def main(argv, prog=''):
# Create an instance of the matting class
mat = Matting()
# Parse the command line arguments
success, args, unprocessedArgv, msg = parseArguments(argv, mat, prog)
if not success:
print 'Error: Argument parsing: ', msg
return success, unprocessedArgv
# Initialize the variables for measuring timings
t1 = t2 = t3 = t4 = 0
if args.matting:
# Get the value of the openCV timer
t1 = cv.getTickCount()
# Call the routine that reads the images and stores them in
# the appropriate data structure stored with the matting
# instance
#
# Note: The images themselves are supposed to be private
# variables. They should be acccessed using the
# readImage(), writeImage(), useTriangulationResults()
# methods of the matting class. The images are referenced
# by their string descriptor
for (fname, key) in [(args.backA[0], 'backA'),
(args.backB[0], 'backB'),
(args.compA[0], 'compA'),
(args.compB[0], 'compB')]:
success, msg = mat.readImage(fname, key)
if not success:
print 'Error: %s'%msg
return success, unprocessedArgv
# Get the value of the openCV timer
t2 = cv.getTickCount()
# Run the triangulation matting algorithm. The routine
# returns a tuple whose first element is True iff the routine
# was successfully executed and the second element is
# an error message string (if the routine failed)
print 'Triangulation matting...'
success, text = mat.triangulationMatting()
if not success:
print 'Error: Triangulation matting routine failed: %s'%text
return success, unprocessedArgv
# Get the value of the openCV timer
t3 = cv.getTickCount()
# Call the routine that writes to disk images stored in a matting
# instance.
# Note: The images themselves are supposed to be private variables
# They should be acccessed using the readImage(), writeImage()
# and useTriangulationResults() methods of the matting class
# The images are referenced by their string descriptor
for (fname, key) in [(args.colOut[0], 'colOut'),
(args.alphaOut[0], 'alphaOut')]:
success, msg = mat.writeImage(fname, key)
if not success:
print msg
print 'Error: Image %s cannot be written'%fname
return success, unprocessedArgv
# Get the value of the openCV timer
t4 = cv.getTickCount()
elif args.compositing:
t1 = cv.getTickCount()
# Call the routine that reads the images and stores them in
# the appropriate data structure stored with the matting
# instance
#
# Note: The images themselves are supposed to be private
# variables. They should be acccessed using the
# readImage(), writeImage(), useTriangulationResults()
# methods of the matting class. The images are referenced
# by their string descriptor
for (fname, key) in [(args.colIn[0], 'colIn'),
(args.alphaIn[0], 'alphaIn'),
(args.backIn[0], 'backIn')]:
success, msg = mat.readImage(fname, key)
if not success:
print 'Error: %s'%msg
return success, unprocessedArgv
print 'Compositing...'
t2 = cv.getTickCount()
# Run the compositing algorithm. The routine
# returns a tuple whose first element is True iff the routine
# was successfully executed and the second element is
# an error message string (if the routine failed)
success, text = mat.createComposite()
if not success:
print 'Error: %s'%text
return success, unprocessedArgv
t3 = cv.getTickCount()
success, msg = mat.writeImage(args.compOut[0], 'compOut')
if not success:
print msg
print 'Error: Image %s cannot be written'%fname
return success, unprocessedArgv
t4 = cv.getTickCount()
print '----------------------------------\nTimings\n----------------------------------'
print 'Reading: %g seconds'%((t2-t1)/cv.getTickFrequency())
print 'Processing: %g seconds'%((t3-t2)/cv.getTickFrequency())
print 'Writing: %g seconds'%((t4-t3)/cv.getTickFrequency())
# return any command-line arguments that were not processed
return success, unprocessedArgv
def main(argv, prog=''):
# Create an instance of the matting class
mat = Matting()
# Parse the command line arguments
success, args, unprocessedArgv, msg = parseArguments(argv, mat, prog)
if not success:
print 'Error: Argument parsing: ', msg
return success, unprocessedArgv
# Initialize the variables for measuring timings
t1 = t2 = t3 = t4 = 0
if args.matting:
# Get the value of the openCV timer
t1 = cv.getTickCount()
# Call the routine that reads the images and stores them in
# the appropriate data structure stored with the matting
# instance
#
# Note: The images themselves are supposed to be private
# variables. They should be acccessed using the
# readImage(), writeImage(), useTriangulationResults()
# methods of the matting class. The images are referenced
# by their string descriptor
for (fname,
key) in [(args.backA[0], 'backA'), (args.backB[0], 'backB'),
(args.compA[0], 'compA'), (args.compB[0], 'compB')]:
success, msg = mat.readImage(fname, key)
if not success:
print 'Error: %s' % msg
return success, unprocessedArgv
# Get the value of the openCV timer
t2 = cv.getTickCount()
# Run the triangulation matting algorithm. The routine
# returns a tuple whose first element is True iff the routine
# was successfully executed and the second element is
# an error message string (if the routine failed)
print 'Triangulation matting...'
success, text = mat.triangulationMatting()
if not success:
print 'Error: Triangulation matting routine failed: %s' % text
return success, unprocessedArgv
# Get the value of the openCV timer
t3 = cv.getTickCount()
# Call the routine that writes to disk images stored in a matting
# instance.
# Note: The images themselves are supposed to be private variables
# They should be acccessed using the readImage(), writeImage()
# and useTriangulationResults() methods of the matting class
# The images are referenced by their string descriptor
for (fname, key) in [(args.colOut[0], 'colOut'),
(args.alphaOut[0], 'alphaOut')]:
success, msg = mat.writeImage(fname, key)
if not success:
print msg
print 'Error: Image %s cannot be written' % fname
return success, unprocessedArgv
# Get the value of the openCV timer
t4 = cv.getTickCount()
elif args.compositing:
t1 = cv.getTickCount()
# Call the routine that reads the images and stores them in
# the appropriate data structure stored with the matting
# instance
#
# Note: The images themselves are supposed to be private
# variables. They should be acccessed using the
# readImage(), writeImage(), useTriangulationResults()
# methods of the matting class. The images are referenced
# by their string descriptor
for (fname, key) in [(args.colIn[0], 'colIn'),
(args.alphaIn[0], 'alphaIn'),
(args.backIn[0], 'backIn')]:
success, msg = mat.readImage(fname, key)
if not success:
print 'Error: %s' % msg
return success, unprocessedArgv
print 'Compositing...'
t2 = cv.getTickCount()
# Run the compositing algorithm. The routine
# returns a tuple whose first element is True iff the routine
# was successfully executed and the second element is
# an error message string (if the routine failed)
success, text = mat.createComposite()
if not success:
print 'Error: %s' % text
return success, unprocessedArgv
t3 = cv.getTickCount()
success, msg = mat.writeImage(args.compOut[0], 'compOut')
if not success:
print msg
print 'Error: Image %s cannot be written' % fname
return success, unprocessedArgv
t4 = cv.getTickCount()
print '----------------------------------\nTimings\n----------------------------------'
print 'Reading: %g seconds' % ((t2 - t1) / cv.getTickFrequency())
print 'Processing: %g seconds' % ((t3 - t2) / cv.getTickFrequency())
print 'Writing: %g seconds' % ((t4 - t3) / cv.getTickFrequency())
# return any command-line arguments that were not processed
return success, unprocessedArgv