def imageTransform(image, maskImage, T):
height, width = len(image), len(image[0])
centreX, centreY = width/2, height/2
sImage = createImageRGB(width, height)
for y, x in itertools.product(range(0, height-1), range(0, width-1)):
# Alpha and colour
alpha = maskImage[y,x]/256.0
if alpha == 0:
continue
rgb = (image[y,x]/4.0 + image[y+1,x+1]/4.0 + image[y+1,x]/4.0 + \
image[y,x+1]/4.0) * alpha
# Transform
cx, cy = x - centreX, y - centreY
p0z = T[2][0] * cx + T[2][1] * cy + T[2][2]
p1z = T[2][0] * (cx+1) + T[2][1] * cy + T[2][2]
p2z = T[2][0] * (cx+1) + T[2][1] * (cy+1) + T[2][2]
if p0z != 0 and p1z != 0 and p2z !=0:
p0x = int((T[0][0] * cx + T[0][1] * cy + T[0][2]) / p0z + centreX)
p0y = int((T[1][0] * cx + T[1][1] * cy + T[1][2]) / p0z + centreY)
p1x = int((T[0][0] * (cx+1) + T[0][1] * cy + T[0][2]) / p1z + centreX)
p1y = int((T[1][0] * (cx+1) + T[1][1] * cy + T[1][2]) / p1z + centreY)
p2x = int((T[0][0] * (cx+1) + T[0][1] * (cy+1) + T[0][2]) / p2z + centreX)
p2y = int((T[1][0] * (cx+1) + T[1][1] * (cy+1) + T[1][2]) / p2z + centreY)
# Fill output image
v1, v2 = [p1x - p0x, p1y - p0y], [p2x - p0x, p2y - p0y]
lv1 = max(.001,sqrt(v1[0]*v1[0] + v1[1]*v1[1]))
lv2 = max(.001,sqrt(v2[0]*v2[0] + v2[1]*v2[1]))
v1N = [v1[0]/lv1, v1[1]/lv1]
v2N = [v2[0]/lv2, v2[1]/lv2]
for dV1, dV2 in itertools.product(range(0, int(lv1)+1), range(0, int(lv2)+1)):
a,b = int(p0x + dV1 * v1N[0] + dV2 * v2N[0]), int(p0y + dV1 * v1N[1] + dV2 * v2N[1])
if a>0 and a < width and b > 0 and b < height:
sImage[b,a] = rgb
return sImage
def getPointColours(xy, mask, image):
nfaces = len(xy)
height = len(image)
width = len(image[0])
colourImages = [ ]
for faceNum in range(0, nfaces):
face = xy[faceNum]
npts = len(face)
colours = createImageRGB(npts, npts)
for a,b in itertools.product(range(0, npts-1), range(0, npts-1)):
y,x = face[a][b][1], face[a][b][0]
if y>0 and y<height and x>0 and x<width:
alpha = mask[y,x] / 256.0
if alpha > 0.0:
c = image[y,x]
colours[a,b] = [alpha*c[0],alpha*c[1],alpha*c[2]]
colourImages.append(colours)
return colourImages
D = dc / 255.0 + (m / regionSide) * ds
if D < minD[0]:
minD = [D, wy, wx]
[_, minY, minX] = minD
newRegionColour[minY, minX] += colour
newRegionPos[minY, minX] += [y, x]
newRegionSize[minY, minX] += 1
regionsID[y, x] = [minY, minX]
# Update regions
for x, y in itertools.product(range(0, regW), range(0, regH)):
if newRegionSize[y, x] > 0:
regionPos[y, x] = newRegionPos[y, x] / newRegionSize[y, x]
regionColour[y, x] = newRegionColour[y, x] / newRegionSize[y, x]
# Show regions
resultRegions = createImageRGB(width, height)
for x, y in itertools.product(range(0, width), range(0, height)):
border = False
for wx, wy in itertools.product(range(x, x + 2), range(y, y + 2)):
if wy >= 0 and wy < height and wx >= 0 and wx < width:
if regionsID[y, x, 0] != regionsID[wy, wx, 0] or regionsID[
y, x, 1] != regionsID[wy, wx, 1]:
border = True
if border:
resultRegions[y, x] = [255, 255, 255]
else:
[h, w] = regionsID[y, x]
resultRegions[y, x] = regionColour[h, w]
showImageRGB(resultRegions)
sigma = 4.0
# Read image into array
inputImage, width, height = imageReadRGB(pathToDir + imageName)
# Show input image
showImageRGB(inputImage)
# Three float array to store colors to be used in the surface plot
colorsRGB = createImageF(histSize, histSize, 3)
# Quantization scale
colourScale = 256.0 / histSize
# Create region image and histogram
regionImage = createImageRGB(2 * regionRadius[0], 2 * regionRadius[1])
histogram = createImageF(histSize, histSize)
sumValue = 0
for deltaX, deltaY in itertools.product(
range(-regionRadius[0], regionRadius[0]),
range(-regionRadius[1], regionRadius[1])):
x, y = position[0] + deltaX, position[1] + deltaY
px, py = deltaX + regionRadius[0], deltaY + regionRadius[1]
if x > 0 and y > 0 and x < width and y < height:
regionImage[py, px] = inputImage[y, x]
w = exp(-(deltaX * deltaX + deltaY * deltaY) / (2 * sigma * sigma))
rgb = inputImage[y, x] / 256.0
s = [.4, 0.8, 0.8, 100.0, 0.0] # Angle, scaleXY, translationXY
T = [[ s[1]*cos(s[0]), s[1]*sin(s[0]), s[3]], \
[ -s[2]*sin(s[0]), s[2]*cos(s[0]), s[4]], \
[0 ,0, 1]]
if transformationType == "Affine":
# Affine transformation
T = [[ .8, .1, 100], \
[ -.2, 1, 0], \
[0 ,0, 1]]
if transformationType == "Homography":
# Homography
T = [[ .8, 0, 100], \
[ .2,1, 0], \
[.0005 ,-0.0005 , 1.2]]
tImage = createImageRGB(width, height)
for y, x in itertools.product(range(0, height - 1), range(0, width - 1)):
# Alpha and colour
alpha = maskImage[y, x] / 256.0
if alpha == 0:
continue
rgb = (inputImage[y,x]/4.0 + inputImage[y+1,x+1]/4.0 + \
inputImage[y+1,x]/4.0 + inputImage[y,x+1]/4.0) * alpha
# Transform
cx, cy = x - centreX, y - centreY
p0z = T[2][0] * cx + T[2][1] * cy + T[2][2]
p1z = T[2][0] * (cx + 1) + T[2][1] * cy + T[2][2]
p2z = T[2][0] * (cx + 1) + T[2][1] * (cy + 1) + T[2][2]
if p0z != 0 and p1z != 0 and p2z != 0: