def FT3(im,
test=1,
phase2=False,
upperrange=1.1,
lowerrange=0.45): #AverageBlur
img = np.array(im)
if test != 0:
img = img[:, :, :3]
kernel = np.ones((3, 3), np.float32) / 25
dst = cv2.blur(img, (5, 5), 0)
snr2 = float(signaltonoise(dst, axis=None))
index = img == dst
dst2 = np.abs(img - dst)
snr3 = float(signaltonoise(dst2, axis=None))
if phase2 == True:
if snr3 < upperrange and snr3 > lowerrange:
return im
return []
def FT1(im,
test=1,
phase2=False,
upperrange=0.7,
lowerrange=0.15): #medianblur
img = np.array(im)
if test != 0:
img = img[:, :, :3]
kernel = np.ones((3, 3), np.float32) / 25
dst = cv2.medianBlur(img, 25)
snr2 = float(signaltonoise(dst, axis=None))
index = img == dst
dst2 = np.abs(img - dst)
snr3 = float(signaltonoise(dst2, axis=None))
if phase2 == True:
if snr3 < upperrange and snr3 > lowerrange:
return im
return []
def FT12(im, test=1, phase2=False, upperrange=0.6, lowerrange=0.15): #TopHat
img = np.array(im)
if test != 0:
img = img[:, :, :3]
try:
img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
except:
img = img
kernel = np.ones((3, 3), np.uint8)
dst = cv2.morphologyEx(img, cv2.MORPH_TOPHAT, kernel)
snr2 = float(signaltonoise(dst, axis=None))
index = img == dst
dst2 = np.abs(img - dst)
snr3 = float(signaltonoise(dst2, axis=None))
if phase2 == True:
if snr3 < upperrange and snr3 > lowerrange:
return im
return []
def FT8(im, test=1, phase2=False, upperrange=0.7, lowerrange=0.25): #Dialte
img = np.array(im)
if test != 0:
img = img[:, :, :3]
try:
img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
except:
img = img
kernel = np.ones((5, 5), np.uint8)
dst = cv2.dilate(img, kernel, iterations=1)
snr2 = float(signaltonoise(dst, axis=None))
index = img == dst
dst2 = np.abs(img - dst)
snr3 = float(signaltonoise(dst2, axis=None))
if phase2 == True:
if snr3 < upperrange and snr3 > lowerrange:
return im
return []
def FT4(im,
test=1,
phase2=False,
upperrange=1.1,
lowerrange=0.3): #Bilateral blur
img = np.array(im)
if test != 0:
img = img[:, :, :3]
try:
img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
except:
img = img
dst = cv2.bilateralFilter(img, 6, 75, 75)
snr2 = float(signaltonoise(dst, axis=None))
index = img == dst
dst2 = np.abs(img - dst)
snr3 = float(signaltonoise(dst2, axis=None))
if phase2 == True:
if snr3 < upperrange and snr3 > lowerrange:
return im
return []
def FT6(im,
test=1,
phase2=False,
upperrange=1.3,
lowerrange=0.7): #AdditivePoissonNoise
img = np.array(im)
if test != 0:
img = img[:, :, :3]
aug = iaa.AdditiveGaussianNoise(loc=0, scale=0.1 * 255)
im_arr = aug.augment_image(img)
dst2 = np.abs(img - np.array(im_arr))
snr3 = float(signaltonoise(dst2, axis=None))
if phase2 == True:
if snr3 < upperrange and snr3 > lowerrange:
return im
return []
def FT5(im,
test=1,
phase2=False,
upperrange=1.3,
lowerrange=0.7): #AdditivePoissonNoise
img = np.array(im)
if test != 0:
img = img[:, :, :3]
kernel = np.ones((3, 3), np.float32) / 25
aug = iaa.AdditivePoissonNoise(lam=10.0, per_channel=True)
im_arr = aug.augment_image(img)
dst2 = np.abs(img - np.array(im_arr))
snr3 = float(signaltonoise(dst2, axis=None))
if phase2 == True:
if snr3 < upperrange and snr3 > lowerrange:
return im
return []