def NDVIFilter(image):
''' NDVI Filter '''
original = convertQImageToMat(image)
lowerLimit = 5
# First, make containers
oldHeight, oldWidth = original[:, :, 0].shape
ndviImage = np.zeros((oldHeight, oldWidth, 3),
np.uint8) # make a blank RGB image
red = (original[:, :, 2]).astype('float')
blue = (original[:, :, 0]).astype('float')
# Perform NDVI calculation
summ = red + blue
summ[
summ <
lowerLimit] = lowerLimit # do some saturation to prevent low intensity noise
ndvi = (((red - blue) / (summ) + 1) * 127).astype('uint8') # the index
redSat = (ndvi - 128) * 2 # red channel
bluSat = ((255 - ndvi) - 128) * 2 # blue channel
redSat[ndvi < 128] = 0 # if the NDVI is negative, no red info
bluSat[ndvi >= 128] = 0 # if the NDVI is positive, no blue info
# Red Channel
ndviImage[:, :, 2] = redSat
# Blue Channel
ndviImage[:, :, 0] = bluSat
# Green Channel
ndviImage[:, :, 1] = 255 - (bluSat + redSat)
return convertMatToQImage(ndviImage)
def EdgeFilter(image, sigma=0.33):
''' Edge Image Filter '''
gray = convertQImageToMat(image)
v = np.median(gray)
lower = int(max(0, (1.0 - sigma) * v))
upper = int(min(255, (1.0 + sigma) * v))
canny = Canny(gray, lower, upper)
return convertMatToQImage(canny)
def EdgeFilter(image, sigma=0.33):
"""Edge Image Filter
@type image: QImage
@param image:
@return: QImage
"""
gray = convertQImageToMat(image)
v = np.median(gray)
lower = int(max(0, (1.0 - sigma) * v))
upper = int(min(255, (1.0 + sigma) * v))
canny = Canny(gray, lower, upper)
return convertMatToQImage(canny)
def AutoContrastFilter(image):
''' Auto Contrast Image Filter '''
img = convertQImageToMat(image)
clahe = createCLAHE(clipLimit=4., tileGridSize=(20, 20))
# convert from BGR to LAB color space
lab = cvtColor(img, COLOR_BGR2LAB)
l, a, b = split(lab) # split on 3 different channels
l2 = clahe.apply(l) # apply CLAHE to the L-channel
lab = merge((l2, a, b)) # merge channels
invert = cvtColor(lab, COLOR_LAB2BGR) # convert from LAB to BGR
return convertMatToQImage(invert)
def EdgeFilter(image):
''' Edge Image Filter '''
gray = convertQImageToMat(VideoFilters.GrayFilter(image))
canny = Canny(gray, 100, 150)
return convertMatToQImage(canny)
