async def blur(self, radius, sigma=0):
if sigma == 0:
sigma = radius
if radius > MAX_RADIUS:
radius = MAX_RADIUS
matrix, matrix_size = self.generate_1d_matrix(sigma, radius)
mode, data = self.engine.image_data_as_rgb()
imgdata = _convolution.apply(
mode,
data,
self.engine.size[0],
self.engine.size[1],
matrix,
matrix_size,
True,
)
imgdata = _convolution.apply(
mode,
imgdata,
self.engine.size[0],
self.engine.size[1],
matrix,
1,
True,
)
self.engine.set_image_data(imgdata)
def blur(self, radius, sigma=0):
if sigma == 0:
sigma = radius
if radius > MAX_RADIUS:
raise RuntimeError("Radius too large, maximum allowed value is %d" % MAX_RADIUS)
matrix, matrix_size = self.generate_1d_matrix(sigma, radius)
imgdata = _convolution.apply(self.engine.get_image_mode(), self.engine.get_image_data(), self.engine.size[0], self.engine.size[1], matrix, matrix_size, True)
imgdata = _convolution.apply(self.engine.get_image_mode(), imgdata, self.engine.size[0], self.engine.size[1], matrix, 1, True)
self.engine.set_image_data(imgdata)
def apply_blur(mode, data, size, radius, sigma=0):
if sigma == 0:
sigma = radius
radius = min(radius, MAX_RADIUS)
matrix, matrix_size = generate_1d_matrix(sigma, radius)
data = _convolution.apply(
mode, data, size[0], size[1], matrix, matrix_size, True
)
return _convolution.apply(mode, data, size[0], size[1], matrix, 1, True)
def blur(self, radius, sigma=0):
if sigma == 0:
sigma = radius
if radius > MAX_RADIUS:
radius = MAX_RADIUS
matrix, matrix_size = self.generate_1d_matrix(sigma, radius)
mode, data = self.engine.image_data_as_rgb()
imgdata = _convolution.apply(mode, data, self.engine.size[0], self.engine.size[1], matrix, matrix_size, True)
imgdata = _convolution.apply(mode, imgdata, self.engine.size[0], self.engine.size[1], matrix, 1, True)
self.engine.set_image_data(imgdata)
def convolution(self, matrix, columns, should_normalize=True):
matrix = tuple(matrix.split(';'))
mode, data = self.engine.image_data_as_rgb()
imgdata = _convolution.apply(mode, data, self.engine.size[0],
self.engine.size[1], matrix, columns,
should_normalize)
self.engine.set_image_data(imgdata)
def convolution(self, matrix, columns, should_normalize=True):
matrix = tuple(matrix.split(';'))
mode, data = self.engine.image_data_as_rgb()
imgdata = _convolution.apply(mode, data, self.engine.size[0], self.engine.size[1], matrix, columns, should_normalize)
self.engine.set_image_data(imgdata)
def convolution(self, matrix, columns, should_normalize=True):
matrix = tuple(matrix.split(';'))
imgdata = _convolution.apply(self.engine.get_image_mode(), self.engine.get_image_data(), self.engine.size[0], self.engine.size[1], matrix, columns, should_normalize)
self.engine.set_image_data(imgdata)
