def addZW(inmats, weights):
mats = inmats.items()
outmat = sameMat(mats[0][1])
for key, mat in mats:
tmp = sameMat(mat)
cv.Scale(zscale(mat), tmp, weights[key])
cv.Add(outmat, tmp, outmat)
return outmat
def addW(inmats, weights):
mats = inmats.items()
outmat = sameMat(mats[0][1])
for key, mat in mats:
if not key in weights:
continue
tmp = sameMat(mat)
cv.Scale(mat, tmp, weights[key])
cv.Add(outmat, tmp, outmat)
return outmat
def sobel(inmat, ws = 7):
h = sameMat(inmat)
v = sameMat(inmat)
outmat = sameMat(inmat)
cv.Sobel(inmat, h, 1, 0, ws)
cv.Sobel(inmat, v, 0, 1, ws)
cv.Mul(h, h, h)
cv.Mul(v, v, v)
cv.Add(h, v, outmat)
cv.Pow(outmat, outmat, 0.5)
return outmat
def contrast(inmat, ws = 51):
sq = sameMat(inmat)
smth = sameMat(inmat)
outmat = sameMat(inmat)
cv.Mul(inmat, inmat, sq)
cv.Smooth(sq, sq, cv.CV_GAUSSIAN, ws, ws)
cv.Smooth(inmat, smth, cv.CV_GAUSSIAN, ws, ws)
cv.Mul(smth, smth, smth)
cv.Sub(sq, smth, outmat)
cv.Normalize(outmat, outmat, 0, 1, cv.CV_MINMAX)
cv.Pow(outmat, outmat, 0.5)
cv.Threshold(outmat, outmat, 0, 0, cv.CV_THRESH_TOZERO)
del smth, sq
return outmat
def contrast(inmat, ws = 41): # Former: 51, pixels per degree?
constrastLogger.debug("Kernel size for normal contrast: %s" % ws)
sq = sameMat(inmat)
smth = sameMat(inmat)
outmat = sameMat(inmat)
cv.Mul(inmat, inmat, sq)
cv.Smooth(sq, sq, cv.CV_GAUSSIAN, ws, ws)
cv.Smooth(inmat, smth, cv.CV_GAUSSIAN, ws, ws)
cv.Mul(smth, smth, smth)
cv.Sub(sq, smth, outmat)
cv.Normalize(outmat, outmat, 0, 1, cv.CV_MINMAX)
cv.Pow(outmat, outmat, 0.5)
cv.Threshold(outmat, outmat, 0, 0, cv.CV_THRESH_TOZERO)
del smth, sq
return outmat
def multiply(inmat, value):
outmat = sameMat(inmat)
cv.Scale(inmat, outmat, value)
return outmat
def smooth(inmat, ws = 51):
outmat = sameMat(inmat)
cv.Smooth(inmat, outmat, cv.CV_GAUSSIAN, ws, ws)
return outmat
cv.Scale(mat, tmp, weights[key])
cv.Add(outmat, tmp, outmat)
return outmat
def equalize(inmat):
mat = cv.CreateMat(inmat.rows, inmat.cols, cv.CV_8UC1)
cv.Normalize(inmat, inmat, 0, 255, cv.CV_MINMAX)
cv.Convert(inmat, mat)
cv.EqualizeHist(mat, mat)
return mat
def spatialbias(inmat, biasmat, (x, y), base=1.0, gain=1.0, bias_zero=None):
outmat = sameMat(inmat)
if bias_zero is not None:
ZPX, ZPY = bias_zero
else:
ZPX, ZPY = biasmat.cols / 2, biasmat.rows / 2
# extract bias source subrect
srcX = max(ZPX - x, 0)
srcY = max(ZPY - y, 0)
srcW = min(min(ZPX - x, 0) + inmat.cols, biasmat.cols - srcX)
srcH = min(min(ZPY - y, 0) + inmat.rows, biasmat.rows - srcY)
srcRect = cv.GetSubRect(biasmat, (srcX, srcY, srcW, srcH))
# bias in size and coordinates of target matrix
tarbias = sameMat(inmat)
cv.Set(tarbias, 0)
def smooth(inmat, ws = 41): # Former 51
smoothLogger.debug("Kernel size for smooth: %s" % ws)
outmat = sameMat(inmat)
cv.Smooth(inmat, outmat, cv.CV_GAUSSIAN, ws, ws) # a third parameter could adjust the SD of the gaussian!
# otherwise sigma is automatically calculated by 0.3 * (ws/2-1) + 0.8
return outmat