def main():
image = bayer("itau02.png")
template = bayer("keyboard.png")
correlation = correlate(image, template)
c_max = max(correlation)
c_min = min(correlation)
signal = (correlation - c_min) * 255 / (c_max - c_min)
toimage(signal).save("signal.png")
winner = where(correlation == c_max, 255, 0)
toimage(winner).save("winner.png")
print searchmax(winner)
def __init__(self, memory, *descriptors, **rois):
r'''Creates a new visual map out of a memory object, a collection of
object descriptors, and an optional dictionary of Regions of
Interest (ROI's).
'''
self.memory = bayer(memory)
self.descriptors = dict(descriptors)
self.rois = rois
def __call__(self, inputs=None, context=None):
sight = context.memory[self.index]
description = sight.descriptors[self.label]
if inputs != None:
return description(inputs, context=sight)
while True:
sleep(self.delay)
inputs = percept(bayer(self.source))
try:
return description(inputs, context=sight)
except failure:
pass
def main():
image = bayer('keyboard_seen.png')
template = bayer('2.png')
print templatesearch(image, template)
def __call__(self, context):
inputs = percept(bayer(self.image))
return what.__call__(self, inputs, context)
