autolens/data/array/util/mask_util.py
def edge_pixels_from_mask(mask):
    """Compute a 1D array listing all edge pixel indexes in the masks. An edge pixel is a pixel which is not fully \
    surrounding by False masks values i.e. it is on an edge."""

    edge_pixel_total = total_edge_pixels_from_mask(mask)

    edge_pixels = np.zeros(edge_pixel_total)
    edge_index = 0
    regular_index = 0

    for y in range(mask.shape[0]):
        for x in range(mask.shape[1]):
            if not mask[y, x]:
                if mask[y + 1, x] or mask[y - 1, x] or mask[y, x + 1] or mask[y, x - 1] or \
                        mask[y + 1, x + 1] or mask[y + 1, x - 1] or mask[y - 1, x + 1] or mask[y - 1, x - 1]:
                    edge_pixels[edge_index] = regular_index
                    edge_index += 1

                regular_index += 1

    return edge_pixels
def edge_pixels_from_mask(mask):
    """Compute a 1D array listing all edge pixel indexes in the masks. An edge pixel is a pixel which is not fully \
    surrounding by False masks values i.e. it is on an edge."""

    edge_pixel_total = total_edge_pixels_from_mask(mask)

    edge_pixels = np.zeros(edge_pixel_total)
    edge_index = 0
    regular_index = 0

    for y in range(mask.shape[0]):
        for x in range(mask.shape[1]):
            if not mask[y, x]:
                if mask[y + 1, x] or mask[y - 1, x] or mask[y, x + 1] or mask[y, x - 1] or \
                        mask[y + 1, x + 1] or mask[y + 1, x - 1] or mask[y - 1, x + 1] or mask[y - 1, x - 1]:
                    edge_pixels[edge_index] = regular_index
                    edge_index += 1

                regular_index += 1

    return edge_pixels
Compute a 1D array listing all edge pixel indexes in the masks. An edge pixel is a pixel which is not fully \
    surrounding by False masks values i.e. it is on an edge.