def segment(image, addr, extras):
log = cap.logger(extras, image)
components = findComponents(image, log)
log.log(cap.drawComponents(image, components))
angles = map(lambda comp: findAngle(comp, log), components)
angles = filter(lambda angle: angle != 0.0 and abs(angle) <= 27.0, angles)
if len(angles) != 0:
angle = fsum(angles) / len(angles)
image = cap.doRotate(image,
-angle,
fillval=255,
interpolation=cv.CV_INTER_NN)
log.log(image)
components = findComponents(image)
assert (len(components) <= nSegs)
log.log(cap.drawComponents(image, components))
#components = cap.spltCCs(components, cap.partsFromnSegs5(components), projRadius=5, thresh=2)
#components = filtCCs(components, (15, 15), 200, 0.2)
components = map(lambda comp: addBackground(comp, image, bgcolor=96),
components)
segments = map(lambda comp: comp[3], components)
segments = map(removeBadBackground, segments)
log.log(cap.joinImagesH(segments))
segments = map(lambda seg: cap.smoothNoise1(seg, bgcolor=0), segments)
log.log(cap.joinImagesH(segments))
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_SEGMENT)
return segments
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 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 segment(image, addr, extras):
clone = cv.CloneImage(image)
log = cap.logger(extras, image)
components = cap.findCCs(image, erasecol=0, doContinue=None, doSkip=lambda comp: comp[0] <= 25)
log.log(cap.drawComponents(clone, components))
if len(components) != nSegs:
components = cap.joinCCs(components, cap.rectsIntersectH)
log.log(cap.drawComponents(clone, components))
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_SEGMENT)
assert(len(components) == nSegs)
segments = map(lambda comp: comp[3], components)
return segments
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
image = cap.doResize(image, factor, cv.CV_INTER_CUBIC)
log.log(image)
image = undistort(image)
log.log(image)
cv.Threshold(image, image, 200, 255, cv.CV_THRESH_BINARY)
log.log(image)
image = cap.repaintCCs(image, doRepaint=lambda comp, col: comp[0] <= 10 and col <= 128)
log.log(image)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return image
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
image = cap.doResize(image, factor, cv.CV_INTER_CUBIC)
log.log(image)
image = undistort(image)
log.log(image)
cv.Threshold(image, image, 200, 255, cv.CV_THRESH_BINARY)
log.log(image)
image = cap.repaintCCs(
image, doRepaint=lambda comp, col: comp[0] <= 10 and col <= 128)
log.log(image)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return image
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
alpha, dark = rotAngle(image)
log.log(dark, False)
clear = clearNoise(image)
log.log(clear, False)
straight = cap.doRotate(clear, -alpha, fillval=0, resize=False, interpolation=cv.CV_INTER_NN)
#cv.Threshold(straight, straight, 128, 255, cv.CV_THRESH_BINARY)
log.log(straight)
cv.Dilate(straight, straight)
cv.Erode(straight, straight)
log.log(straight)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return straight
def segment(image, addr, extras):
clone = cv.CloneImage(image)
log = cap.logger(extras, image)
components = cap.findCCs(image,
erasecol=0,
doContinue=None,
doSkip=lambda comp: comp[0] <= 25)
log.log(cap.drawComponents(clone, components))
if len(components) != nSegs:
components = cap.joinCCs(components, cap.rectsIntersectH)
log.log(cap.drawComponents(clone, components))
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_SEGMENT)
assert (len(components) == nSegs)
segments = map(lambda comp: comp[3], components)
return segments
def segment(image, addr, extras):
log = cap.logger(extras, image)
clone = cv.CloneImage(image)
components = cap.findCCs(image, 0, lambda col: col <= 128, lambda comp: comp[0] < 10)
log.log(cap.drawComponents(clone, components), False)
components = cap.joinCCs(components, cap.rectsIntersectH)
log.log(cap.drawComponents(clone, components), False)
assert(len(components) <= nSegs)
parts = cap.partsFromnSegs5(components)
components = cap.spltCCs(components, parts, projRadius=4, thresh=1)
log.log(cap.drawComponents(clone, components), False)
segments = map(lambda comp: comp[3], components)
log.log(cap.joinImagesH(segments), False)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_SEGMENT)
return segments
def segment(image, addr, extras):
clone = cv.CloneImage(image)
log = cap.logger(extras, image)
components = cap.findCCs(image, erasecol=255, doContinue=lambda col: col == 255, doSkip=lambda comp: comp[0] <= 20)
#components = cap.spltCCs(components, cap.partsFromSegW(components, 20), projRadius=5, thresh=1)
log.log(cap.drawComponents(clone, components))
while len(components) > nSegs:
smallest = cap.argmin(components, itemgetter(0))
del(components[smallest])
assert(len(components) == nSegs)
log.log(cap.drawComponents(clone, components))
segments = map(lambda comp: comp[3], components)
log.log(cap.joinImagesH(segments))
segments = map(deRotate, segments)
log.log(cap.joinImagesH(segments))
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_SEGMENT)
return segments
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
alpha, dark = rotAngle(image)
log.log(dark, False)
clear = clearNoise(image)
log.log(clear, False)
straight = cap.doRotate(clear,
-alpha,
fillval=0,
resize=False,
interpolation=cv.CV_INTER_NN)
#cv.Threshold(straight, straight, 128, 255, cv.CV_THRESH_BINARY)
log.log(straight)
cv.Dilate(straight, straight)
cv.Erode(straight, straight)
log.log(straight)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return straight
def segment(image, addr, extras):
clone = cv.CloneImage(image)
log = cap.logger(extras, image)
components = cap.findCCs(image,
erasecol=255,
doContinue=lambda col: col == 255,
doSkip=lambda comp: comp[0] <= 20)
#components = cap.spltCCs(components, cap.partsFromSegW(components, 20), projRadius=5, thresh=1)
log.log(cap.drawComponents(clone, components))
while len(components) > nSegs:
smallest = cap.argmin(components, itemgetter(0))
del (components[smallest])
assert (len(components) == nSegs)
log.log(cap.drawComponents(clone, components))
segments = map(lambda comp: comp[3], components)
log.log(cap.joinImagesH(segments))
segments = map(deRotate, segments)
log.log(cap.joinImagesH(segments))
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_SEGMENT)
return segments
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
image = removeLightColors(image)
log.log(image)
image = remapColors(image)
log.log(image)
image = smoothNoise2(image)
log.log(image)
image = cap.smoothNoise1(image)
log.log(image)
mask = getNoiseMask(image, 15, 4)
cv.Or(mask, findColor(image, myunkn), mask)
log.log(mask)
image = doInpaint(image, mask)
log.log(image)
image = sharpenColors(image)
log.log(image)
image = cap.repaintCCs(image, doRepaint=lambda comp, col: comp[0] <= 5 or comp[2][2] <= 2 or comp[2][3] <= 2)
log.log(image)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return image
def segment(image, addr, extras):
log = cap.logger(extras, image)
components = findComponents(image, log)
log.log(cap.drawComponents(image, components))
angles = map(lambda comp: findAngle(comp, log), components)
angles = filter(lambda angle: angle != 0.0 and abs(angle) <= 27.0, angles)
if len(angles) != 0:
angle = fsum(angles) / len(angles)
image = cap.doRotate(image, -angle, fillval=255, interpolation=cv.CV_INTER_NN)
log.log(image)
components = findComponents(image)
assert(len(components) <= nSegs)
log.log(cap.drawComponents(image, components))
#components = cap.spltCCs(components, cap.partsFromnSegs5(components), projRadius=5, thresh=2)
#components = filtCCs(components, (15, 15), 200, 0.2)
components = map(lambda comp: addBackground(comp, image, bgcolor=96), components)
segments = map(lambda comp: comp[3], components)
segments = map(removeBadBackground, segments)
log.log(cap.joinImagesH(segments))
segments = map(lambda seg: cap.smoothNoise1(seg, bgcolor=0), segments)
log.log(cap.joinImagesH(segments))
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_SEGMENT)
return segments
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
image = removeLightColors(image)
log.log(image)
image = remapColors(image)
log.log(image)
image = smoothNoise2(image)
log.log(image)
image = cap.smoothNoise1(image)
log.log(image)
mask = getNoiseMask(image, 15, 4)
cv.Or(mask, findColor(image, myunkn), mask)
log.log(mask)
image = doInpaint(image, mask)
log.log(image)
image = sharpenColors(image)
log.log(image)
image = cap.repaintCCs(image,
doRepaint=lambda comp, col: comp[0] <= 5 or comp[2][
2] <= 2 or comp[2][3] <= 2)
log.log(image)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return image
def preprocess(image, addr, extras):
log = cap.logger(extras, image)
image = cutLetters(image, 116, log)
log.log(image)
cap.processExtras(log.steps, addr, extras, cap.CAP_STAGE_PREPROCESS)
return image
def recognise(segments, addr, extras):
allParts = cap.partsFromnSegs5(segments)
result = splitRecogniseAll(segments, allParts, shiftRadius=4)
cap.processExtras([cap.joinImagesH(segments)], addr, extras, cap.CAP_STAGE_RECOGNISE)
return result
def recognise(segments, addr, extras):
allParts = cap.partsFromnSegs5(segments)
result = splitRecogniseAll(segments, allParts, shiftRadius=4)
cap.processExtras([cap.joinImagesH(segments)], addr, extras,
cap.CAP_STAGE_RECOGNISE)
return result