


"""simple docstring"""







from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros
def _A		(		lowercase ,					lowercase	):







    """simple docstring"""
    a	,   a					=image.shape
    a					=cols - block_size[1] + 1
    a					=rows - block_size[0] + 1
    a					=zeros((dst_height * dst_width, block_size[1] * block_size[0])	)
    a					=0
    for i in range(0 ,					lowercase	):
        for j in range(0 ,					lowercase	):
            a					=ravel(image[i : i + block_size[0], j : j + block_size[1]]	)
            a					=window
            row += 1

    return image_array
def _A		(		lowercase ,					lowercase	):







    """simple docstring"""
    a	,   a					=image.shape[0], image.shape[1]
    a					=filter_kernel.shape[0]
    a					=k_size // 2
    # Pads image with the edge values of array.
    a					=pad(lowercase ,					lowercase ,					mode='''edge'''	)

    # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
    a					=imacol(lowercase ,					(k_size, k_size)	)

    #  turn the kernel into shape(k*k, 1)
    a					=ravel(lowercase	)
    # reshape and get the dst image
    a					=dot(lowercase ,					lowercase	).reshape(lowercase ,					lowercase	)
    return dst


if __name__ == "__main__":
       # read original image
       lowerCamelCase_     :     int    		=						imread(R"""../image_data/lena.jpg""")
       # turn image in gray scale value
       lowerCamelCase_     :     Union[str, Any]    		=						cvtColor(img, COLOR_BGR2GRAY)
       # Laplace operator
       lowerCamelCase_     :     Optional[int]    		=						array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
       lowerCamelCase_     :     str    		=						img_convolve(gray, Laplace_kernel).astype(uinta)
       imshow("""Laplacian""", out)
       waitKey(0)



"""simple docstring"""







from cva import destroyAllWindows, imread, imshow, waitKey
def _A		(		lowercase ,					lowercase	):







    """simple docstring"""
    a	,   a					=img.shape[0], img.shape[1]

    def to_grayscale(lowercase ,					lowercase ,					lowercase	):
        return 0.2126 * red + 0.587 * green + 0.114 * blue

    def normalize(lowercase	):
        return min(lowercase ,					2_55	)

    for i in range(lowercase	):
        for j in range(lowercase	):
            a					=int(to_grayscale(*img[i][j]	)	)
            a					=[
                normalize(lowercase	),
                normalize(greyscale + factor	),
                normalize(greyscale + 2 * factor	),
            ]

    return img


if __name__ == "__main__":
       # read original image
       lowerCamelCase_     :     Any    		=						{
           percentage: imread("""image_data/lena.jpg""", 1) for percentage in (1_0, 2_0, 3_0, 4_0)
       }

       for percentage, img in images.items():
              make_sepia(img, percentage)

       for percentage, img in images.items():
              imshow(F'Original image with sepia (factor: {percentage})', img)

       waitKey(0)
       destroyAllWindows()