এসসিপি

from scipy import ndimage

data = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]

result = ndimage.gaussian_filter(data, sigma=1)

print(result)

from scipy import ndimage

data = [
    [1, 2, 3],
    [4, 100, 6],
    [7, 8, 9]
]

result = ndimage.median_filter(data, size=3)

print(result)

from scipy import ndimage

data = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]

result = ndimage.uniform_filter(data, size=3)

print(result)

from scipy import ndimage

data = [
    [1, 1, 1],
    [1, 5, 1],
    [1, 1, 1]
]

result = ndimage.sobel(data)

print(result)

from scipy import ndimage

data = [
    [1, 2, 3],
    [4, 8, 6],
    [7, 8, 9]
]

result = ndimage.prewitt(data)

print(result)

from scipy import ndimage

data = [
    [1, 1, 1],
    [1, 5, 1],
    [1, 1, 1]
]

result = ndimage.laplace(data)

print(result)

from scipy import ndimage

data = [
    [1, 2, 1],
    [2, 4, 2],
    [1, 2, 1]
]

kernel = [
    [0, 1, 0],
    [1, 2, 1],
    [0, 1, 0]
]

result = ndimage.convolve(data, kernel)

print(result)

from scipy import ndimage

data = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]

kernel = [
    [1, 0],
    [0, -1]
]

result = ndimage.correlate(data, kernel)

print(result)

from scipy import ndimage

data = [
    [1, 2],
    [3, 4],
    [5, 6]
]

result = ndimage.rotate(
    data,
    90
)

print(result)

from scipy import ndimage

data = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]

result = ndimage.shift(
    data,
    [1, 1]
)

print(result)

from scipy import ndimage

data = [
    [1, 2],
    [3, 4]
]

result = ndimage.zoom(data, 2)

print(result)

from scipy import ndimage

data = [
    [1, 2],
    [3, 4]
]

matrix = [
    [1, 0],
    [0, 1]
]

result = ndimage.affine_transform(
    data,
    matrix
)

print(result)

from scipy import ndimage

data = [
    [1, 2],
    [3, 4]
]

coordinates = [
    [0, 1],
    [0, 1]
]

result = ndimage.map_coordinates(
    data,
    coordinates,
    order=1
)

print(result)

from scipy import ndimage

data = [
    [1, 0, 0],
    [0, 1, 1],
    [0, 0, 1]
]

result, count = ndimage.label(data)

print(result)
print(count)

from scipy import ndimage

data = [
    [1, 0, 0],
    [0, 2, 2],
    [0, 0, 2]
]

labels, count = ndimage.label(data)

result = ndimage.find_objects(labels)

print(result)

from scipy import ndimage

data = [
    [0, 0, 0],
    [0, 1, 0],
    [0, 0, 0]
]

result = ndimage.binary_dilation(data)

print(result)

from scipy import ndimage

data = [
    [1, 1, 1],
    [1, 1, 1],
    [1, 1, 1]
]

result = ndimage.binary_erosion(data)

print(result)

from scipy import ndimage

data = [
    [0, 1, 0],
    [1, 1, 1],
    [0, 1, 0]
]

result = ndimage.binary_opening(data)

print(result)

from scipy import ndimage

data = [
    [1, 1, 1],
    [1, 0, 1],
    [1, 1, 1]
]

result = ndimage.binary_closing(data)

print(result)