def crop(image, offset, size):
w, h = size
# If there will be a border, use CopyMakeBorder.
# Setting ROI, no border is created and resulting image is smaller
if offset[0]>0 or \
offset[1]>0 or \
offset[0]+cv.GetSize(image)[0]<w or \
offset[1]+cv.GetSize(image)[1]<h:
finalImg = cv.CreateImage((w, h), cv.IPL_DEPTH_8U, 3)
# offset may have negative values, if there will be a right/bottom border
useOffset = (max(0, offset[0]), max(0, offset[1]))
# Need to crop first as CopyMakeBorder will complain if the source is too big for the destination
# (The ROI is the opposite of the offset)
cv.SetImageROI(image, (-offset[0], -offset[1], w, h))
cv.CopyMakeBorder(image, finalImg, useOffset, GAP_BORDER)
return finalImg
else:
cv.SetImageROI(image, (-offset[0], -offset[1], w, h))
return image
def size_image(img, imgsize):
# check if we need to crop out ROI
roiWidth = img.width
roiHeight = img.height
if (img.width > imgsize[1]):
roiWidth = imgsize[1]
if (img.height > imgsize[0]):
roiHeight = imgsize[0]
roi = (0, 0, roiWidth, roiHeight)
cv.SetImageROI(img, roi)
imgTrim = cv.CreateImage((roi[2], roi[3]), img.depth, img.nChannels)
cv.Copy(img, imgTrim)
# check if we need to pad
padSize = 0
padSize = max(padSize, imgsize[0] - imgTrim.height)
padSize = max(padSize, imgsize[1] - imgTrim.width)
if padSize == 0: # no padding needed
return imgTrim
else:
padSize = int(round((padSize + .5) / 2.))
# copy make border
imgPad = cv.CreateImage(
(imgTrim.width + 2 * padSize, imgTrim.height + 2 * padSize),
img.depth, img.nChannels)
cv.CopyMakeBorder(imgTrim, imgPad, (0, 0), 0)
roi = (0, 0, imgsize[1], imgsize[0])
cv.SetImageROI(imgPad, roi)
imgFinal = cv.CreateImage((roi[2], roi[3]), img.depth, img.nChannels)
cv.Copy(imgPad, imgFinal)
return imgFinal
def smoothNoise1(image, bgcolor=255):
temp = cv.CreateImage((image.width + 2, image.height + 2), image.depth, image.nChannels)
result = cv.CreateImage(cv.GetSize(image), image.depth, image.nChannels)
cv.CopyMakeBorder(image, temp, (1, 1), 0, bgcolor)
for x in xrange(1, image.width + 1):
for y in xrange(1, image.height + 1):
if temp[y + 1, x] == temp[y - 1, x] and temp[y, x] != temp[y + 1, x]:
result[y - 1, x - 1] = temp[y + 1, x]
elif temp[y, x + 1] == temp[y, x - 1] and temp[y, x] != temp[y, x + 1]:
result[y - 1, x - 1] = temp[y, x + 1]
else:
result[y - 1, x - 1] = temp[y, x]
return result
def smooth_constborder(A, xwin=5, ywin=5, val=0):
""" Smooths A with a Gaussian kernel (with window size [XWIN,YWIN]),
handling the borders of A by using VAL as the intensity value used
for pixels outside of A.
Input:
IplImage A:
Output:
IplImage A_smoothed.
"""
wA, hA = cv.GetSize(A)
A_big = cv.CreateImage((wA + 2 * xwin, hA + 2 * ywin), A.depth, A.channels)
# Pass '0' as bordertype due to undocumented OpenCV flag IPL_BORDER_CONSTANT
# being 0. Wow!
cv.CopyMakeBorder(A, A_big, (xwin, ywin), 0, val)
cv.Smooth(A_big, A_big, cv.CV_GAUSSIAN, param1=xwin, param2=ywin)
cv.SetImageROI(A_big, (xwin, ywin, wA, hA))
return A_big
def smooth(I, xwin, ywin, bordertype=None, val=255.0):
""" Apply a gaussian blur to I, with window size [XWIN,YWIN].
If BORDERTYPE is 'const', then treat pixels that lie outside of I as
VAL (rather than what OpenCV defaults to).
Input:
IplImage I:
"""
w, h = cv.GetSize(I)
if bordertype == 'const':
Ibig = cv.CreateImage((w + 2 * xwin, h + 2 * ywin), I.depth,
I.channels)
cv.CopyMakeBorder(I, Ibig, (xwin, ywin), 0, value=val)
cv.SetImageROI(Ibig, (xwin, ywin, w, h))
else:
Ibig = I
Iout = cv.CreateImage((w, h), I.depth, I.channels)
cv.Smooth(Ibig, Iout, cv.CV_GAUSSIAN, param1=xwin, param2=ywin)
return Iout
def smoothNoise2(image):
b = 2
temp = cv.CreateImage((image.width + 4, image.height + 4), image.depth,
image.nChannels)
result = cv.CreateImage(cv.GetSize(image), image.depth, image.nChannels)
# IPL_BORDER_CONSTANT = 0
# IPL_BORDER_REPLICATE = 1
cv.CopyMakeBorder(image, temp, (b, b), 0, 255)
for x in xrange(b, image.width + b):
for y in xrange(b, image.height + b):
if temp[y + 1, x] == temp[y - 1, x] and \
temp[y + 2, x] == temp[y - 2, x] and \
temp[y + 1, x] == temp[y + 2, x] and \
temp[y, x] != temp[y + 1, x]:
result[y - b, x - b] = temp[y + 1, x]
elif temp[y, x + 1] == temp[y, x - 1] and \
temp[y, x + 2] == temp[y, x - 2] and \
temp[y, x + 1] == temp[y, x + 2] and \
temp[y, x] != temp[y, x + 1]:
result[y - b, x - b] = temp[y, x + 1]
else:
result[y - b, x - b] = temp[y, x]
return result
def opencvSaliency(self, scaledImageGray):
cvImageGray = cv.CreateMat(scaledImageGray.height,
scaledImageGray.width, cv.CV_32FC1)
cv.Convert(scaledImageGray, cvImageGray)
src = cvImageGray
dftWidth = cv.GetOptimalDFTSize(src.width - 1)
dftHeight = cv.GetOptimalDFTSize(src.height - 1)
real = cv.CreateMat(dftHeight, dftWidth, cv.CV_32FC1)
imaginary = cv.CreateMat(dftHeight, dftWidth, cv.CV_32FC1)
dft = cv.CreateMat(dftHeight, dftWidth, cv.CV_32FC2)
tmp = cv.GetSubRect(real, (0, 0, src.width, src.height))
cv.Copy(src, tmp)
cv.Zero(imaginary)
cv.Merge(real, imaginary, None, None, dft)
# do the fft
cv.DFT(dft, dft, cv.CV_DXT_FORWARD, src.height)
cv.Split(dft, real, imaginary, None, None)
cv.CartToPolar(real, imaginary, real, imaginary, 0)
cv.Log(real, real)
filtered = cv.CreateMat(dftHeight, dftWidth, cv.CV_32FC1)
cv.Copy(real, filtered)
cv.Smooth(filtered, filtered, cv.CV_BLUR)
cv.Sub(real, filtered, real, None)
cv.Exp(real, real)
cv.PolarToCart(real, imaginary, real, imaginary, 0)
#cv.PolarToCart( np.ones( shape=(dftHeight,dftWidth), dtype=np.float32 ), imaginary, real, imaginary,0 )
# do inverse fourier transform
cv.Merge(real, imaginary, None, None, dft)
cv.DFT(dft, dft, cv.CV_DXT_INV_SCALE, src.height)
cv.Split(dft, real, imaginary, None, None)
# get magnitude
cv.CartToPolar(real, imaginary, real, None, 0)
cv.Pow(real, real, 2.0)
FILTER_RAD = 3
IPL_BORDER_CONSTANT = 0
sfiltered = cv.CreateMat(real.height + FILTER_RAD * 2,
real.width + FILTER_RAD * 2, cv.CV_32FC1)
cv.CopyMakeBorder(real, sfiltered, (FILTER_RAD, FILTER_RAD),
IPL_BORDER_CONSTANT)
cv.Smooth(sfiltered, sfiltered, cv.CV_GAUSSIAN, 2 * FILTER_RAD + 1)
(min, max, minLoc, maxLoc) = cv.MinMaxLoc(sfiltered)
cv.ConvertScale(sfiltered, sfiltered, 1 / (max - min),
-min / (max - min))
# copy result to output image
tmp = cv.GetSubRect(sfiltered,
(FILTER_RAD, FILTER_RAD, src.width, src.height))
cv.Copy(tmp, cvImageGray)
#cvReleaseMat(&sfiltered);
#cvReleaseMat(&real);
#cvReleaseMat(&filtered);
#cvReleaseMat(&imaginary);
#cvReleaseMat(&dft);
saliencyMap = np.array(255.0 * np.array(cvImageGray), dtype=np.uint8)
return saliencyMap
def isolate_numbers(image, name='unnamed.jpg'):
h, w = image.shape
#MAX_WIDTH = w * 0.33
raw_im_cv = array2cv(image)
# Strip the black line on the bottom
try:
transposed = zip(*cv2array(raw_im_cv))
left_col = list(enumerate(reversed(transposed[2])))
right_col = list(enumerate(reversed(transposed[-2])))
findit = lambda a: a[0][0] if a[0][1][0] == 255 else findit(a[
1:]) # It just works!
h -= max(findit(left_col), findit(right_col))
cv.SetImageROI(raw_im_cv, (0, 0, w, h))
raw_im_cv = cv.CloneImage(raw_im_cv)
except IndexError:
pass
im_cv = cv.CreateImage((w + 6, h + 6), 8, 1)
im_cv_c = cv.CreateImage((w + 6, h + 6), 8, 3)
cv.Rectangle(im_cv, (0, 0), cv.GetSize(im_cv), cv.CV_RGB(255, 255, 255),
cv.CV_FILLED)
cv.CopyMakeBorder(raw_im_cv, im_cv, (3, 3), 0, (255, 255, 255))
cv.CvtColor(im_cv, im_cv_c, cv.CV_GRAY2RGB)
storage = cv.CreateMemStorage()
contours = cv.FindContours(im_cv,
storage,
mode=cv.CV_RETR_LIST,
method=cv.CV_CHAIN_APPROX_NONE,
offset=(0, 0))
if not contours:
return None
else:
cv.DrawContours(im_cv, contours, (0, 0, 0), (0, 0, 0), 7, -1)
rects = []
i = -1
while contours:
i += 1
storage2 = cv.CreateMemStorage(0)
hull = cv.ConvexHull2(contours, storage2, cv.CV_CLOCKWISE, 1)
if hull:
#cv.PolyLine(im_cv_c, [hull], 1, cv.RGB(0, 255, 0), 4, cv.CV_AA)
xmax, xmin, ymax, ymin = 0, w, 0, h
for x, y in list(hull):
xmax = max(xmax, x)
ymax = max(ymax, y)
xmin = min(xmin, x)
ymin = min(ymin, y)
height = (ymax - ymin)
width = (xmax - xmin)
if xmin < 5 or width < 50 or height < 50:
contours = contours.h_next()
continue
#cv.Rectangle(im_cv_c, (xmin, ymin), (xmax, ymax), cv.RGB(0, 255, 255), 4)
rects.append((xmin, ymin, xmax, ymax))
contours = contours.h_next()
rects = sorted(rects)
pointer = 0
while pointer < len(rects) - 1:
me = rects[pointer]
you = rects[pointer + 1]
right = me[2]
left = you[0]
if right > left:
me = (me[0], min(me[1],
you[1]), max(me[2],
you[2]), max(me[3], you[3]))
rects = rects[:pointer] + [me] + rects[pointer + 2:]
else:
pointer += 1
numbers = []
#i = 0
for xmin, ymin, xmax, ymax in rects:
#cv.Rectangle(im_cv_c, (xmin, ymin), (xmax, ymax), cv.RGB(128, 0, 128), 4)
cv.SetImageROI(im_cv_c, (xmin, ymin, xmax - xmin, ymax - ymin))
dst = cv.CreateImage((40, 40), 8, 3)
cv.Resize(im_cv_c, dst)
#cv.SaveImage('numbers/' + name.replace('.jpg', '.%d.jpg' % (i,)), dst)
_, tmp = tempfile.mkstemp('.png')
cv.SaveImage(tmp, dst)
dst = cv2.imread(tmp, 0)
os.unlink(tmp)
_, bw = cv2.threshold(dst, 80, 255,
cv.CV_THRESH_BINARY + cv.CV_THRESH_OTSU)
numbers.append(bw)
#i += 1
return numbers
def doCopyMakeBorder(image, border, fillval):
result = cv.CreateImage(
(image.width + border * 2, image.height + border * 2), image.depth,
image.nChannels)
cv.CopyMakeBorder(image, result, (border, border), 0, fillval)
return result
