Пример #1
0
def split_image_into_sudoku_pieces_adaptive_global(image, otsu_local=False, apply_gaussian=False):
    L = image.shape[0]
    d = int(np.ceil(L / 9))
    dd = d // 5
    output = []
    if apply_gaussian:
        image = gaussian_filter(image, sigma=1.0)
    if not otsu_local:
        image = to_binary_adaptive(image)
    for k in range(9):
        this_row = []
        start_row_i = max([k * d - dd, 0])
        stop_row_i = min([(k + 1) * d + dd, L])
        for kk in range(9):
            start_col_i = max([kk * d - dd, 0])
            stop_col_i = min([(kk + 1) * d + dd, L])
            i = image[start_row_i:stop_row_i, start_col_i:stop_col_i].copy()
            if otsu_local:
                i = to_binary_otsu(i)
            i = binary_opening(i)
            i = to_binary_otsu(i)
            if apply_gaussian:
                i = to_binary_otsu(binary_dilation(i))
            this_row.append(i)
        output.append(this_row)
    return output, image
Пример #2
0
def get_centered_blob(img, border_size=1):
    img = to_binary_otsu(img)
    blob = _get_most_centered_blob(img)
    if blob is None:
        blob = _get_most_centered_blob(to_binary_otsu(binary_dilation(img)))
        if blob is None:
            return None
    blob_img = add_border(blob, (28, 28), border_size=border_size)
    blob_img = to_binary_otsu(blob_img)

    return blob_img
Пример #3
0
def get_centered_blob(img, border_size=1):
    img = to_binary_otsu(img)
    blob = _get_most_centered_blob(img)
    if blob is None:
        blob = _get_most_centered_blob(to_binary_otsu(binary_dilation(img)))
        if blob is None:
            return None
    blob_img = add_border(blob, (28, 28), border_size=border_size)
    blob_img = to_binary_otsu(blob_img)

    return blob_img