():
args = configureArguments()
configureLogging(args.log)
logging.info("Starting web crawler")
subjectsQueue = Queue.Queue()
newSubjectHandler = NewSubjectDetectedEventHandler()
try:
logging.debug('Creating custom event handler...')
handler = FileCreatedEventHandler(subjectsQueue)
observer = Observer()
observer.schedule(handler, args.newSubjectsFolder)
observer.start()
logging.debug('Starting notifier infinite loop...')
while True:
if not subjectsQueue.empty():
newSubjectHandler.newSubject(subjectsQueue.get())
time.sleep(1)
except KeyboardInterrupt:
observer.stop()
observer.join()
logging.info('END web crawler gracefully.')
def main():
args = configureArguments()
configureLogging(args.log)
#faceSize = (100, 100)
faceSize = None
logging.debug('Creating face recognizer...')
#fr = cv2.createFisherFaceRecognizer()
fr = cv2.createLBPHFaceRecognizer()
#modelFile = '/home/juan/ciberpunks/faces/lpbFaceModel'
#if os.path.isfile(modelFile):
# fr.load(modelFile)
# logging.info('Loaded saved model state.')
#else:
trainPaths = [
'/home/juan/ciberpunks/faces/at&t_database',
'/home/juan/ciberpunks/faces/lfw2',
'/home/juan/ciberpunks/faces/prestico']
[images, labels, subjects] = readImages(trainPaths, faceSize)
logging.debug('Training face recognizer...')
fr.train(images, labels)
#fr.save(modelFile)
#logging.info('Saved a trained model state.')
logging.debug('Staring face recognition...')
#recognizePictureCandidates(fr, subjects, faceSize)
recognizeVideo(fr, args.videoFileName, subjects, args.haarFolder)
def main():
args = configureArguments()
configureLogging(args.log)
logging.info("Starting video delay...")
picWin = "Sonria..."
try:
camera = cv2.VideoCapture(0)
outputSize = calculateScaledSize(args.outputWidth, capture=camera)
if not camera.isOpened():
logging.error("Arrrgggghhhh! Camera is not open...")
return None
cv2.namedWindow(picWin)
if args.delay == 0:
readOk = True
while cv2.waitKey(1) == -1:
readOk, image = camera.read()
cv2.imshow(picWin, image)
cv2.waitKey(1)
else:
fps = camera.get(cv2.cv.CV_CAP_PROP_FPS)
logging.debug("Detected {0} FPS".format(fps))
fps = fps if fps > 0 else 30
logging.debug("Using {0} FPS".format(fps))
frameBufferSize = fps * args.delay
framesBuffer = [None] * frameBufferSize
logging.debug("Start reading and buffering {0} frames...".format(frameBufferSize))
i = 0
while cv2.waitKey(1) and i < frameBufferSize:
readOk, image = camera.read()
framesBuffer[i] = image
i += 1
logging.debug("Start display of buffered images and queue new ones...")
while True:
for i in xrange(frameBufferSize):
readOk, image = camera.read()
delayedImage = framesBuffer[i]
framesBuffer[i] = image
outputImage = delayedImage # cv2.resize(delayedImage, outputSize)
cv2.imshow(picWin, outputImage)
cv2.waitKey(1)
except KeyboardInterrupt:
pass
logging.debug("Trying to exit app gracefuly.")
camera.release()
cv2.destroyWindow(picWin)
logging.info("Exit video delay OK.")
def main():
args = configureArguments()
configureLogging(args.log)
windowTitle = "Test draw app"
cv2.namedWindow(windowTitle)
haarFolder = "/home/juan/ciberpunks/opencv-2.4.11/data/haarcascades"
faceCascade = loadCascadeClassifier(haarFolder + "/haarcascade_frontalface_alt2.xml")
leftEyeCascade = loadCascadeClassifier(haarFolder + "/haarcascade_lefteye_2splits.xml")
rightEyeCascade = loadCascadeClassifier(haarFolder + "/haarcascade_righteye_2splits.xml")
mouthCascade = loadCascadeClassifier(haarFolder + '/haarcascade_mcs_mouth.xml')
color = (120,120,130)
thickness = 2
width = 600
image = cv2.imread('/home/juan/ciberpunks/faces/news/[email protected]')
image = cv2.resize(image, calculateScaledSize(width, image=image))
if image is None:
print 'ERROR: no se pudo leer la imagen.'
return
minFaceSize = (10, 10)
minEyeSize = (5, 5)
faces = detectFaces(image, faceCascade, leftEyeCascade, rightEyeCascade, minFaceSize, minEyeSize)
for (x, y, w, h, leftEyes, rightEyes) in faces:
center = calculateCenter((x,y,w,h))
cv2.line(image, (x,0), (x, width), color, 2)
cv2.line(image, (x+w,0), (x+w, width), color, 2)
cv2.line(image, (0,y), (width, y), color, 2)
cv2.line(image, (0,y+h), (width, y+h), color, 2)
drawLabel("Juan Gabriel", image, (x, y+20))
cv2.imshow(windowTitle, image)
cv2.waitKey(6000)
cv2.destroyWindow(windowTitle)
