def shared_roi(*images):
'''Return the part of the region of interest that all arguments share.
Returns None if they don't share one rect all together.'''
roi = Rectangle.from_cv_rect(cv.GetImageROI(images[0]))
for image in images[1:]:
roi = Rectangle.from_cv_rect(cv.GetImageROI(image)).union(roi)
return roi.as_cv_rect() if roi.is_real else None
def displayDepth(name, dep, imshow=cv.ShowImage):
width = cv.GetImageROI(dep)[2]
height = cv.GetImageROI(dep)[3]
disp = cv.CloneImage(dep)
cv.ConvertScale(disp, disp, 10);
imshow(name, disp)
del disp
def cvCmpS(src, scalar, dst, code):
width1 = cv.GetImageROI(src)[2]
height1 = cv.GetImageROI(src)[3]
width2 = cv.GetImageROI(dst)[2]
height2 = cv.GetImageROI(dst)[3]
if not (width1 == width2 and height1 == height2):
print 'cvCmpS src, dst size error'
print (width1, height1), (width2, height2)
cv.CmpS(src, scalar, dst, code)
def cvCopy(src, dst, mask=None):
width1 = cv.GetImageROI(src)[2]
height1 = cv.GetImageROI(src)[3]
width2 = cv.GetImageROI(dst)[2]
height2 = cv.GetImageROI(dst)[3]
if not (src.depth == dst.depth and width1 == width2 and height1 == height2):
print 'cvCopy argument error'
print (width1, height1, src.depth), (width2, height2, dst.depth)
raise RuntimeError
cv.Copy(src, dst, mask)
return
def calibrate(self, img, mask_range = (50, 100)):
# mask: ignore pixels that are really close or far away, like the
# Nao (close, low values) and kinect noise (far far away, high values)
_, _, width, height = cv.GetImageROI(img)
mask = cv.CreateImage((width, height), cv.IPL_DEPTH_8U, 1)
cv.InRangeS(img, mask_range[0], mask_range[1], mask)
# using the mask, create a new image containing only the pixels of
# interest.
self.base_img = cv.CreateImage((width, height), cv.IPL_DEPTH_8U, 1)
cv.SetImageROI(self.base_img, cv.GetImageROI(img))
# get the minimum value, and subtract that from all pixels so only
# the difference in depth in the image remains.
minimum, _, _, _ = cv.MinMaxLoc(img, mask)
cv.SubS(img, minimum, self.base_img)
def render_with_histogram(img):
'''Just a utility to draw a grayscale histogram next to an image.'''
_, _, width, height = cv.GetImageROI(img)
canvas = cv.CreateImage((width + 200, max(height, 255)), cv.IPL_DEPTH_8U, 1)
cv.Rectangle(canvas, (width, 0), (width + 200, height), (0), cv.CV_FILLED)
cv.SetImageROI(canvas, (0, 0, width, height))
cv.Copy(img, canvas)
cv.SetImageROI(canvas, (width, 0, 200, canvas.height))
hist = cv.CreateHist([255], cv.CV_HIST_ARRAY, [(0,255)], 1)
cv.CalcHist([img], hist)
values = [cv.QueryHistValue_1D(hist, n) for n in range(255)]
max_value = max(values)
for n, value in enumerate(values):
cv.Rectangle(canvas,
(0, n),
(int((value / max_value) * 200), n + 1),
(255), cv.CV_FILLED)
cv.SetImageROI(canvas, (0, 0, canvas.width, canvas.height))
return canvas
def filter(self, input_img):
original_input_roi = cv.GetImageROI(input_img)
filter_roi = shared_roi(input_img, self.base_img)
if not filter_roi:
raise Exception("input image and training image do not share a region of interest")
cv.SetImageROI(input_img, filter_roi)
# and that is it! Just subtract the difference we calibrated on from
# the normal image, and tada!
input_roi = cv.GetImageROI(input_img)
cv.SetImageROI(self.base_img, input_roi)
cv.Sub(input_img, self.base_img, input_img)
cv.SetImageROI(input_img, original_input_roi)
def cvConvertScale(src, dst, scale=None, offs=None):
width1 = cv.GetImageROI(src)[2]
height1 = cv.GetImageROI(src)[3]
width2 = cv.GetImageROI(dst)[2]
height2 = cv.GetImageROI(dst)[3]
if not (width1 == width2 and height1 == height2 and src.nChannels == dst.nChannels):
print 'cvConvertScale argument error'
print (width1, height1, src.nChannels), (width2, height2, dst.nChannels)
raise RuntimeError
if scale and offs:
cv.ConvertScale(src, dst, scale, offs)
elif scale:
cv.ConvertScale(src, dst, scale)
elif offs:
cv.ConvertScale(src, dst, offset = offs)
else:
cv.ConvertScale(src, dst)
def clone_color_image(img):
'''Create a new color image based on a grayscale image'''
roi = cv.GetImageROI(img)
color = cv.CreateImage((img.width, img.height), img.depth, 4)
cv.SetImageROI(color, roi)
empty = cv.CreateImage((img.width, img.height), img.depth, 1)
cv.SetImageROI(empty, roi)
cv.Merge(img, img, img, empty, color)
return color
def cvAnd(A, B, dst):
width1 = cv.GetImageROI(A)[2]
height1 = cv.GetImageROI(A)[3]
width2 = cv.GetImageROI(B)[2]
height2 = cv.GetImageROI(B)[3]
width3 = cv.GetImageROI(dst)[2]
height3 = cv.GetImageROI(dst)[3]
if not (width1 == width3 and height1 == height3 and A.depth == dst.depth):
print 'cvAnd argument error: size, type of src1, dst'
print (width1, height1, A.depth), (width3, height3, dst.depth)
raise RuntimeError
cv.And(A,B,dst)
