def recognise(image, addr, extras):
result = ""
x = image.width - 1
channels = getChannels(image)
bestBounds = []
#cv.NamedWindow("pic", 1)
#cv.NamedWindow("cols", 0)
while len(result) < nSegs and x >= minW:
x = cap.getBound(image, cap.CAP_BOUND_RIGHT, start=x)
ratings = []
for w in xrange(minW, min(maxW + 1, x)):
bounds = findBounds(image, x, w)
subImage = cap.getSubImage(image, bounds)
flags = findColors(subImage)
for index, flag in enumerate(flags):
if not flag: continue
seg = getSegment(channels[index], image, bounds)
seg = cap.flattenImage(adjustSize(seg, segSize))
guesses = ann.run(seg)
charIndex = cap.argmax(guesses)
ratings.append((guesses[charIndex], charIndex, index, bounds, seg))
best = max(ratings, key=itemgetter(0))
result += charset[best[1]]
bestChannel = channels[best[2]]
cv.SetImageROI(bestChannel, best[3])
cv.Set(bestChannel, 96, bestChannel)
cv.ResetImageROI(bestChannel)
bestBounds.append(best[3])
bestW = best[3][2]
x -= bestW
#print ann.run(best[4])
cap.processExtras([cap.drawComponents(image, bestBounds)], addr, extras, cap.CAP_STAGE_RECOGNISE)
return result[::-1]
def recogniseOne(seg):
resized = adjustSize(seg, segSize)
array = cap.flattenImage(resized)
guesses = ann.run(array)
ichar = cap.argmax(guesses)
guess = guesses[ichar]
return (guess, ichar)
def recogniseOne(seg):
resized = adjustSize(seg, segSize)
array = cap.flattenImage(resized)
guesses = ann.run(array)
ichar = cap.argmax(guesses)
guess = guesses[ichar]
return (guess, ichar)
def recognise(image, addr, extras):
result = ""
x = image.width - 1
channels = getChannels(image)
bestBounds = []
#cv.NamedWindow("pic", 1)
#cv.NamedWindow("cols", 0)
while len(result) < nSegs and x >= minW:
x = cap.getBound(image, cap.CAP_BOUND_RIGHT, start=x)
ratings = []
for w in xrange(minW, min(maxW + 1, x)):
bounds = findBounds(image, x, w)
subImage = cap.getSubImage(image, bounds)
flags = findColors(subImage)
for index, flag in enumerate(flags):
if not flag: continue
seg = getSegment(channels[index], image, bounds)
seg = cap.flattenImage(adjustSize(seg, segSize))
guesses = ann.run(seg)
charIndex = cap.argmax(guesses)
ratings.append(
(guesses[charIndex], charIndex, index, bounds, seg))
best = max(ratings, key=itemgetter(0))
result += charset[best[1]]
bestChannel = channels[best[2]]
cv.SetImageROI(bestChannel, best[3])
cv.Set(bestChannel, 96, bestChannel)
cv.ResetImageROI(bestChannel)
bestBounds.append(best[3])
bestW = best[3][2]
x -= bestW
#print ann.run(best[4])
cap.processExtras([cap.drawComponents(image, bestBounds)], addr, extras,
cap.CAP_STAGE_RECOGNISE)
return result[::-1]
