def gaussianBlur(image, filterSize=43, sigma=opencvFilt2sigma(43)):
"""Blur an image with a particular strength filter.
Default is 43, 139 gives a very strong blur, but takes a while
"""
# Carry out the filter operation
cv.cvSmooth(image, image, cv.CV_GAUSSIAN, filterSize, 0, sigma)
return image
def gaussianBlur(image, filterSize=43, sigma=opencvFilt2sigma(43)):
"""Blur an image with a particular strength filter.
Default is 43, 139 gives a very strong blur, but takes a while
"""
# Carry out the filter operation
cv.cvSmooth(image, image, cv.CV_GAUSSIAN, filterSize, 0, sigma)
return image
def mlGaussianBlur(image):
"""Method using code from Sturla on the [email protected]"""
img = array(image)
sigma = opencvFilt2sigma(43.0)
gain = gaussian2D(np.ones(image.shape[0:2]), sigma) # corrects edges
for i in range(3):
img[:, :, i] = gaussian2D(img[:, :, i], sigma) / gain
return img
def mlGaussianBlur(image):
"""Method using code from Sturla on the [email protected]"""
img = array(image)
sigma = opencvFilt2sigma(43.0)
gain = gaussian2D(np.ones(image.shape[0:2]), sigma) # corrects edges
for i in range(3):
img[:,:,i] = gaussian2D(img[:,:,i], sigma) / gain
return img
def gaussianBlur3Way(np_image, sigma=opencvFilt2sigma(43.0)):
"""Blur an image with scipy using 3 seperate gaussian filters
This is exactly equivalent to the above function"""
r = ndimage.filters.gaussian_filter(np_image[:,:,0], sigma=(sigma, sigma))
g = ndimage.filters.gaussian_filter(np_image[:,:,1], sigma=(sigma, sigma))
b = ndimage.filters.gaussian_filter(np_image[:,:,2], sigma=(sigma, sigma))
return array([r,g,b]).transpose((1,2,0))
def gaussianBlur3Way(np_image, sigma=opencvFilt2sigma(43.0)):
"""Blur an image with scipy using 3 seperate gaussian filters
This is exactly equivalent to the above function"""
r = ndimage.filters.gaussian_filter(np_image[:, :, 0],
sigma=(sigma, sigma))
g = ndimage.filters.gaussian_filter(np_image[:, :, 1],
sigma=(sigma, sigma))
b = ndimage.filters.gaussian_filter(np_image[:, :, 2],
sigma=(sigma, sigma))
return array([r, g, b]).transpose((1, 2, 0))
@scipyFromOpenCV
def mlGaussianBlur(image):
"""Method using code from Sturla on the [email protected]"""
img = array(image)
sigma = opencvFilt2sigma(43.0)
gain = gaussian2D(np.ones(image.shape[0:2]), sigma) # corrects edges
for i in range(3):
img[:, :, i] = gaussian2D(img[:, :, i], sigma) / gain
return img
########
sigma = opencvFilt2sigma(43.0)
@scipyFromOpenCV
def gaussianBlur(np_image):
"""Blur an image with scipy"""
result = ndimage.filters.gaussian_filter(np_image,
sigma=(sigma, sigma, 0),
order=0,
mode='reflect')
return result
def testGaussianBlur():
"""Test that the guassian blur function gives the exact same output
return tmp[:n,:m]
@scipyFromOpenCV
def mlGaussianBlur(image):
"""Method using code from Sturla on the [email protected]"""
img = array(image)
sigma = opencvFilt2sigma(43.0)
gain = gaussian2D(np.ones(image.shape[0:2]), sigma) # corrects edges
for i in range(3):
img[:,:,i] = gaussian2D(img[:,:,i], sigma) / gain
return img
########
sigma = opencvFilt2sigma(43.0)
@scipyFromOpenCV
def gaussianBlur(np_image):
"""Blur an image with scipy"""
result = ndimage.filters.gaussian_filter(np_image,
sigma=(sigma, sigma, 0),
order=0,
mode='reflect'
)
return result
def testGaussianBlur():
"""Test that the guassian blur function gives the exact same output