def blurriness(img):
from PIL.ImageFilter import Kernel
from PIL.ImageStat import Stat
lap = Kernel((3, 3), [0, 1, 0, 1, -4, 1, 0, 1, 0])
img.copy().filter(lap)
img_stat = Stat(img)
return img_stat.var
def detect_edge(self, source_image, target_image):
cie = self._cie_image.convert('L')
kernel = Kernel((3, 3), (0, -1, 0, -1, 4, -1, 0, -1, 0), 1, 1)
edges = cie.filter(kernel)
r, _, b = target_image.split()
target_image = Image.merge(target_image.mode, [r, edges, b])
return target_image
def detect_edge(self, cie_image):
return cie_image.filter(Kernel((3, 3), (0, -1, 0, -1, 4, -1, 0, -1, 0), 1, 1))
def make_kernel(matrix: list, **kwargs) -> Kernel:
matrix = np.array(matrix)
assert notEmpty(matrix), 'Empty kernel'
n, m = (len(matrix), len(matrix[0]))
return Kernel(size=(n, m), kernel=matrix.flatten(), **kwargs)