Python morphology.medial_axis方法代码示例

# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import medial_axis [as 别名]
def to_sdf(self):
        """ Converts the 2D image to a 2D signed distance field.

        Returns
        -------
        :obj:`numpy.ndarray`
            2D float array of the signed distance field
        """
        # compute medial axis transform
        skel, sdf_in = morph.medial_axis(self.data, return_distance=True)
        useless_skel, sdf_out = morph.medial_axis(
            np.iinfo(np.uint8).max - self.data, return_distance=True)

        # convert to true sdf
        sdf = sdf_out - sdf_in
        return sdf 

# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import medial_axis [as 别名]
def vectorize_lines(im: np.ndarray, threshold: float = 0.2, min_sp_dist: int = 10):
    """
    Vectorizes lines from a binarized array.

    Args:
        im (np.ndarray): Array of shape (3, H, W) with the first dimension
                         being probabilities for (start_separators,
                         end_separators, baseline).

    Returns:
        [[x0, y0, ... xn, yn], [xm, ym, ..., xk, yk], ... ]
        A list of lists containing the points of all baseline polylines.
    """
    # split into baseline and separator map
    st_map = im[0]
    end_map = im[1]
    sep_map = st_map + end_map
    bl_map = im[2]
    # binarize
    bin = im > threshold
    skel, skel_dist_map = medial_axis(bin[2], return_distance=True)
    elongation_offset = np.max(skel_dist_map)
    sp_can = _find_superpixels(skel, heatmap=bl_map, min_sp_dist=min_sp_dist)
    if not sp_can.size:
        logger.warning('No superpixel candidates found in network output. Likely empty page.')
        return []
    intensities = _compute_sp_states(sp_can, bl_map, st_map, end_map)
    clusters = _cluster_lines(intensities)
    lines = _interpolate_lines(clusters, elongation_offset, bl_map.shape, st_map, end_map)
    return lines 

# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import medial_axis [as 别名]
def place_routers_on_skeleton(d, cmethod):
    wireless = np.where(d["graph"] == Cell.Wireless, 1, 0)
    # perform skeletonization
    skeleton = skeletonize(wireless)
    med_axis = medial_axis(wireless)

    skel = skeleton
    # skel = med_axis
    # get all skeleton positions
    pos = []
    for i in range(skel.shape[0]):
        for j in range(skel.shape[1]):
            if skel[i][j]:
                pos.append((i, j))

    budget = d['budget']
    shuffle(pos)

    max_num_routers = min([int(d['budget'] / d['price_router']), len(pos)])
    print("Num of routers constrained by:")
    print(" budget:   %d" % int(int(d['budget'] / d['price_router'])))
    print(" skeleton: %d" % len(pos))

    for i in tqdm(range(max_num_routers), desc="Placing Routers"):
        new_router = pos[i]
        a, b = new_router

        # check if remaining budget is enough
        d["graph"][a][b] = Cell.Router
        d, ret, cost = _add_cabel(d, new_router, budget)
        budget -= cost

        if not ret:
            break

    return d 

# 需要导入模块: from skimage import morphology [as 别名]
# 或者: from skimage.morphology import medial_axis [as 别名]
def place_routers_on_skeleton_iterative(d, cmethod):
    budget = d['budget']
    R = d['radius']
    max_num_routers = int(d['budget'] / d['price_router'])
    coverage = np.where(d["graph"] == Cell.Wireless, 1, 0).astype(np.bool)

    pbar = tqdm(range(max_num_routers), desc="Placing Routers")
    while budget > 0:
        # perform skeletonization
        # skeleton = skeletonize(coverage)
        skeleton = medial_axis(coverage)
        # get all skeleton positions
        pos = np.argwhere(skeleton > 0).tolist()
        # escape if no positions left
        if not len(pos):
            break
        # get a random position
        shuffle(pos)
        a, b = pos[0]
        # place router
        d["graph"][a][b] = Cell.Router
        d, ret, cost = _add_cabel(d, (a, b), budget)
        if not ret:
            print("No budget available!")
            break
        budget -= cost
        # refresh wireless map by removing new coverage
        m = wireless_access(a, b, R, d['graph']).astype(np.bool)
        coverage[(a - R):(a + R + 1), (b - R):(b + R + 1)] &= ~m
        pbar.update()
    pbar.close()

    return d