utils.py 文件源码

def grid_to_adjacency_matrix(grid, neighborhood=8):
    """Convert a boolean grid where 0's express holes and 1's connected pixel
    into a sparse adjacency matrix representing the grid-graph.
    Neighborhood for each pixel is calculated from its 4 or 8 more immediate
    surrounding neighbors (defaults to 8)."""
    coords = np.argwhere(grid)
    coords_x = coords[:, 0]
    coords_y = coords[:, 1]
    # lil is the most performance format to build a sparse matrix iteratively
    matrix = sparse.lil_matrix((0, coords.shape[0]), dtype=np.uint8)
    if neighborhood == 4:
        for px, py in coords:
            row = (((px == coords_x) & (np.abs(py - coords_y) == 1)) |
                   ((np.abs(px - coords_x) == 1) & (py == coords_y)))
            matrix = sparse.vstack([matrix, row])
    else:
        for px, py in coords:
            row = (np.abs(px - coords_x) <= 1) & (np.abs(py - coords_y) <= 1)
            matrix = sparse.vstack([matrix, row])
    matrix.setdiag(1)
    # Once built, we convert it to compressed sparse columns or rows
    return matrix.tocsc()  # or .tocsr()