trid_photo_inpainting_utils.py

import os
import copy
import functools

import cv2
import numpy as np
from scipy.interpolate import interp1d
from skimage.transform import resize
import matplotlib.pyplot as plt

try:
    import cynetworkx as netx
except ImportError:
    import networkx as netx
import transforms3d

from vispy import scene, io
from vispy.scene import visuals
from vispy.visuals.filters import Alpha
from moviepy.editor import ImageSequenceClip

__all__ = [
    'path_planning',
    'read_MiDaS_depth',
    'sparse_bilateral_filtering',
    'write_ply',
    'read_ply',
    'output_3d_photo',
]

def edge_forward_3P(net, mask, context, rgb, disp, edge, unit_length=128):
    input = np.concatenate((rgb, disp / disp.max(), edge, context, mask), axis=1)
    n, c, h, w = input.shape
    residual_h = int(np.ceil(h / float(unit_length)) * unit_length - h)
    residual_w = int(np.ceil(w / float(unit_length)) * unit_length - w)
    anchor_h = residual_h // 2
    anchor_w = residual_w // 2
    enlarge_input = np.zeros((n, c, h + residual_h, w + residual_w)).astype(np.float32)
    enlarge_input[..., anchor_h:anchor_h + h, anchor_w:anchor_w + w] = input
    if not "onnxruntime" in str(type(net)):
        output = net.predict({'enlarge_input': enlarge_input})
    else:
        output = net.run(['edge_output'], {'enlarge_input': enlarge_input})
    edge_output = output[0]
    edge_output = edge_output[..., anchor_h:anchor_h + h, anchor_w:anchor_w + w]
    return edge_output


def depth_forward_3P(net, mask, context, depth, edge, unit_length=128):
    input = np.concatenate((depth, edge, context, mask), axis=1)
    n, c, h, w = input.shape
    residual_h = int(np.ceil(h / float(unit_length)) * unit_length - h)
    residual_w = int(np.ceil(w / float(unit_length)) * unit_length - w)
    anchor_h = residual_h // 2
    anchor_w = residual_w // 2
    enlarge_input = np.zeros((n, c, h + residual_h, w + residual_w)).astype(np.float32)
    enlarge_input[..., anchor_h:anchor_h + h, anchor_w:anchor_w + w] = input
    if not "onnxruntime" in str(type(net)):
        output = net.predict({'enlarge_input': enlarge_input})
    else:
        output = net.run(['depth_output'], {'enlarge_input': enlarge_input})
    depth_output = output[0]
    depth_output = depth_output[..., anchor_h:anchor_h + h, anchor_w:anchor_w + w]
    return depth_output


def color_forward_3P(net, mask, context, rgb, edge, unit_length=128):
    input = np.concatenate((rgb, edge, context, mask), axis=1)
    n, c, h, w = input.shape
    residual_h = int(np.ceil(h / float(unit_length)) * unit_length - h)
    residual_w = int(np.ceil(w / float(unit_length)) * unit_length - w)
    anchor_h = residual_h // 2
    anchor_w = residual_w // 2
    enlarge_input = np.zeros((n, c, h + residual_h, w + residual_w)).astype(np.float32)
    enlarge_input[..., anchor_h:anchor_h + h, anchor_w:anchor_w + w] = input
    if not "onnxruntime" in str(type(net)):
        output = net.predict({'enlarge_input': enlarge_input})
    else:
        output = net.run(['rgb_output'], {'enlarge_input': enlarge_input})
    rgb_output = output[0]
    rgb_output = rgb_output[..., anchor_h:anchor_h + h, anchor_w:anchor_w + w]
    return rgb_output


def path_planning(num_frames, x, y, z, path_type=''):
    if path_type == 'straight-line':
        corner_points = np.array([[0, 0, 0], [(0 + x) * 0.5, (0 + y) * 0.5, (0 + z) * 0.5], [x, y, z]])
        corner_t = np.linspace(0, 1, len(corner_points))
        t = np.linspace(0, 1, num_frames)
        cs = interp1d(corner_t, corner_points, axis=0, kind='quadratic')
        spline = cs(t)
        xs, ys, zs = [xx.squeeze() for xx in np.split(spline, 3, 1)]
    elif path_type == 'double-straight-line':
        corner_points = np.array([[-x, -y, -z], [0, 0, 0], [x, y, z]])
        corner_t = np.linspace(0, 1, len(corner_points))
        t = np.linspace(0, 1, num_frames)
        cs = interp1d(corner_t, corner_points, axis=0, kind='quadratic')
        spline = cs(t)
        xs, ys, zs = [xx.squeeze() for xx in np.split(spline, 3, 1)]
    elif path_type == 'circle':
        xs, ys, zs = [], [], []
        for frame_id, bs_shift_val in enumerate(np.arange(-2.0, 2.0, (4. / num_frames))):
            xs += [np.cos(bs_shift_val * np.pi) * 1 * x]
            ys += [np.sin(bs_shift_val * np.pi) * 1 * y]
            zs += [np.cos(bs_shift_val * np.pi / 2.) * 1 * z]
        xs, ys, zs = np.array(xs), np.array(ys), np.array(zs)

    return xs, ys, zs


def open_small_mask(mask, context, open_iteration, kernel):
    np_mask = mask.squeeze().astype(np.uint8)
    np_context = context.squeeze().astype(np.uint8)
    np_input = np_mask + np_context
    for _ in range(open_iteration):
        np_input = cv2.erode(
            cv2.dilate(np_input, np.ones((kernel, kernel)), iterations=1),
            np.ones((kernel, kernel)),
            iterations=1)
    np_mask[(np_input - np_context) > 0] = 1
    out_mask = np_mask.astype(mask.dtype)[None, None, ...]

    return out_mask


def filter_irrelevant_edge_new(
        self_edge, comp_edge, other_edges,
        other_edges_with_id, current_edge_id,
        context, depth, mesh, context_cc, spdb=False):
    other_edges = other_edges.squeeze().astype(np.uint8)
    other_edges_with_id = other_edges_with_id.squeeze()
    self_edge = self_edge.squeeze()
    dilate_bevel_self_edge = cv2.dilate((self_edge + comp_edge).astype(np.uint8),
                                        np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]]), iterations=1)
    dilate_cross_self_edge = cv2.dilate((self_edge + comp_edge).astype(np.uint8),
                                        np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]]).astype(np.uint8), iterations=1)
    edge_ids = np.unique(other_edges_with_id * context + (-1) * (1 - context)).astype(int)
    end_depth_maps = np.zeros_like(self_edge)
    self_edge_ids = np.sort(np.unique(other_edges_with_id[self_edge > 0]).astype(int))
    self_edge_ids = self_edge_ids[1:] if self_edge_ids.shape[0] > 0 and self_edge_ids[0] == -1 else self_edge_ids
    self_comp_ids = np.sort(np.unique(other_edges_with_id[comp_edge > 0]).astype(int))
    self_comp_ids = self_comp_ids[1:] if self_comp_ids.shape[0] > 0 and self_comp_ids[0] == -1 else self_comp_ids
    edge_ids = edge_ids[1:] if edge_ids[0] == -1 else edge_ids
    other_edges_info = []
    extend_other_edges = np.zeros_like(other_edges)
    if spdb is True:
        f, ((ax1, ax2, ax3)) = plt.subplots(1, 3, sharex=True, sharey=True);
        ax1.imshow(self_edge);
        ax2.imshow(context);
        ax3.imshow(other_edges_with_id * context + (-1) * (1 - context));
        plt.show()
    filter_self_edge = np.zeros_like(self_edge)
    for self_edge_id in self_edge_ids:
        filter_self_edge[other_edges_with_id == self_edge_id] = 1
    dilate_self_comp_edge = cv2.dilate(comp_edge, kernel=np.ones((3, 3)), iterations=2)
    valid_self_comp_edge = np.zeros_like(comp_edge)
    for self_comp_id in self_comp_ids:
        valid_self_comp_edge[self_comp_id == other_edges_with_id] = 1
    self_comp_edge = dilate_self_comp_edge * valid_self_comp_edge
    filter_self_edge = (filter_self_edge + self_comp_edge).clip(0, 1)
    for edge_id in edge_ids:
        other_edge_locs = (other_edges_with_id == edge_id).astype(np.uint8)
        condition = (other_edge_locs * other_edges * context.astype(np.uint8))
        end_cross_point = dilate_cross_self_edge * condition * (1 - filter_self_edge)
        end_bevel_point = dilate_bevel_self_edge * condition * (1 - filter_self_edge)
        if end_bevel_point.max() != 0:
            end_depth_maps[end_bevel_point != 0] = depth[end_bevel_point != 0]
            if end_cross_point.max() == 0:
                nxs, nys = np.where(end_bevel_point != 0)
                for nx, ny in zip(nxs, nys):
                    bevel_node = [xx for xx in context_cc if xx[0] == nx and xx[1] == ny][0]
                for ne in mesh.neighbors(bevel_node):
                    if other_edges_with_id[ne[0], ne[1]] > -1 and dilate_cross_self_edge[ne[0], ne[1]] > 0:
                        extend_other_edges[ne[0], ne[1]] = 1
                        break
        else:
            other_edges[other_edges_with_id == edge_id] = 0
    other_edges = (other_edges + extend_other_edges).clip(0, 1) * context

    return other_edges, end_depth_maps, other_edges_info


def clean_far_edge_new(
        input_edge, end_depth_maps, mask, context,
        global_mesh, info_on_pix, self_edge, inpaint_id, config):
    mesh = netx.Graph()
    hxs, hys = np.where(input_edge * mask > 0)
    valid_near_edge = (input_edge != 0).astype(np.uint8) * context
    valid_map = mask + context
    invalid_edge_ids = []
    for hx, hy in zip(hxs, hys):
        node = (hx, hy)
        mesh.add_node((hx, hy))
        eight_nes = [ne for ne in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1), \
                                   (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1), (hx + 1, hy - 1)] \
                     if 0 <= ne[0] < input_edge.shape[0] and 0 <= ne[1] < input_edge.shape[1] and 0 < input_edge[
                         ne[0], ne[1]]]  # or end_depth_maps[ne[0], ne[1]] != 0]
        for ne in eight_nes:
            mesh.add_edge(node, ne, length=np.hypot(ne[0] - hx, ne[1] - hy))
            if end_depth_maps[ne[0], ne[1]] != 0:
                mesh.nodes[ne[0], ne[1]]['cnt'] = True
                mesh.nodes[ne[0], ne[1]]['depth'] = end_depth_maps[ne[0], ne[1]]
            elif mask[ne[0], ne[1]] != 1:
                four_nes = [nne for nne in
                            [(ne[0] + 1, ne[1]), (ne[0] - 1, ne[1]), (ne[0], ne[1] + 1), (ne[0], ne[1] - 1)] \
                            if nne[0] < end_depth_maps.shape[0] and nne[0] >= 0 and nne[1] < end_depth_maps.shape[1] and
                            nne[1] >= 0]
                for nne in four_nes:
                    if end_depth_maps[nne[0], nne[1]] != 0:
                        mesh.add_edge(nne, ne, length=np.hypot(nne[0] - ne[0], nne[1] - ne[1]))
                        mesh.nodes[nne[0], nne[1]]['cnt'] = True
                        mesh.nodes[nne[0], nne[1]]['depth'] = end_depth_maps[nne[0], nne[1]]
    ccs = [*netx.connected_components(mesh)]
    end_pts = []
    for cc in ccs:
        end_pts.append(set())
        for node in cc:
            if mesh.nodes[node].get('cnt') is not None:
                end_pts[-1].add((node[0], node[1], mesh.nodes[node]['depth']))
    predef_npaths = [None for _ in range(len(ccs))]
    fpath_map = np.zeros_like(input_edge) - 1
    npath_map = np.zeros_like(input_edge) - 1
    npaths, fpaths = dict(), dict()
    break_flag = False
    end_idx = 0
    while end_idx < len(end_pts):
        end_pt, cc = [*zip(end_pts, ccs)][end_idx]
        end_idx += 1
        sorted_end_pt = []
        fpath = []
        iter_fpath = []
        if len(end_pt) > 2 or len(end_pt) == 0:
            if len(end_pt) > 2:
                continue
            continue
        if len(end_pt) == 2:
            ravel_end = [*end_pt]
            tmp_sub_mesh = mesh.subgraph(list(cc)).copy()
            tmp_npath = [*netx.shortest_path(tmp_sub_mesh, (ravel_end[0][0], ravel_end[0][1]),
                                             (ravel_end[1][0], ravel_end[1][1]), weight='length')]
            fpath_map1, npath_map1, disp_diff1 = plan_path(
                mesh, info_on_pix, cc, ravel_end[0:1], global_mesh,
                input_edge, mask, valid_map, inpaint_id, npath_map=None,
                fpath_map=None, npath=tmp_npath)
            fpath_map2, npath_map2, disp_diff2 = plan_path(
                mesh, info_on_pix, cc, ravel_end[1:2], global_mesh,
                input_edge, mask, valid_map, inpaint_id, npath_map=None,
                fpath_map=None, npath=tmp_npath)
            tmp_disp_diff = [disp_diff1, disp_diff2]
            self_end = []
            edge_len = []
            ds_edge = cv2.dilate(self_edge.astype(np.uint8), np.ones((3, 3)), iterations=1)
            if ds_edge[ravel_end[0][0], ravel_end[0][1]] > 0:
                self_end.append(1)
            else:
                self_end.append(0)
            if ds_edge[ravel_end[1][0], ravel_end[1][1]] > 0:
                self_end.append(1)
            else:
                self_end.append(0)
            edge_len = [np.count_nonzero(npath_map1), np.count_nonzero(npath_map2)]
            sorted_end_pts = [xx[0] for xx in sorted(zip(ravel_end, self_end, edge_len, [disp_diff1, disp_diff2]),
                                                     key=lambda x: (x[1], x[2]), reverse=True)]
            re_npath_map1, re_fpath_map1 = (npath_map1 != -1).astype(np.uint8), (fpath_map1 != -1).astype(np.uint8)
            re_npath_map2, re_fpath_map2 = (npath_map2 != -1).astype(np.uint8), (fpath_map2 != -1).astype(np.uint8)
            if np.count_nonzero(re_npath_map1 * re_npath_map2 * mask) / \
                    (np.count_nonzero((re_npath_map1 + re_npath_map2) * mask) + 1e-6) > 0.5 \
                    and np.count_nonzero(re_fpath_map1 * re_fpath_map2 * mask) / \
                    (np.count_nonzero((re_fpath_map1 + re_fpath_map2) * mask) + 1e-6) > 0.5 \
                    and tmp_disp_diff[0] != -1 and tmp_disp_diff[1] != -1:
                my_fpath_map, my_npath_map, npath, fpath = \
                    plan_path_e2e(mesh, cc, sorted_end_pts, global_mesh, input_edge, mask, valid_map, inpaint_id,
                                  npath_map=None, fpath_map=None)
                npath_map[my_npath_map != -1] = my_npath_map[my_npath_map != -1]
                fpath_map[my_fpath_map != -1] = my_fpath_map[my_fpath_map != -1]
                if len(fpath) > 0:
                    edge_id = global_mesh.nodes[[*sorted_end_pts][0]]['edge_id']
                    fpaths[edge_id] = fpath
                    npaths[edge_id] = npath
                invalid_edge_ids.append(edge_id)
            else:
                if tmp_disp_diff[0] != -1:
                    ratio_a = tmp_disp_diff[0] / (np.sum(tmp_disp_diff) + 1e-8)
                else:
                    ratio_a = 0
                if tmp_disp_diff[1] != -1:
                    ratio_b = tmp_disp_diff[1] / (np.sum(tmp_disp_diff) + 1e-8)
                else:
                    ratio_b = 0
                npath_len = len(tmp_npath)
                if npath_len > config['depth_edge_dilate_2'] * 2:
                    npath_len = npath_len - (config['depth_edge_dilate_2'] * 1)
                tmp_npath_a = tmp_npath[:int(np.floor(npath_len * ratio_a))]
                tmp_npath_b = tmp_npath[::-1][:int(np.floor(npath_len * ratio_b))]
                tmp_merge = []
                if len(tmp_npath_a) > 0 and sorted_end_pts[0][0] == tmp_npath_a[0][0] and sorted_end_pts[0][1] == \
                        tmp_npath_a[0][1]:
                    if len(tmp_npath_a) > 0 and mask[tmp_npath_a[-1][0], tmp_npath_a[-1][1]] > 0:
                        tmp_merge.append([sorted_end_pts[:1], tmp_npath_a])
                    if len(tmp_npath_b) > 0 and mask[tmp_npath_b[-1][0], tmp_npath_b[-1][1]] > 0:
                        tmp_merge.append([sorted_end_pts[1:2], tmp_npath_b])
                elif len(tmp_npath_b) > 0 and sorted_end_pts[0][0] == tmp_npath_b[0][0] and sorted_end_pts[0][1] == \
                        tmp_npath_b[0][1]:
                    if len(tmp_npath_b) > 0 and mask[tmp_npath_b[-1][0], tmp_npath_b[-1][1]] > 0:
                        tmp_merge.append([sorted_end_pts[:1], tmp_npath_b])
                    if len(tmp_npath_a) > 0 and mask[tmp_npath_a[-1][0], tmp_npath_a[-1][1]] > 0:
                        tmp_merge.append([sorted_end_pts[1:2], tmp_npath_a])
                for tmp_idx in range(len(tmp_merge)):
                    if len(tmp_merge[tmp_idx][1]) == 0:
                        continue
                    end_pts.append(tmp_merge[tmp_idx][0])
                    ccs.append(set(tmp_merge[tmp_idx][1]))
        if len(end_pt) == 1:
            sub_mesh = mesh.subgraph(list(cc)).copy()
            pnodes = netx.periphery(sub_mesh)
            if len(end_pt) == 1:
                ends = [*end_pt]
            elif len(sorted_end_pt) == 1:
                ends = [*sorted_end_pt]
            try:
                edge_id = global_mesh.nodes[ends[0]]['edge_id']
            except:
                raise
            pnodes = sorted(pnodes,
                            key=lambda x: np.hypot((x[0] - ends[0][0]), (x[1] - ends[0][1])),
                            reverse=True)[0]
            npath = [*netx.shortest_path(sub_mesh, (ends[0][0], ends[0][1]), pnodes, weight='length')]
            for np_node in npath:
                npath_map[np_node[0], np_node[1]] = edge_id
            fpath = []
            if global_mesh.nodes[ends[0]].get('far') is None:
                print("None far")
            else:
                fnodes = global_mesh.nodes[ends[0]].get('far')
                dmask = mask + 0
                did = 0
                while True:
                    did += 1
                    dmask = cv2.dilate(dmask, np.ones((3, 3)), iterations=1)
                    if did > 3:
                        break
                    ffnode = [fnode for fnode in fnodes if
                              (dmask[fnode[0], fnode[1]] > 0 and mask[fnode[0], fnode[1]] == 0 and \
                               global_mesh.nodes[fnode].get('inpaint_id') != inpaint_id + 1)]
                    if len(ffnode) > 0:
                        fnode = ffnode[0]
                        break
                if len(ffnode) == 0:
                    continue
                fpath.append((fnode[0], fnode[1]))
                barrel_dir = np.array([[1, 0], [1, 1], [0, 1], [-1, 1], [-1, 0], [-1, -1], [0, -1], [1, -1]])
                n2f_dir = (int(fnode[0] - npath[0][0]), int(fnode[1] - npath[0][1]))
                while True:
                    if barrel_dir[0, 0] == n2f_dir[0] and barrel_dir[0, 1] == n2f_dir[1]:
                        n2f_barrel = barrel_dir.copy()
                        break
                    barrel_dir = np.roll(barrel_dir, 1, axis=0)
                for step in range(0, len(npath)):
                    if step == 0:
                        continue
                    elif step == 1:
                        next_dir = (npath[step][0] - npath[step - 1][0], npath[step][1] - npath[step - 1][1])
                        while True:
                            if barrel_dir[0, 0] == next_dir[0] and barrel_dir[0, 1] == next_dir[1]:
                                next_barrel = barrel_dir.copy()
                                break
                            barrel_dir = np.roll(barrel_dir, 1, axis=0)
                        barrel_pair = np.stack((n2f_barrel, next_barrel), axis=0)
                        n2f_dir = (barrel_pair[0, 0, 0], barrel_pair[0, 0, 1])
                    elif step > 1:
                        next_dir = (npath[step][0] - npath[step - 1][0], npath[step][1] - npath[step - 1][1])
                        while True:
                            if barrel_pair[1, 0, 0] == next_dir[0] and barrel_pair[1, 0, 1] == next_dir[1]:
                                next_barrel = barrel_pair.copy()
                                break
                            barrel_pair = np.roll(barrel_pair, 1, axis=1)
                        n2f_dir = (barrel_pair[0, 0, 0], barrel_pair[0, 0, 1])
                    new_locs = []
                    if abs(n2f_dir[0]) == 1:
                        new_locs.append((npath[step][0] + n2f_dir[0], npath[step][1]))
                    if abs(n2f_dir[1]) == 1:
                        new_locs.append((npath[step][0], npath[step][1] + n2f_dir[1]))
                    if len(new_locs) > 1:
                        new_locs = sorted(new_locs,
                                          key=lambda xx: np.hypot((xx[0] - fpath[-1][0]), (xx[1] - fpath[-1][1])))
                    break_flag = False
                    for new_loc in new_locs:
                        new_loc_nes = [xx for xx in [(new_loc[0] + 1, new_loc[1]), (new_loc[0] - 1, new_loc[1]),
                                                     (new_loc[0], new_loc[1] + 1), (new_loc[0], new_loc[1] - 1)] \
                                       if xx[0] >= 0 and xx[0] < fpath_map.shape[0] and xx[1] >= 0 and xx[1] <
                                       fpath_map.shape[1]]
                        if np.all([(fpath_map[nlne[0], nlne[1]] == -1) for nlne in new_loc_nes]) != True:
                            break
                        if npath_map[new_loc[0], new_loc[1]] != -1:
                            if npath_map[new_loc[0], new_loc[1]] != edge_id:
                                break_flag = True
                                break
                            else:
                                continue
                        if valid_map[new_loc[0], new_loc[1]] == 0:
                            break_flag = True
                            break
                        fpath.append(new_loc)
                    if break_flag is True:
                        break
                if step != len(npath) - 1:
                    for xx in npath[step:]:
                        if npath_map[xx[0], xx[1]] == edge_id:
                            npath_map[xx[0], xx[1]] = -1
                    npath = npath[:step]
            if len(fpath) > 0:
                for fp_node in fpath:
                    fpath_map[fp_node[0], fp_node[1]] = edge_id
                fpaths[edge_id] = fpath
                npaths[edge_id] = npath
        fpath_map[valid_near_edge != 0] = -1
        if len(fpath) > 0:
            iter_fpath = copy.deepcopy(fpaths[edge_id])
        for node in iter_fpath:
            if valid_near_edge[node[0], node[1]] != 0:
                fpaths[edge_id].remove(node)

    return fpath_map, npath_map, False, npaths, fpaths, invalid_edge_ids


def plan_path_e2e(
        mesh, cc, end_pts, global_mesh, input_edge,
        mask, valid_map, inpaint_id, npath_map=None,
        fpath_map=None):
    my_npath_map = np.zeros_like(input_edge) - 1
    my_fpath_map = np.zeros_like(input_edge) - 1
    sub_mesh = mesh.subgraph(list(cc)).copy()
    ends_1, ends_2 = end_pts[0], end_pts[1]
    edge_id = global_mesh.nodes[ends_1]['edge_id']
    npath = [*netx.shortest_path(sub_mesh, (ends_1[0], ends_1[1]), (ends_2[0], ends_2[1]), weight='length')]
    for np_node in npath:
        my_npath_map[np_node[0], np_node[1]] = edge_id
    fpath = []
    if global_mesh.nodes[ends_1].get('far') is None:
        print("None far")
    else:
        fnodes = global_mesh.nodes[ends_1].get('far')
        dmask = mask + 0
        while True:
            dmask = cv2.dilate(dmask, np.ones((3, 3)), iterations=1)
            ffnode = [fnode for fnode in fnodes if (dmask[fnode[0], fnode[1]] > 0 and mask[fnode[0], fnode[1]] == 0 and \
                                                    global_mesh.nodes[fnode].get('inpaint_id') != inpaint_id + 1)]
            if len(ffnode) > 0:
                fnode = ffnode[0]
                break
        e_fnodes = global_mesh.nodes[ends_2].get('far')
        dmask = mask + 0
        while True:
            dmask = cv2.dilate(dmask, np.ones((3, 3)), iterations=1)
            e_ffnode = [e_fnode for e_fnode in e_fnodes if
                        (dmask[e_fnode[0], e_fnode[1]] > 0 and mask[e_fnode[0], e_fnode[1]] == 0 and \
                         global_mesh.nodes[e_fnode].get('inpaint_id') != inpaint_id + 1)]
            if len(e_ffnode) > 0:
                e_fnode = e_ffnode[0]
                break
        fpath.append((fnode[0], fnode[1]))
        if len(e_ffnode) == 0 or len(ffnode) == 0:
            return my_npath_map, my_fpath_map, [], []
        barrel_dir = np.array([[1, 0], [1, 1], [0, 1], [-1, 1], [-1, 0], [-1, -1], [0, -1], [1, -1]])
        n2f_dir = (int(fnode[0] - npath[0][0]), int(fnode[1] - npath[0][1]))
        while True:
            if barrel_dir[0, 0] == n2f_dir[0] and barrel_dir[0, 1] == n2f_dir[1]:
                n2f_barrel = barrel_dir.copy()
                break
            barrel_dir = np.roll(barrel_dir, 1, axis=0)
        for step in range(0, len(npath)):
            if step == 0:
                continue
            elif step == 1:
                next_dir = (npath[step][0] - npath[step - 1][0], npath[step][1] - npath[step - 1][1])
                while True:
                    if barrel_dir[0, 0] == next_dir[0] and barrel_dir[0, 1] == next_dir[1]:
                        next_barrel = barrel_dir.copy()
                        break
                    barrel_dir = np.roll(barrel_dir, 1, axis=0)
                barrel_pair = np.stack((n2f_barrel, next_barrel), axis=0)
                n2f_dir = (barrel_pair[0, 0, 0], barrel_pair[0, 0, 1])
            elif step > 1:
                next_dir = (npath[step][0] - npath[step - 1][0], npath[step][1] - npath[step - 1][1])
                while True:
                    if barrel_pair[1, 0, 0] == next_dir[0] and barrel_pair[1, 0, 1] == next_dir[1]:
                        next_barrel = barrel_pair.copy()
                        break
                    barrel_pair = np.roll(barrel_pair, 1, axis=1)
                n2f_dir = (barrel_pair[0, 0, 0], barrel_pair[0, 0, 1])
            new_locs = []
            if abs(n2f_dir[0]) == 1:
                new_locs.append((npath[step][0] + n2f_dir[0], npath[step][1]))
            if abs(n2f_dir[1]) == 1:
                new_locs.append((npath[step][0], npath[step][1] + n2f_dir[1]))
            if len(new_locs) > 1:
                new_locs = sorted(new_locs, key=lambda xx: np.hypot((xx[0] - fpath[-1][0]), (xx[1] - fpath[-1][1])))
            break_flag = False
            for new_loc in new_locs:
                new_loc_nes = [xx for xx in [(new_loc[0] + 1, new_loc[1]), (new_loc[0] - 1, new_loc[1]),
                                             (new_loc[0], new_loc[1] + 1), (new_loc[0], new_loc[1] - 1)] \
                               if xx[0] >= 0 and xx[0] < my_fpath_map.shape[0] and xx[1] >= 0 and xx[1] <
                               my_fpath_map.shape[1]]
                if fpath_map is not None and np.sum([fpath_map[nlne[0], nlne[1]] for nlne in new_loc_nes]) != 0:
                    break_flag = True
                    break
                if my_npath_map[new_loc[0], new_loc[1]] != -1:
                    continue
                if npath_map is not None and npath_map[new_loc[0], new_loc[1]] != edge_id:
                    break_flag = True
                    break
                fpath.append(new_loc)
            if break_flag is True:
                break
        if (e_fnode[0], e_fnode[1]) not in fpath:
            fpath.append((e_fnode[0], e_fnode[1]))
        if step != len(npath) - 1:
            for xx in npath[step:]:
                if my_npath_map[xx[0], xx[1]] == edge_id:
                    my_npath_map[xx[0], xx[1]] = -1
            npath = npath[:step]
        if len(fpath) > 0:
            for fp_node in fpath:
                my_fpath_map[fp_node[0], fp_node[1]] = edge_id

    return my_fpath_map, my_npath_map, npath, fpath


def plan_path(
        mesh, info_on_pix, cc, end_pt, global_mesh, input_edge,
        mask, valid_map, inpaint_id, npath_map=None,
        fpath_map=None, npath=None):
    my_npath_map = np.zeros_like(input_edge) - 1
    my_fpath_map = np.zeros_like(input_edge) - 1
    sub_mesh = mesh.subgraph(list(cc)).copy()
    pnodes = netx.periphery(sub_mesh)
    ends = [*end_pt]
    edge_id = global_mesh.nodes[ends[0]]['edge_id']
    pnodes = sorted(pnodes,
                    key=lambda x: np.hypot((x[0] - ends[0][0]), (x[1] - ends[0][1])),
                    reverse=True)[0]
    if npath is None:
        npath = [*netx.shortest_path(sub_mesh, (ends[0][0], ends[0][1]), pnodes, weight='length')]
    else:
        if (ends[0][0], ends[0][1]) == npath[0]:
            npath = npath
        elif (ends[0][0], ends[0][1]) == npath[-1]:
            npath = npath[::-1]
    for np_node in npath:
        my_npath_map[np_node[0], np_node[1]] = edge_id
    fpath = []
    if global_mesh.nodes[ends[0]].get('far') is None:
        print("None far")
    else:
        fnodes = global_mesh.nodes[ends[0]].get('far')
        dmask = mask + 0
        did = 0
        while True:
            did += 1
            if did > 3:
                return my_fpath_map, my_npath_map, -1
            dmask = cv2.dilate(dmask, np.ones((3, 3)), iterations=1)
            ffnode = [fnode for fnode in fnodes if (dmask[fnode[0], fnode[1]] > 0 and mask[fnode[0], fnode[1]] == 0 and \
                                                    global_mesh.nodes[fnode].get('inpaint_id') != inpaint_id + 1)]
            if len(ffnode) > 0:
                fnode = ffnode[0]
                break

        fpath.append((fnode[0], fnode[1]))
        disp_diff = 0.
        for n_loc in npath:
            if mask[n_loc[0], n_loc[1]] != 0:
                disp_diff = abs(abs(1. / info_on_pix[(n_loc[0], n_loc[1])][0]['depth']) - abs(1. / ends[0][2]))
                break
        barrel_dir = np.array([[1, 0], [1, 1], [0, 1], [-1, 1], [-1, 0], [-1, -1], [0, -1], [1, -1]])
        n2f_dir = (int(fnode[0] - npath[0][0]), int(fnode[1] - npath[0][1]))
        while True:
            if barrel_dir[0, 0] == n2f_dir[0] and barrel_dir[0, 1] == n2f_dir[1]:
                n2f_barrel = barrel_dir.copy()
                break
            barrel_dir = np.roll(barrel_dir, 1, axis=0)
        for step in range(0, len(npath)):
            if step == 0:
                continue
            elif step == 1:
                next_dir = (npath[step][0] - npath[step - 1][0], npath[step][1] - npath[step - 1][1])
                while True:
                    if barrel_dir[0, 0] == next_dir[0] and barrel_dir[0, 1] == next_dir[1]:
                        next_barrel = barrel_dir.copy()
                        break
                    barrel_dir = np.roll(barrel_dir, 1, axis=0)
                barrel_pair = np.stack((n2f_barrel, next_barrel), axis=0)
                n2f_dir = (barrel_pair[0, 0, 0], barrel_pair[0, 0, 1])
            elif step > 1:
                next_dir = (npath[step][0] - npath[step - 1][0], npath[step][1] - npath[step - 1][1])
                while True:
                    if barrel_pair[1, 0, 0] == next_dir[0] and barrel_pair[1, 0, 1] == next_dir[1]:
                        next_barrel = barrel_pair.copy()
                        break
                    barrel_pair = np.roll(barrel_pair, 1, axis=1)
                n2f_dir = (barrel_pair[0, 0, 0], barrel_pair[0, 0, 1])
            new_locs = []
            if abs(n2f_dir[0]) == 1:
                new_locs.append((npath[step][0] + n2f_dir[0], npath[step][1]))
            if abs(n2f_dir[1]) == 1:
                new_locs.append((npath[step][0], npath[step][1] + n2f_dir[1]))
            if len(new_locs) > 1:
                new_locs = sorted(new_locs, key=lambda xx: np.hypot((xx[0] - fpath[-1][0]), (xx[1] - fpath[-1][1])))
            break_flag = False
            for new_loc in new_locs:
                new_loc_nes = [xx for xx in [(new_loc[0] + 1, new_loc[1]), (new_loc[0] - 1, new_loc[1]),
                                             (new_loc[0], new_loc[1] + 1), (new_loc[0], new_loc[1] - 1)] \
                               if xx[0] >= 0 and xx[0] < my_fpath_map.shape[0] and xx[1] >= 0 and xx[1] <
                               my_fpath_map.shape[1]]
                if fpath_map is not None and np.all(
                        [(fpath_map[nlne[0], nlne[1]] == -1) for nlne in new_loc_nes]) != True:
                    break_flag = True
                    break
                if np.all([(my_fpath_map[nlne[0], nlne[1]] == -1) for nlne in new_loc_nes]) != True:
                    break_flag = True
                    break
                if my_npath_map[new_loc[0], new_loc[1]] != -1:
                    continue
                if npath_map is not None and npath_map[new_loc[0], new_loc[1]] != edge_id:
                    break_flag = True
                    break
                if valid_map[new_loc[0], new_loc[1]] == 0:
                    break_flag = True
                    break
                fpath.append(new_loc)
            if break_flag is True:
                break
        if step != len(npath) - 1:
            for xx in npath[step:]:
                if my_npath_map[xx[0], xx[1]] == edge_id:
                    my_npath_map[xx[0], xx[1]] = -1
            npath = npath[:step]
        if len(fpath) > 0:
            for fp_node in fpath:
                my_fpath_map[fp_node[0], fp_node[1]] = edge_id

    return my_fpath_map, my_npath_map, disp_diff


def refresh_node(
        old_node, old_feat, new_node, new_feat, mesh, stime=False):
    mesh.add_node(new_node)
    mesh.nodes[new_node].update(new_feat)
    mesh.nodes[new_node].update(old_feat)
    for ne in mesh.neighbors(old_node):
        mesh.add_edge(new_node, ne)
    if mesh.nodes[new_node].get('far') is not None:
        tmp_far_nodes = mesh.nodes[new_node]['far']
        for far_node in tmp_far_nodes:
            if mesh.has_node(far_node) is False:
                mesh.nodes[new_node]['far'].remove(far_node)
                continue
            if mesh.nodes[far_node].get('near') is not None:
                for idx in range(len(mesh.nodes[far_node].get('near'))):
                    if mesh.nodes[far_node]['near'][idx][0] == new_node[0] and mesh.nodes[far_node]['near'][idx][1] == \
                            new_node[1]:
                        if len(mesh.nodes[far_node]['near'][idx]) == len(old_node):
                            mesh.nodes[far_node]['near'][idx] = new_node
    if mesh.nodes[new_node].get('near') is not None:
        tmp_near_nodes = mesh.nodes[new_node]['near']
        for near_node in tmp_near_nodes:
            if mesh.has_node(near_node) is False:
                mesh.nodes[new_node]['near'].remove(near_node)
                continue
            if mesh.nodes[near_node].get('far') is not None:
                for idx in range(len(mesh.nodes[near_node].get('far'))):
                    if mesh.nodes[near_node]['far'][idx][0] == new_node[0] and mesh.nodes[near_node]['far'][idx][1] == \
                            new_node[1]:
                        if len(mesh.nodes[near_node]['far'][idx]) == len(old_node):
                            mesh.nodes[near_node]['far'][idx] = new_node
    if new_node != old_node:
        mesh.remove_node(old_node)
    if stime is False:
        return mesh
    else:
        return mesh, None, None


def create_placeholder(
        context, mask, depth, fpath_map, npath_map, mesh, inpaint_id,
        edge_ccs, extend_edge_cc, all_edge_maps, self_edge_id):
    add_node_time = 0
    add_edge_time = 0
    add_far_near_time = 0
    valid_area = context + mask
    H, W = mesh.graph['H'], mesh.graph['W']
    edge_cc = edge_ccs[self_edge_id]
    num_com = len(edge_cc) + len(extend_edge_cc)
    hxs, hys = np.where(mask > 0)
    for hx, hy in zip(hxs, hys):
        mesh.add_node((hx, hy), inpaint_id=inpaint_id + 1, num_context=num_com)
    for hx, hy in zip(hxs, hys):
        four_nes = [(x, y) for x, y in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] if \
                    0 <= x < mesh.graph['H'] and 0 <= y < mesh.graph['W'] and valid_area[x, y] != 0]
        for ne in four_nes:
            if mask[ne[0], ne[1]] != 0:
                if not mesh.has_edge((hx, hy), ne):
                    mesh.add_edge((hx, hy), ne)
            elif depth[ne[0], ne[1]] != 0:
                if mesh.has_node((ne[0], ne[1], depth[ne[0], ne[1]])) and \
                        not mesh.has_edge((hx, hy), (ne[0], ne[1], depth[ne[0], ne[1]])):
                    mesh.add_edge((hx, hy), (ne[0], ne[1], depth[ne[0], ne[1]]))
                else:
                    print("Undefined context node.")
    near_ids = np.unique(npath_map)
    if near_ids[0] == -1: near_ids = near_ids[1:]
    for near_id in near_ids:
        hxs, hys = np.where((fpath_map == near_id) & (mask > 0))
        if hxs.shape[0] > 0:
            mesh.graph['max_edge_id'] = mesh.graph['max_edge_id'] + 1
        else:
            break
        for hx, hy in zip(hxs, hys):
            mesh.nodes[(hx, hy)]['edge_id'] = int(round(mesh.graph['max_edge_id']))
            four_nes = [(x, y) for x, y in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] if \
                        x < mesh.graph['H'] and x >= 0 and y < mesh.graph['W'] and y >= 0 and npath_map[
                            x, y] == near_id]
            for xx in four_nes:
                xx_n = copy.deepcopy(xx)
                if not mesh.has_node(xx_n):
                    if mesh.has_node((xx_n[0], xx_n[1], depth[xx_n[0], xx_n[1]])):
                        xx_n = (xx_n[0], xx_n[1], depth[xx_n[0], xx_n[1]])
                if mesh.has_edge((hx, hy), xx_n):
                    # pass
                    mesh.remove_edge((hx, hy), xx_n)
                if mesh.nodes[(hx, hy)].get('near') is None:
                    mesh.nodes[(hx, hy)]['near'] = []
                mesh.nodes[(hx, hy)]['near'].append(xx_n)
        connect_point_exception = set()
        hxs, hys = np.where((npath_map == near_id) & (all_edge_maps > -1))
        for hx, hy in zip(hxs, hys):
            unknown_id = int(round(all_edge_maps[hx, hy]))
            if unknown_id != near_id and unknown_id != self_edge_id:
                unknown_node = set([xx for xx in edge_ccs[unknown_id] if xx[0] == hx and xx[1] == hy])
                connect_point_exception |= unknown_node
        hxs, hys = np.where((npath_map == near_id) & (mask > 0))
        if hxs.shape[0] > 0:
            mesh.graph['max_edge_id'] = mesh.graph['max_edge_id'] + 1
        else:
            break
        for hx, hy in zip(hxs, hys):
            mesh.nodes[(hx, hy)]['edge_id'] = int(round(mesh.graph['max_edge_id']))
            mesh.nodes[(hx, hy)]['connect_point_id'] = int(round(near_id))
            mesh.nodes[(hx, hy)]['connect_point_exception'] = connect_point_exception
            four_nes = [(x, y) for x, y in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] if \
                        x < mesh.graph['H'] and x >= 0 and y < mesh.graph['W'] and y >= 0 and fpath_map[
                            x, y] == near_id]
            for xx in four_nes:
                xx_n = copy.deepcopy(xx)
                if not mesh.has_node(xx_n):
                    if mesh.has_node((xx_n[0], xx_n[1], depth[xx_n[0], xx_n[1]])):
                        xx_n = (xx_n[0], xx_n[1], depth[xx_n[0], xx_n[1]])
                if mesh.has_edge((hx, hy), xx_n):
                    mesh.remove_edge((hx, hy), xx_n)
                if mesh.nodes[(hx, hy)].get('far') is None:
                    mesh.nodes[(hx, hy)]['far'] = []
                mesh.nodes[(hx, hy)]['far'].append(xx_n)

    return mesh, add_node_time, add_edge_time, add_far_near_time


def smooth_cntsyn_gap(
        init_depth_map, mask_region, context_region, init_mask_region=None):
    if init_mask_region is not None:
        curr_mask_region = init_mask_region * 1
    else:
        curr_mask_region = mask_region * 0
    depth_map = init_depth_map.copy()
    for _ in range(2):
        cm_mask = context_region + curr_mask_region
        depth_s1 = np.roll(depth_map, 1, 0)
        depth_s2 = np.roll(depth_map, -1, 0)
        depth_s3 = np.roll(depth_map, 1, 1)
        depth_s4 = np.roll(depth_map, -1, 1)
        mask_s1 = np.roll(cm_mask, 1, 0)
        mask_s2 = np.roll(cm_mask, -1, 0)
        mask_s3 = np.roll(cm_mask, 1, 1)
        mask_s4 = np.roll(cm_mask, -1, 1)
        fluxin_depths = (depth_s1 * mask_s1 + depth_s2 * mask_s2 + depth_s3 * mask_s3 + depth_s4 * mask_s4) / \
                        ((mask_s1 + mask_s2 + mask_s3 + mask_s4) + 1e-6)
        fluxin_mask = (fluxin_depths != 0) * mask_region
        init_mask = (fluxin_mask * (curr_mask_region >= 0).astype(np.float32) > 0).astype(np.uint8)
        depth_map[init_mask > 0] = fluxin_depths[init_mask > 0]
        if init_mask.shape[-1] > curr_mask_region.shape[-1]:
            curr_mask_region[init_mask.sum(-1, keepdims=True) > 0] = 1
        else:
            curr_mask_region[init_mask > 0] = 1
        depth_map[fluxin_mask > 0] = fluxin_depths[fluxin_mask > 0]

    return depth_map


def read_MiDaS_depth(
        depth, disp_rescale=10., h=None, w=None):
    disp = depth - depth.min()
    disp = cv2.blur(disp / disp.max(), ksize=(3, 3)) * disp.max()
    disp = (disp / disp.max()) * disp_rescale
    if h is not None and w is not None:
        disp = resize(disp / disp.max(), (h, w), order=1) * disp.max()
    depth = 1. / np.maximum(disp, 0.05)

    return depth


def require_depth_edge(context_edge, mask):
    dilate_mask = cv2.dilate(mask, np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]]).astype(np.uint8), iterations=1)
    if (dilate_mask * context_edge).max() == 0:
        return False
    else:
        return True


def refine_color_around_edge(
        mesh, info_on_pix, edge_ccs, config, spdb=False):
    H, W = mesh.graph['H'], mesh.graph['W']
    tmp_edge_ccs = copy.deepcopy(edge_ccs)
    for edge_id, edge_cc in enumerate(edge_ccs):
        if len(edge_cc) == 0:
            continue
        near_maps = np.zeros((H, W)).astype(bool)
        far_maps = np.zeros((H, W)).astype(bool)
        tmp_far_nodes = set()
        far_nodes = set()
        near_nodes = set()
        end_nodes = set()
        for i in range(5):
            if i == 0:
                for edge_node in edge_cc:
                    if mesh.nodes[edge_node].get('depth_edge_dilate_2_color_flag') is not True:
                        break
                    if mesh.nodes[edge_node].get('inpaint_id') == 1:
                        near_nodes.add(edge_node)
                        tmp_node = mesh.nodes[edge_node].get('far')
                        tmp_node = set(tmp_node) if tmp_node is not None else set()
                        tmp_far_nodes |= tmp_node
                rmv_tmp_far_nodes = set()
                for far_node in tmp_far_nodes:
                    if not (mesh.has_node(far_node) and mesh.nodes[far_node].get('inpaint_id') == 1):
                        rmv_tmp_far_nodes.add(far_node)
                if len(tmp_far_nodes - rmv_tmp_far_nodes) == 0:
                    break
                else:
                    for near_node in near_nodes:
                        near_maps[near_node[0], near_node[1]] = True
                        mesh.nodes[near_node]['refine_rgbd'] = True
                        mesh.nodes[near_node]['backup_depth'] = near_node[2] \
                            if mesh.nodes[near_node].get('real_depth') is None else mesh.nodes[near_node]['real_depth']
                        mesh.nodes[near_node]['backup_color'] = mesh.nodes[near_node]['color']
                for far_node in tmp_far_nodes:
                    if mesh.has_node(far_node) and mesh.nodes[far_node].get('inpaint_id') == 1:
                        far_nodes.add(far_node)
                        far_maps[far_node[0], far_node[1]] = True
                        mesh.nodes[far_node]['refine_rgbd'] = True
                        mesh.nodes[far_node]['backup_depth'] = far_node[2] \
                            if mesh.nodes[far_node].get('real_depth') is None else mesh.nodes[far_node]['real_depth']
                        mesh.nodes[far_node]['backup_color'] = mesh.nodes[far_node]['color']
                tmp_far_nodes = far_nodes
                tmp_near_nodes = near_nodes
            else:
                tmp_far_nodes = new_tmp_far_nodes
                tmp_near_nodes = new_tmp_near_nodes
                new_tmp_far_nodes = None
                new_tmp_near_nodes = None
            new_tmp_far_nodes = set()
            new_tmp_near_nodes = set()
            for node in tmp_near_nodes:
                for ne_node in mesh.neighbors(node):
                    if far_maps[ne_node[0], ne_node[1]] == False and \
                            near_maps[ne_node[0], ne_node[1]] == False:
                        if mesh.nodes[ne_node].get('inpaint_id') == 1:
                            new_tmp_near_nodes.add(ne_node)
                            near_maps[ne_node[0], ne_node[1]] = True
                            mesh.nodes[ne_node]['refine_rgbd'] = True
                            mesh.nodes[ne_node]['backup_depth'] = ne_node[2] \
                                if mesh.nodes[ne_node].get('real_depth') is None else mesh.nodes[ne_node]['real_depth']
                            mesh.nodes[ne_node]['backup_color'] = mesh.nodes[ne_node]['color']
                        else:
                            mesh.nodes[ne_node]['backup_depth'] = ne_node[2] \
                                if mesh.nodes[ne_node].get('real_depth') is None else mesh.nodes[ne_node]['real_depth']
                            mesh.nodes[ne_node]['backup_color'] = mesh.nodes[ne_node]['color']
                            end_nodes.add(node)
            near_nodes.update(new_tmp_near_nodes)
            for node in tmp_far_nodes:
                for ne_node in mesh.neighbors(node):
                    if far_maps[ne_node[0], ne_node[1]] == False and \
                            near_maps[ne_node[0], ne_node[1]] == False:
                        if mesh.nodes[ne_node].get('inpaint_id') == 1:
                            new_tmp_far_nodes.add(ne_node)
                            far_maps[ne_node[0], ne_node[1]] = True
                            mesh.nodes[ne_node]['refine_rgbd'] = True
                            mesh.nodes[ne_node]['backup_depth'] = ne_node[2] \
                                if mesh.nodes[ne_node].get('real_depth') is None else mesh.nodes[ne_node]['real_depth']
                            mesh.nodes[ne_node]['backup_color'] = mesh.nodes[ne_node]['color']
                        else:
                            mesh.nodes[ne_node]['backup_depth'] = ne_node[2] \
                                if mesh.nodes[ne_node].get('real_depth') is None else mesh.nodes[ne_node]['real_depth']
                            mesh.nodes[ne_node]['backup_color'] = mesh.nodes[ne_node]['color']
                            end_nodes.add(node)
            far_nodes.update(new_tmp_far_nodes)
        if len(far_nodes) == 0:
            tmp_edge_ccs[edge_id] = set()
            continue
        for node in new_tmp_far_nodes | new_tmp_near_nodes:
            for ne_node in mesh.neighbors(node):
                if far_maps[ne_node[0], ne_node[1]] == False and near_maps[ne_node[0], ne_node[1]] == False:
                    end_nodes.add(node)
                    mesh.nodes[ne_node]['backup_depth'] = ne_node[2] \
                        if mesh.nodes[ne_node].get('real_depth') is None else mesh.nodes[ne_node]['real_depth']
                    mesh.nodes[ne_node]['backup_color'] = mesh.nodes[ne_node]['color']
        tmp_end_nodes = end_nodes

        refine_nodes = near_nodes | far_nodes
        remain_refine_nodes = copy.deepcopy(refine_nodes)
        accum_idx = 0
        while len(remain_refine_nodes) > 0:
            accum_idx += 1
            if accum_idx > 100:
                break
            new_tmp_end_nodes = None
            new_tmp_end_nodes = set()
            survive_tmp_end_nodes = set()
            for node in tmp_end_nodes:
                re_depth, re_color, re_count = 0, np.array([0., 0., 0.]), 0
                for ne_node in mesh.neighbors(node):
                    if mesh.nodes[ne_node].get('refine_rgbd') is True:
                        if ne_node not in tmp_end_nodes:
                            new_tmp_end_nodes.add(ne_node)
                    else:
                        try:
                            re_depth += mesh.nodes[ne_node]['backup_depth']
                            re_color += mesh.nodes[ne_node]['backup_color'].astype(np.float32)
                            re_count += 1.
                        except:
                            raise
                if re_count > 0:
                    re_depth = re_depth / re_count
                    re_color = re_color / re_count
                    mesh.nodes[node]['backup_depth'] = re_depth
                    mesh.nodes[node]['backup_color'] = re_color
                    mesh.nodes[node]['refine_rgbd'] = False
                else:
                    survive_tmp_end_nodes.add(node)
            for node in tmp_end_nodes - survive_tmp_end_nodes:
                if node in remain_refine_nodes:
                    remain_refine_nodes.remove(node)
            tmp_end_nodes = new_tmp_end_nodes
        if spdb == True:
            bfrd_canvas = np.zeros((H, W))
            bfrc_canvas = np.zeros((H, W, 3)).astype(np.uint8)
            aftd_canvas = np.zeros((H, W))
            aftc_canvas = np.zeros((H, W, 3)).astype(np.uint8)
            for node in refine_nodes:
                bfrd_canvas[node[0], node[1]] = abs(node[2])
                aftd_canvas[node[0], node[1]] = abs(mesh.nodes[node]['backup_depth'])
                bfrc_canvas[node[0], node[1]] = mesh.nodes[node]['color'].astype(np.uint8)
                aftc_canvas[node[0], node[1]] = mesh.nodes[node]['backup_color'].astype(np.uint8)
            f, (ax1, ax2, ax3, ax4) = plt.subplots(1, 4, sharex=True, sharey=True);
            ax1.imshow(bfrd_canvas)
            ax2.imshow(aftd_canvas)
            ax3.imshow(bfrc_canvas)
            ax4.imshow(aftc_canvas)
            plt.show()
        for node in refine_nodes:
            if mesh.nodes[node].get('refine_rgbd') is not None:
                mesh.nodes[node].pop('refine_rgbd')
                mesh.nodes[node]['color'] = mesh.nodes[node]['backup_color']
                for info in info_on_pix[(node[0], node[1])]:
                    if info['depth'] == node[2]:
                        info['color'] = mesh.nodes[node]['backup_color']

    return mesh, info_on_pix


def refine_depth_around_edge(
        mask_depth, far_edge, uncleaned_far_edge, near_edge, mask, all_depth, config):
    mask = mask.squeeze()
    uncleaned_far_edge = uncleaned_far_edge.squeeze()
    far_edge = far_edge.squeeze()
    near_edge = near_edge.squeeze()
    mask_depth = mask_depth.squeeze()
    dilate_far_edge = cv2.dilate(
        uncleaned_far_edge.astype(np.uint8),
        kernel=np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]]).astype(np.uint8), iterations=1)
    near_edge[dilate_far_edge == 0] = 0
    dilate_near_edge = cv2.dilate(
        near_edge.astype(np.uint8),
        kernel=np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]]).astype(np.uint8), iterations=1)
    far_edge[dilate_near_edge == 0] = 0
    init_far_edge = far_edge.copy()
    init_near_edge = near_edge.copy()
    for i in range(config['depth_edge_dilate_2']):
        init_far_edge = cv2.dilate(init_far_edge, kernel=np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]]).astype(np.uint8),
                                   iterations=1)
        init_far_edge[init_near_edge == 1] = 0
        init_near_edge = cv2.dilate(init_near_edge, kernel=np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]]).astype(np.uint8),
                                    iterations=1)
        init_near_edge[init_far_edge == 1] = 0
    init_far_edge[mask == 0] = 0
    init_near_edge[mask == 0] = 0
    hole_far_edge = 1 - init_far_edge
    hole_near_edge = 1 - init_near_edge
    while True:
        change = False
        hole_far_edge[init_near_edge == 1] = 0
        hole_near_edge[init_far_edge == 1] = 0
        far_pxs, far_pys = np.where((hole_far_edge == 0) * (init_far_edge == 1) > 0)
        current_hole_far_edge = hole_far_edge.copy()
        for far_px, far_py in zip(far_pxs, far_pys):
            min_px = max(far_px - 1, 0)
            max_px = min(far_px + 2, mask.shape[0] - 1)
            min_py = max(far_py - 1, 0)
            max_py = min(far_py + 2, mask.shape[1] - 1)
            hole_far = current_hole_far_edge[min_px: max_px, min_py: max_py]
            tmp_mask = mask[min_px: max_px, min_py: max_py]
            all_depth_patch = all_depth[min_px: max_px, min_py: max_py] * 0
            all_depth_mask = (all_depth_patch != 0).astype(np.uint8)
            cross_element = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])[min_px - (far_px - 1): max_px - (far_px - 1),
                            min_py - (far_py - 1): max_py - (far_py - 1)]
            combine_mask = (tmp_mask + all_depth_mask).clip(0, 1) * hole_far * cross_element
            tmp_patch = combine_mask * (mask_depth[min_px: max_px, min_py: max_py] + all_depth_patch)
            number = np.count_nonzero(tmp_patch)
            if number > 0:
                mask_depth[far_px, far_py] = np.sum(tmp_patch).astype(np.float32) / max(number, 1e-6)
                hole_far_edge[far_px, far_py] = 1
                change = True
        near_pxs, near_pys = np.where((hole_near_edge == 0) * (init_near_edge == 1) > 0)
        current_hole_near_edge = hole_near_edge.copy()
        for near_px, near_py in zip(near_pxs, near_pys):
            min_px = max(near_px - 1, 0)
            max_px = min(near_px + 2, mask.shape[0] - 1)
            min_py = max(near_py - 1, 0)
            max_py = min(near_py + 2, mask.shape[1] - 1)
            hole_near = current_hole_near_edge[min_px: max_px, min_py: max_py]
            tmp_mask = mask[min_px: max_px, min_py: max_py]
            all_depth_patch = all_depth[min_px: max_px, min_py: max_py] * 0
            all_depth_mask = (all_depth_patch != 0).astype(np.uint8)
            cross_element = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])[min_px - near_px + 1:max_px - near_px + 1,
                            min_py - near_py + 1:max_py - near_py + 1]
            combine_mask = (tmp_mask + all_depth_mask).clip(0, 1) * hole_near * cross_element
            tmp_patch = combine_mask * (mask_depth[min_px: max_px, min_py: max_py] + all_depth_patch)
            number = np.count_nonzero(tmp_patch)
            if number > 0:
                mask_depth[near_px, near_py] = np.sum(tmp_patch) / max(number, 1e-6)
                hole_near_edge[near_px, near_py] = 1
                change = True
        if change is False:
            break

    return mask_depth


### bilateral_filtering


def sparse_bilateral_filtering(
        depth, image, config, HR=False, mask=None, num_iter=None):
    """
    config:
    - filter_size
    """
    save_images = []
    save_depths = []
    save_discontinuities = []
    vis_depth = depth.copy()

    for i in range(num_iter):
        if isinstance(config["filter_size"], list):
            window_size = config["filter_size"][i]
        else:
            window_size = config["filter_size"]
        vis_image = image.copy()
        save_images.append(vis_image)
        save_depths.append(vis_depth)
        u_over, b_over, l_over, r_over = vis_depth_discontinuity(vis_depth, config, mask=mask)
        vis_image[u_over > 0] = np.array([0, 0, 0])
        vis_image[b_over > 0] = np.array([0, 0, 0])
        vis_image[l_over > 0] = np.array([0, 0, 0])
        vis_image[r_over > 0] = np.array([0, 0, 0])

        discontinuity_map = (u_over + b_over + l_over + r_over).clip(0.0, 1.0)
        discontinuity_map[depth == 0] = 1
        save_discontinuities.append(discontinuity_map)
        if mask is not None:
            discontinuity_map[mask == 0] = 0
        vis_depth = bilateral_filter(
            vis_depth, config,
            discontinuity_map=discontinuity_map,
            mask=mask, window_size=window_size
        )

    return save_images, save_depths


def vis_depth_discontinuity(
        depth, config, vis_diff=False, label=False, mask=None):
    """
    config:
    -
    """
    if label == False:
        disp = 1. / depth
        u_diff = (disp[1:, :] - disp[:-1, :])[:-1, 1:-1]
        b_diff = (disp[:-1, :] - disp[1:, :])[1:, 1:-1]
        l_diff = (disp[:, 1:] - disp[:, :-1])[1:-1, :-1]
        r_diff = (disp[:, :-1] - disp[:, 1:])[1:-1, 1:]
        if mask is not None:
            u_mask = (mask[1:, :] * mask[:-1, :])[:-1, 1:-1]
            b_mask = (mask[:-1, :] * mask[1:, :])[1:, 1:-1]
            l_mask = (mask[:, 1:] * mask[:, :-1])[1:-1, :-1]
            r_mask = (mask[:, :-1] * mask[:, 1:])[1:-1, 1:]
            u_diff = u_diff * u_mask
            b_diff = b_diff * b_mask
            l_diff = l_diff * l_mask
            r_diff = r_diff * r_mask
        u_over = (np.abs(u_diff) > config['depth_threshold']).astype(np.float32)
        b_over = (np.abs(b_diff) > config['depth_threshold']).astype(np.float32)
        l_over = (np.abs(l_diff) > config['depth_threshold']).astype(np.float32)
        r_over = (np.abs(r_diff) > config['depth_threshold']).astype(np.float32)
    else:
        disp = depth
        u_diff = (disp[1:, :] * disp[:-1, :])[:-1, 1:-1]
        b_diff = (disp[:-1, :] * disp[1:, :])[1:, 1:-1]
        l_diff = (disp[:, 1:] * disp[:, :-1])[1:-1, :-1]
        r_diff = (disp[:, :-1] * disp[:, 1:])[1:-1, 1:]
        if mask is not None:
            u_mask = (mask[1:, :] * mask[:-1, :])[:-1, 1:-1]
            b_mask = (mask[:-1, :] * mask[1:, :])[1:, 1:-1]
            l_mask = (mask[:, 1:] * mask[:, :-1])[1:-1, :-1]
            r_mask = (mask[:, :-1] * mask[:, 1:])[1:-1, 1:]
            u_diff = u_diff * u_mask
            b_diff = b_diff * b_mask
            l_diff = l_diff * l_mask
            r_diff = r_diff * r_mask
        u_over = (np.abs(u_diff) > 0).astype(np.float32)
        b_over = (np.abs(b_diff) > 0).astype(np.float32)
        l_over = (np.abs(l_diff) > 0).astype(np.float32)
        r_over = (np.abs(r_diff) > 0).astype(np.float32)
    u_over = np.pad(u_over, 1, mode='constant')
    b_over = np.pad(b_over, 1, mode='constant')
    l_over = np.pad(l_over, 1, mode='constant')
    r_over = np.pad(r_over, 1, mode='constant')
    u_diff = np.pad(u_diff, 1, mode='constant')
    b_diff = np.pad(b_diff, 1, mode='constant')
    l_diff = np.pad(l_diff, 1, mode='constant')
    r_diff = np.pad(r_diff, 1, mode='constant')

    if vis_diff:
        return [u_over, b_over, l_over, r_over], [u_diff, b_diff, l_diff, r_diff]
    else:
        return [u_over, b_over, l_over, r_over]


def bilateral_filter(
        depth, config, discontinuity_map=None, mask=None, window_size=False):
    sigma_s = config['sigma_s']
    sigma_r = config['sigma_r']
    if window_size == False:
        window_size = config['filter_size']
    midpt = window_size // 2
    ax = np.arange(-midpt, midpt + 1.)
    xx, yy = np.meshgrid(ax, ax)
    if discontinuity_map is not None:
        spatial_term = np.exp(-(xx ** 2 + yy ** 2) / (2. * sigma_s ** 2))

    # padding
    depth = depth[1:-1, 1:-1]
    depth = np.pad(depth, ((1, 1), (1, 1)), 'edge')
    pad_depth = np.pad(depth, (midpt, midpt), 'edge')
    if discontinuity_map is not None:
        discontinuity_map = discontinuity_map[1:-1, 1:-1]
        discontinuity_map = np.pad(discontinuity_map, ((1, 1), (1, 1)), 'edge')
        pad_discontinuity_map = np.pad(discontinuity_map, (midpt, midpt), 'edge')
        pad_discontinuity_hole = 1 - pad_discontinuity_map
    # filtering
    output = depth.copy()
    pad_depth_patches = rolling_window(pad_depth, [window_size, window_size], [1, 1])
    if discontinuity_map is not None:
        pad_discontinuity_patches = rolling_window(pad_discontinuity_map, [window_size, window_size], [1, 1])
        pad_discontinuity_hole_patches = rolling_window(pad_discontinuity_hole, [window_size, window_size], [1, 1])

    if mask is not None:
        pad_mask = np.pad(mask, (midpt, midpt), 'constant')
        pad_mask_patches = rolling_window(pad_mask, [window_size, window_size], [1, 1])

    if discontinuity_map is not None:
        pH, pW = pad_depth_patches.shape[:2]
        for pi in range(pH):
            for pj in range(pW):
                if mask is not None and mask[pi, pj] == 0:
                    continue
                if discontinuity_map is not None:
                    if bool(pad_discontinuity_patches[pi, pj].any()) is False:
                        continue
                    discontinuity_patch = pad_discontinuity_patches[pi, pj]
                    discontinuity_holes = pad_discontinuity_hole_patches[pi, pj]
                depth_patch = pad_depth_patches[pi, pj]
                depth_order = depth_patch.ravel().argsort()
                patch_midpt = depth_patch[window_size // 2, window_size // 2]
                if discontinuity_map is not None:
                    coef = discontinuity_holes.astype(np.float32)
                    if mask is not None:
                        coef = coef * pad_mask_patches[pi, pj]
                else:
                    range_term = np.exp(-(depth_patch - patch_midpt) ** 2 / (2. * sigma_r ** 2))
                    coef = spatial_term * range_term
                if coef.max() == 0:
                    output[pi, pj] = patch_midpt
                    continue
                if discontinuity_map is not None and (coef.max() == 0):
                    output[pi, pj] = patch_midpt
                else:
                    coef = coef / (coef.sum())
                    coef_order = coef.ravel()[depth_order]
                    cum_coef = np.cumsum(coef_order)
                    ind = np.digitize(0.5, cum_coef)
                    output[pi, pj] = depth_patch.ravel()[depth_order][ind]
    else:
        pH, pW = pad_depth_patches.shape[:2]
        for pi in range(pH):
            for pj in range(pW):
                if discontinuity_map is not None:
                    if pad_discontinuity_patches[pi, pj][window_size // 2, window_size // 2] == 1:
                        continue
                    discontinuity_patch = pad_discontinuity_patches[pi, pj]
                    discontinuity_holes = (1. - discontinuity_patch)
                depth_patch = pad_depth_patches[pi, pj]
                depth_order = depth_patch.ravel().argsort()
                patch_midpt = depth_patch[window_size // 2, window_size // 2]
                range_term = np.exp(-(depth_patch - patch_midpt) ** 2 / (2. * sigma_r ** 2))
                if discontinuity_map is not None:
                    coef = spatial_term * range_term * discontinuity_holes
                else:
                    coef = spatial_term * range_term
                if coef.sum() == 0:
                    output[pi, pj] = patch_midpt
                    continue
                if discontinuity_map is not None and (coef.sum() == 0):
                    output[pi, pj] = patch_midpt
                else:
                    coef = coef / (coef.sum())
                    coef_order = coef.ravel()[depth_order]
                    cum_coef = np.cumsum(coef_order)
                    ind = np.digitize(0.5, cum_coef)
                    output[pi, pj] = depth_patch.ravel()[depth_order][ind]

    return output


def rolling_window(a, window, strides):
    assert len(a.shape) == len(window) == len(strides), "\'a\', \'window\', \'strides\' dimension mismatch"
    shape_fn = lambda i, w, s: (a.shape[i] - w) // s + 1
    shape = [shape_fn(i, w, s) for i, (w, s) in enumerate(zip(window, strides))] + list(window)

    def acc_shape(i):
        if i + 1 >= len(a.shape):
            return 1
        else:
            return functools.reduce(lambda x, y: x * y, a.shape[i + 1:])

    _strides = [acc_shape(i) * s * a.itemsize for i, s in enumerate(strides)] + list(a.strides)

    return np.lib.stride_tricks.as_strided(a, shape=shape, strides=_strides)


### mesh tool


def relabel_node(mesh, nodes, cur_node, new_node):
    if cur_node == new_node:
        return mesh
    mesh.add_node(new_node)
    for key, value in nodes[cur_node].items():
        nodes[new_node][key] = value
    for ne in mesh.neighbors(cur_node):
        mesh.add_edge(new_node, ne)
    mesh.remove_node(cur_node)

    return mesh


def filter_edge(mesh, edge_ccs, config, invalid=False):
    context_ccs = [set() for _ in edge_ccs]
    mesh_nodes = mesh.nodes
    for edge_id, edge_cc in enumerate(edge_ccs):
        if config['context_thickness'] == 0:
            continue
        edge_group = {}
        for edge_node in edge_cc:
            far_nodes = mesh_nodes[edge_node].get('far')
            if far_nodes is None:
                continue
            for far_node in far_nodes:
                context_ccs[edge_id].add(far_node)
                if mesh_nodes[far_node].get('edge_id') is not None:
                    if edge_group.get(mesh_nodes[far_node]['edge_id']) is None:
                        edge_group[mesh_nodes[far_node]['edge_id']] = set()
                    edge_group[mesh_nodes[far_node]['edge_id']].add(far_node)
        if len(edge_cc) > 2:
            for edge_key in [*edge_group.keys()]:
                if len(edge_group[edge_key]) == 1:
                    context_ccs[edge_id].remove([*edge_group[edge_key]][0])
    valid_edge_ccs = []
    for xidx, yy in enumerate(edge_ccs):
        if invalid is not True and len(context_ccs[xidx]) > 0:
            valid_edge_ccs.append(yy)
        elif invalid is True and len(context_ccs[xidx]) == 0:
            valid_edge_ccs.append(yy)
        else:
            valid_edge_ccs.append(set())

    return valid_edge_ccs


def extrapolate(
        global_mesh,
        info_on_pix,
        image,
        depth,
        other_edge_with_id,
        edge_map,
        edge_ccs,
        depth_edge_model,
        depth_feat_model,
        rgb_feat_model,
        config,
        direc='right-up'):
    h_off, w_off = global_mesh.graph['hoffset'], global_mesh.graph['woffset']
    noext_H, noext_W = global_mesh.graph['noext_H'], global_mesh.graph['noext_W']

    if "up" in direc.lower() and "-" not in direc.lower():
        all_anchor = [0, h_off + config['context_thickness'], w_off, w_off + noext_W]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [0, h_off, w_off, w_off + noext_W]
        context_anchor = [h_off, h_off + config['context_thickness'], w_off, w_off + noext_W]
        valid_line_anchor = [h_off, h_off + 1, w_off, w_off + noext_W]
        valid_anchor = [min(mask_anchor[0], context_anchor[0]), max(mask_anchor[1], context_anchor[1]),
                        min(mask_anchor[2], context_anchor[2]), max(mask_anchor[3], context_anchor[3])]
    elif "down" in direc.lower() and "-" not in direc.lower():
        all_anchor = [h_off + noext_H - config['context_thickness'], 2 * h_off + noext_H, w_off, w_off + noext_W]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [h_off + noext_H, 2 * h_off + noext_H, w_off, w_off + noext_W]
        context_anchor = [h_off + noext_H - config['context_thickness'], h_off + noext_H, w_off, w_off + noext_W]
        valid_line_anchor = [h_off + noext_H - 1, h_off + noext_H, w_off, w_off + noext_W]
        valid_anchor = [min(mask_anchor[0], context_anchor[0]), max(mask_anchor[1], context_anchor[1]),
                        min(mask_anchor[2], context_anchor[2]), max(mask_anchor[3], context_anchor[3])]
    elif "left" in direc.lower() and "-" not in direc.lower():
        all_anchor = [h_off, h_off + noext_H, 0, w_off + config['context_thickness']]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [h_off, h_off + noext_H, 0, w_off]
        context_anchor = [h_off, h_off + noext_H, w_off, w_off + config['context_thickness']]
        valid_line_anchor = [h_off, h_off + noext_H, w_off, w_off + 1]
        valid_anchor = [min(mask_anchor[0], context_anchor[0]), max(mask_anchor[1], context_anchor[1]),
                        min(mask_anchor[2], context_anchor[2]), max(mask_anchor[3], context_anchor[3])]
    elif "right" in direc.lower() and "-" not in direc.lower():
        all_anchor = [h_off, h_off + noext_H, w_off + noext_W - config['context_thickness'], 2 * w_off + noext_W]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [h_off, h_off + noext_H, w_off + noext_W, 2 * w_off + noext_W]
        context_anchor = [h_off, h_off + noext_H, w_off + noext_W - config['context_thickness'], w_off + noext_W]
        valid_line_anchor = [h_off, h_off + noext_H, w_off + noext_W - 1, w_off + noext_W]
        valid_anchor = [min(mask_anchor[0], context_anchor[0]), max(mask_anchor[1], context_anchor[1]),
                        min(mask_anchor[2], context_anchor[2]), max(mask_anchor[3], context_anchor[3])]
    elif "left" in direc.lower() and "up" in direc.lower() and "-" in direc.lower():
        all_anchor = [0, h_off + config['context_thickness'], 0, w_off + config['context_thickness']]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [0, h_off, 0, w_off]
        context_anchor = "inv-mask"
        valid_line_anchor = None
        valid_anchor = all_anchor
    elif "left" in direc.lower() and "down" in direc.lower() and "-" in direc.lower():
        all_anchor = [h_off + noext_H - config['context_thickness'], 2 * h_off + noext_H, 0,
                      w_off + config['context_thickness']]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [h_off + noext_H, 2 * h_off + noext_H, 0, w_off]
        context_anchor = "inv-mask"
        valid_line_anchor = None
        valid_anchor = all_anchor
    elif "right" in direc.lower() and "up" in direc.lower() and "-" in direc.lower():
        all_anchor = [0, h_off + config['context_thickness'], w_off + noext_W - config['context_thickness'],
                      2 * w_off + noext_W]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [0, h_off, w_off + noext_W, 2 * w_off + noext_W]
        context_anchor = "inv-mask"
        valid_line_anchor = None
        valid_anchor = all_anchor
    elif "right" in direc.lower() and "down" in direc.lower() and "-" in direc.lower():
        all_anchor = [h_off + noext_H - config['context_thickness'], 2 * h_off + noext_H,
                      w_off + noext_W - config['context_thickness'], 2 * w_off + noext_W]
        global_shift = [all_anchor[0], all_anchor[2]]
        mask_anchor = [h_off + noext_H, 2 * h_off + noext_H, w_off + noext_W, 2 * w_off + noext_W]
        context_anchor = "inv-mask"
        valid_line_anchor = None
        valid_anchor = all_anchor

    global_mask = np.zeros_like(depth)
    global_mask[mask_anchor[0]:mask_anchor[1], mask_anchor[2]:mask_anchor[3]] = 1
    mask = global_mask[valid_anchor[0]:valid_anchor[1], valid_anchor[2]:valid_anchor[3]] * 1
    context = 1 - mask
    global_context = np.zeros_like(depth)
    global_context[all_anchor[0]:all_anchor[1], all_anchor[2]:all_anchor[3]] = context

    valid_area = mask + context
    input_rgb = image[valid_anchor[0]:valid_anchor[1], valid_anchor[2]:valid_anchor[3]] / 255. * context[..., None]
    input_depth = depth[valid_anchor[0]:valid_anchor[1], valid_anchor[2]:valid_anchor[3]] * context
    log_depth = np.log(input_depth + 1e-8)
    log_depth[mask > 0] = 0
    input_mean_depth = np.mean(log_depth[context > 0])
    input_zero_mean_depth = (log_depth - input_mean_depth) * context

    input_disp = 1. / np.abs(input_depth)
    input_disp[mask > 0] = 0
    input_disp = input_disp / input_disp.max()
    valid_line = np.zeros_like(depth)
    if valid_line_anchor is not None:
        valid_line[valid_line_anchor[0]:valid_line_anchor[1], valid_line_anchor[2]:valid_line_anchor[3]] = 1
    valid_line = valid_line[all_anchor[0]:all_anchor[1], all_anchor[2]:all_anchor[3]]

    input_edge_map = edge_map[all_anchor[0]:all_anchor[1], all_anchor[2]:all_anchor[3]] * context
    input_other_edge_with_id = other_edge_with_id[all_anchor[0]:all_anchor[1], all_anchor[2]:all_anchor[3]]
    end_depth_maps = ((valid_line * input_edge_map) > 0) * input_depth

    valid_edge_ids = sorted(list(input_other_edge_with_id[(valid_line * input_edge_map) > 0]))
    valid_edge_ids = valid_edge_ids[1:] if (len(valid_edge_ids) > 0 and valid_edge_ids[0] == -1) else valid_edge_ids
    edge = functools.reduce(
        lambda x, y: (x + (input_other_edge_with_id == y).astype(np.uint8)).clip(0, 1),
        [np.zeros_like(mask)] + list(valid_edge_ids)
    )
    t_edge = edge[None, None, ...].astype(np.float32)
    t_rgb = np.expand_dims(input_rgb.transpose(2, 0, 1), axis=0).astype(np.float32)
    t_mask = mask[None, None, ...].astype(np.float32)
    t_context = context[None, None, ...].astype(np.float32)
    t_disp = input_disp[None, None, ...].astype(np.float32)
    t_depth_zero_mean_depth = input_zero_mean_depth[None, None, ...].astype(np.float32)

    edge_output = edge_forward_3P(
        depth_edge_model, t_mask, t_context, t_rgb, t_disp, t_edge)

    output_raw_edge = (edge_output > config['ext_edge_threshold']).astype(float) * t_mask + t_edge
    output_raw_edge = output_raw_edge.squeeze()

    mesh = netx.Graph()
    hxs, hys = np.where(output_raw_edge * mask > 0)
    for hx, hy in zip(hxs, hys):
        node = (hx, hy)
        mesh.add_node((hx, hy))
        eight_nes = [ne for ne in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1), \
                                   (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1), (hx + 1, hy - 1)] \
                     if 0 <= ne[0] < output_raw_edge.shape[0] and 0 <= ne[1] < output_raw_edge.shape[1] and 0 <
                     output_raw_edge[ne[0], ne[1]]]
        for ne in eight_nes:
            mesh.add_edge(node, ne, length=np.hypot(ne[0] - hx, ne[1] - hy))
            if end_depth_maps[ne[0], ne[1]] != 0:
                mesh.nodes[ne[0], ne[1]]['cnt'] = True
                mesh.nodes[ne[0], ne[1]]['depth'] = end_depth_maps[ne[0], ne[1]]
    ccs = [*netx.connected_components(mesh)]
    end_pts = []
    for cc in ccs:
        end_pts.append(set())
        for node in cc:
            if mesh.nodes[node].get('cnt') is not None:
                end_pts[-1].add((node[0], node[1], mesh.nodes[node]['depth']))
    fpath_map = np.zeros_like(output_raw_edge) - 1
    npath_map = np.zeros_like(output_raw_edge) - 1
    for end_pt, cc in zip(end_pts, ccs):
        if len(end_pt) >= 2:
            continue
        if len(end_pt) == 0:
            continue
        if len(end_pt) == 1:
            sub_mesh = mesh.subgraph(list(cc)).copy()
            pnodes = netx.periphery(sub_mesh)
            ends = [*end_pt]
            edge_id = global_mesh.nodes[(ends[0][0] + all_anchor[0], ends[0][1] + all_anchor[2], -ends[0][2])][
                'edge_id']
            pnodes = sorted(pnodes,
                            key=lambda x: np.hypot((x[0] - ends[0][0]), (x[1] - ends[0][1])),
                            reverse=True)[0]
            npath = [*netx.shortest_path(sub_mesh, (ends[0][0], ends[0][1]), pnodes, weight='length')]
            for np_node in npath:
                npath_map[np_node[0], np_node[1]] = edge_id
            fpath = []
            if global_mesh.nodes[(ends[0][0] + all_anchor[0], ends[0][1] + all_anchor[2], -ends[0][2])].get(
                    'far') is None:
                print("None far")
            else:
                fnodes = global_mesh.nodes[(ends[0][0] + all_anchor[0], ends[0][1] + all_anchor[2], -ends[0][2])].get(
                    'far')
                fnodes = [(xx[0] - all_anchor[0], xx[1] - all_anchor[2], xx[2]) for xx in fnodes]
                dmask = mask + 0
                did = 0
                while True:
                    did += 1
                    dmask = cv2.dilate(dmask, np.ones((3, 3)), iterations=1)
                    if did > 3:
                        break
                    # ffnode = [fnode for fnode in fnodes if (dmask[fnode[0], fnode[1]] > 0)]
                    ffnode = [fnode for fnode in fnodes if
                              (dmask[fnode[0], fnode[1]] > 0 and mask[fnode[0], fnode[1]] == 0)]
                    if len(ffnode) > 0:
                        fnode = ffnode[0]
                        break
                if len(ffnode) == 0:
                    continue
                fpath.append((fnode[0], fnode[1]))
                for step in range(0, len(npath) - 1):
                    parr = (npath[step + 1][0] - npath[step][0], npath[step + 1][1] - npath[step][1])
                    new_loc = (fpath[-1][0] + parr[0], fpath[-1][1] + parr[1])
                    new_loc_nes = [
                        xx for xx in [
                            (new_loc[0] + 1, new_loc[1]), (new_loc[0] - 1, new_loc[1]),
                            (new_loc[0], new_loc[1] + 1), (new_loc[0], new_loc[1] - 1)] \
                        if xx[0] >= 0 and xx[0] < fpath_map.shape[0] \
                           and xx[1] >= 0 and xx[1] < fpath_map.shape[1]
                    ]
                    if np.sum([fpath_map[nlne[0], nlne[1]] for nlne in new_loc_nes]) != -4:
                        break
                    if npath_map[new_loc[0], new_loc[1]] != -1:
                        if npath_map[new_loc[0], new_loc[1]] != edge_id:
                            break
                        else:
                            continue
                    if valid_area[new_loc[0], new_loc[1]] == 0:
                        break
                    new_loc_nes_eight = [xx for xx in [(new_loc[0] + 1, new_loc[1]), (new_loc[0] - 1, new_loc[1]),
                                                       (new_loc[0], new_loc[1] + 1), (new_loc[0], new_loc[1] - 1),
                                                       (new_loc[0] + 1, new_loc[1] + 1),
                                                       (new_loc[0] + 1, new_loc[1] - 1),
                                                       (new_loc[0] - 1, new_loc[1] - 1),
                                                       (new_loc[0] - 1, new_loc[1] + 1)] \
                                         if xx[0] >= 0 and xx[0] < fpath_map.shape[0] and xx[1] >= 0 and xx[1] <
                                         fpath_map.shape[1]]
                    if np.sum([int(npath_map[nlne[0], nlne[1]] == edge_id) for nlne in new_loc_nes_eight]) == 0:
                        break
                    fpath.append((fpath[-1][0] + parr[0], fpath[-1][1] + parr[1]))
                if step != len(npath) - 2:
                    for xx in npath[step + 1:]:
                        if npath_map[xx[0], xx[1]] == edge_id:
                            npath_map[xx[0], xx[1]] = -1
            if len(fpath) > 0:
                for fp_node in fpath:
                    fpath_map[fp_node[0], fp_node[1]] = edge_id

    update_edge = (npath_map > -1) * mask + edge
    t_update_edge = update_edge[None, None, ...].astype(np.float32)

    depth_output = depth_forward_3P(
        depth_feat_model, t_mask, t_context, t_depth_zero_mean_depth, t_update_edge)

    depth_output = depth_output.squeeze()
    depth_output = np.exp(depth_output + input_mean_depth) * mask  # + input_depth * context
    for near_id in np.unique(npath_map[npath_map > -1]):
        depth_output = refine_depth_around_edge(
            depth_output.copy(),
            (fpath_map == near_id).astype(np.uint8) * mask,  # far_edge_map_in_mask,
            (fpath_map == near_id).astype(np.uint8),  # far_edge_map,
            (npath_map == near_id).astype(np.uint8) * mask,
            mask.copy(),
            np.zeros_like(mask),
            config)

    rgb_output = color_forward_3P(rgb_feat_model, t_mask, t_context, t_rgb, t_update_edge)

    rgb_output = (
            (rgb_output.squeeze().transpose(1, 2, 0) * mask[..., None] + input_rgb) * 255).astype(
        np.uint8)
    image[all_anchor[0]:all_anchor[1], all_anchor[2]:all_anchor[3]][mask > 0] = rgb_output[
        mask > 0]  # np.array([255,0,0]) # rgb_output[mask > 0]
    depth[all_anchor[0]:all_anchor[1], all_anchor[2]:all_anchor[3]][mask > 0] = depth_output[mask > 0]

    nxs, nys = np.where((npath_map > -1))
    for nx, ny in zip(nxs, nys):
        n_id = npath_map[nx, ny]
        four_nes = [xx for xx in [(nx + 1, ny), (nx - 1, ny), (nx, ny + 1), (nx, ny - 1)] \
                    if 0 <= xx[0] < fpath_map.shape[0] and 0 <= xx[1] < fpath_map.shape[1]]
        for nex, ney in four_nes:
            if fpath_map[nex, ney] == n_id:
                na, nb = (nx + all_anchor[0], ny + all_anchor[2],
                          info_on_pix[(nx + all_anchor[0], ny + all_anchor[2])][0]['depth']), \
                         (nex + all_anchor[0], ney + all_anchor[2],
                          info_on_pix[(nex + all_anchor[0], ney + all_anchor[2])][0]['depth'])
                if global_mesh.has_edge(na, nb):
                    global_mesh.remove_edge(na, nb)
    nxs, nys = np.where((fpath_map > -1))
    for nx, ny in zip(nxs, nys):
        n_id = fpath_map[nx, ny]
        four_nes = [xx for xx in [(nx + 1, ny), (nx - 1, ny), (nx, ny + 1), (nx, ny - 1)] \
                    if 0 <= xx[0] < npath_map.shape[0] and 0 <= xx[1] < npath_map.shape[1]]
        for nex, ney in four_nes:
            if npath_map[nex, ney] == n_id:
                na, nb = (nx + all_anchor[0], ny + all_anchor[2],
                          info_on_pix[(nx + all_anchor[0], ny + all_anchor[2])][0]['depth']), \
                         (nex + all_anchor[0], ney + all_anchor[2],
                          info_on_pix[(nex + all_anchor[0], ney + all_anchor[2])][0]['depth'])
                if global_mesh.has_edge(na, nb):
                    global_mesh.remove_edge(na, nb)
    nxs, nys = np.where(mask > 0)
    for x, y in zip(nxs, nys):
        x = x + all_anchor[0]
        y = y + all_anchor[2]
        cur_node = (x, y, 0)
        new_node = (x, y, -abs(depth[x, y]))
        disp = 1. / -abs(depth[x, y])
        mapping_dict = {cur_node: new_node}
        info_on_pix, global_mesh = update_info(mapping_dict, info_on_pix, global_mesh)
        global_mesh.nodes[new_node]['color'] = image[x, y]
        global_mesh.nodes[new_node]['old_color'] = image[x, y]
        global_mesh.nodes[new_node]['disp'] = disp
        info_on_pix[(x, y)][0]['depth'] = -abs(depth[x, y])
        info_on_pix[(x, y)][0]['disp'] = disp
        info_on_pix[(x, y)][0]['color'] = image[x, y]

    nxs, nys = np.where((npath_map > -1))
    for nx, ny in zip(nxs, nys):
        self_node = (
            nx + all_anchor[0], ny + all_anchor[2], info_on_pix[(nx + all_anchor[0], ny + all_anchor[2])][0]['depth'])
        if global_mesh.has_node(self_node) is False:
            break
        n_id = int(round(npath_map[nx, ny]))
        four_nes = [xx for xx in [(nx + 1, ny), (nx - 1, ny), (nx, ny + 1), (nx, ny - 1)] \
                    if 0 <= xx[0] < fpath_map.shape[0] and 0 <= xx[1] < fpath_map.shape[1]]
        for nex, ney in four_nes:
            ne_node = (nex + all_anchor[0], ney + all_anchor[2],
                       info_on_pix[(nex + all_anchor[0], ney + all_anchor[2])][0]['depth'])
            if global_mesh.has_node(ne_node) is False:
                continue
            if fpath_map[nex, ney] == n_id:
                if global_mesh.nodes[self_node].get('edge_id') is None:
                    global_mesh.nodes[self_node]['edge_id'] = n_id
                    edge_ccs[n_id].add(self_node)
                    info_on_pix[(self_node[0], self_node[1])][0]['edge_id'] = n_id
                if global_mesh.has_edge(self_node, ne_node) is True:
                    global_mesh.remove_edge(self_node, ne_node)
                if global_mesh.nodes[self_node].get('far') is None:
                    global_mesh.nodes[self_node]['far'] = []
                global_mesh.nodes[self_node]['far'].append(ne_node)

    global_fpath_map = np.zeros_like(other_edge_with_id) - 1
    global_fpath_map[all_anchor[0]:all_anchor[1], all_anchor[2]:all_anchor[3]] = fpath_map
    fpath_ids = np.unique(global_fpath_map)
    fpath_ids = fpath_ids[1:] if fpath_ids.shape[0] > 0 and fpath_ids[0] == -1 else []
    fpath_real_id_map = np.zeros_like(global_fpath_map) - 1
    for fpath_id in fpath_ids:
        fpath_real_id = np.unique(((global_fpath_map == fpath_id).astype(int) * (other_edge_with_id + 1)) - 1)
        fpath_real_id = fpath_real_id[1:] if fpath_real_id.shape[0] > 0 and fpath_real_id[0] == -1 else []
        fpath_real_id = fpath_real_id.astype(int)
        fpath_real_id = np.bincount(fpath_real_id).argmax()
        fpath_real_id_map[global_fpath_map == fpath_id] = fpath_real_id
    nxs, nys = np.where((fpath_map > -1))
    for nx, ny in zip(nxs, nys):
        self_node = (
            nx + all_anchor[0], ny + all_anchor[2], info_on_pix[(nx + all_anchor[0], ny + all_anchor[2])][0]['depth'])
        n_id = fpath_map[nx, ny]
        four_nes = [xx for xx in [(nx + 1, ny), (nx - 1, ny), (nx, ny + 1), (nx, ny - 1)] \
                    if 0 <= xx[0] < npath_map.shape[0] and 0 <= xx[1] < npath_map.shape[1]]
        for nex, ney in four_nes:
            ne_node = (nex + all_anchor[0], ney + all_anchor[2],
                       info_on_pix[(nex + all_anchor[0], ney + all_anchor[2])][0]['depth'])
            if global_mesh.has_node(ne_node) is False:
                continue
            if npath_map[nex, ney] == n_id or global_mesh.nodes[ne_node].get('edge_id') == n_id:
                if global_mesh.has_edge(self_node, ne_node) is True:
                    global_mesh.remove_edge(self_node, ne_node)
                if global_mesh.nodes[self_node].get('near') is None:
                    global_mesh.nodes[self_node]['near'] = []
                if global_mesh.nodes[self_node].get('edge_id') is None:
                    f_id = int(round(fpath_real_id_map[self_node[0], self_node[1]]))
                    global_mesh.nodes[self_node]['edge_id'] = f_id
                    info_on_pix[(self_node[0], self_node[1])][0]['edge_id'] = f_id
                    edge_ccs[f_id].add(self_node)
                global_mesh.nodes[self_node]['near'].append(ne_node)

    return info_on_pix, global_mesh, image, depth, edge_ccs


def get_valid_size(imap):
    x_max = np.where(imap.sum(1).squeeze() > 0)[0].max() + 1
    x_min = np.where(imap.sum(1).squeeze() > 0)[0].min()
    y_max = np.where(imap.sum(0).squeeze() > 0)[0].max() + 1
    y_min = np.where(imap.sum(0).squeeze() > 0)[0].min()
    size_dict = {'x_max': x_max, 'y_max': y_max, 'x_min': x_min, 'y_min': y_min}

    return size_dict


def dilate_valid_size(isize_dict, imap, dilate=[0, 0]):
    osize_dict = copy.deepcopy(isize_dict)
    osize_dict['x_min'] = max(0, osize_dict['x_min'] - dilate[0])
    osize_dict['x_max'] = min(imap.shape[0], osize_dict['x_max'] + dilate[0])
    osize_dict['y_min'] = max(0, osize_dict['y_min'] - dilate[0])
    osize_dict['y_max'] = min(imap.shape[1], osize_dict['y_max'] + dilate[1])

    return osize_dict


def size_operation(size_a, size_b, operation):
    assert operation == '+' or operation == '-', "Operation must be '+' (union) or '-' (exclude)"
    osize = {}
    if operation == '+':
        osize['x_min'] = min(size_a['x_min'], size_b['x_min'])
        osize['y_min'] = min(size_a['y_min'], size_b['y_min'])
        osize['x_max'] = max(size_a['x_max'], size_b['x_max'])
        osize['y_max'] = max(size_a['y_max'], size_b['y_max'])
    assert operation != '-', "Operation '-' is undefined !"

    return osize


def fill_dummy_bord(mesh, info_on_pix, image, depth, config):
    context = np.zeros_like(depth).astype(np.uint8)
    context[
    mesh.graph['hoffset']:mesh.graph['hoffset'] + mesh.graph['noext_H'],
    mesh.graph['woffset']:mesh.graph['woffset'] + mesh.graph['noext_W']
    ] = 1
    mask = 1 - context
    xs, ys = np.where(mask > 0)

    cur_depth = 0
    cur_disp = 0
    color = [0, 0, 0]
    for x, y in zip(xs, ys):
        cur_node = (x, y, cur_depth)
        mesh.add_node(cur_node, color=color,
                      synthesis=False,
                      disp=cur_disp,
                      cc_id=set(),
                      ext_pixel=True)
        info_on_pix[(x, y)] = [{'depth': cur_depth,
                                'color': mesh.nodes[(x, y, cur_depth)]['color'],
                                'synthesis': False,
                                'disp': mesh.nodes[cur_node]['disp'],
                                'ext_pixel': True}]
        # for x, y in zip(xs, ys):
        four_nes = [(xx, yy) for xx, yy in [(x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)] if \
                    0 <= x < mesh.graph['H'] and 0 <= y < mesh.graph['W'] and info_on_pix.get((xx, yy)) is not None]
        for ne in four_nes:
            # if (ne[0] - x) + (ne[1] - y) == 1 and info_on_pix.get((ne[0], ne[1])) is not None:
            mesh.add_edge(cur_node, (ne[0], ne[1], info_on_pix[(ne[0], ne[1])][0]['depth']))

    return mesh, info_on_pix


def enlarge_border(mesh, info_on_pix, depth, image, config):
    mesh.graph['hoffset'], mesh.graph['woffset'] = config['extrapolation_thickness'], config['extrapolation_thickness']
    mesh.graph['bord_up'], mesh.graph['bord_left'], mesh.graph['bord_down'], mesh.graph['bord_right'] = \
        0, 0, mesh.graph['H'], mesh.graph['W']
    # new_image = np.pad(image,
    #                    pad_width=((config['extrapolation_thickness'], config['extrapolation_thickness']),
    #                               (config['extrapolation_thickness'], config['extrapolation_thickness']), (0, 0)),
    #                    mode='constant')
    # new_depth = np.pad(depth,
    #                    pad_width=((config['extrapolation_thickness'], config['extrapolation_thickness']),
    #                               (config['extrapolation_thickness'], config['extrapolation_thickness'])),
    #                    mode='constant')

    return mesh, info_on_pix, depth, image


def fill_missing_node(mesh, info_on_pix, image, depth):
    for x in range(mesh.graph['bord_up'], mesh.graph['bord_down']):
        for y in range(mesh.graph['bord_left'], mesh.graph['bord_right']):
            if info_on_pix.get((x, y)) is None:
                print("fill missing node = ", x, y)
                re_depth, re_count = 0, 0
                for ne in [(x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)]:
                    if info_on_pix.get(ne) is not None:
                        re_depth += info_on_pix[ne][0]['depth']
                        re_count += 1
                if re_count == 0:
                    re_depth = -abs(depth[x, y])
                else:
                    re_depth = re_depth / re_count
                depth[x, y] = abs(re_depth)
                info_on_pix[(x, y)] = [{'depth': re_depth,
                                        'color': image[x, y],
                                        'synthesis': False,
                                        'disp': 1. / re_depth}]
                mesh.add_node((x, y, re_depth), color=image[x, y],
                              synthesis=False,
                              disp=1. / re_depth,
                              cc_id=set())
    return mesh, info_on_pix, depth


def refresh_bord_depth(mesh, info_on_pix, image, depth):
    H, W = mesh.graph['H'], mesh.graph['W']
    corner_nodes = [(mesh.graph['bord_up'], mesh.graph['bord_left']),
                    (mesh.graph['bord_up'], mesh.graph['bord_right'] - 1),
                    (mesh.graph['bord_down'] - 1, mesh.graph['bord_left']),
                    (mesh.graph['bord_down'] - 1, mesh.graph['bord_right'] - 1)]
    # (0, W - 1), (H - 1, 0), (H - 1, W - 1)]
    bord_nodes = []
    bord_nodes += [(mesh.graph['bord_up'], xx) for xx in
                   range(mesh.graph['bord_left'] + 1, mesh.graph['bord_right'] - 1)]
    bord_nodes += [(mesh.graph['bord_down'] - 1, xx) for xx in
                   range(mesh.graph['bord_left'] + 1, mesh.graph['bord_right'] - 1)]
    bord_nodes += [(xx, mesh.graph['bord_left']) for xx in
                   range(mesh.graph['bord_up'] + 1, mesh.graph['bord_down'] - 1)]
    bord_nodes += [(xx, mesh.graph['bord_right'] - 1) for xx in
                   range(mesh.graph['bord_up'] + 1, mesh.graph['bord_down'] - 1)]
    for xy in bord_nodes:
        tgt_loc = None
        if xy[0] == mesh.graph['bord_up']:
            tgt_loc = (xy[0] + 1, xy[1])  # (1, xy[1])
        elif xy[0] == mesh.graph['bord_down'] - 1:
            tgt_loc = (xy[0] - 1, xy[1])  # (H - 2, xy[1])
        elif xy[1] == mesh.graph['bord_left']:
            tgt_loc = (xy[0], xy[1] + 1)
        elif xy[1] == mesh.graph['bord_right'] - 1:
            tgt_loc = (xy[0], xy[1] - 1)
        if tgt_loc is not None:
            ne_infos = info_on_pix.get(tgt_loc)
            tgt_depth = ne_infos[0]['depth']
            new_node = (xy[0], xy[1], tgt_depth)
            src_node = (tgt_loc[0], tgt_loc[1], tgt_depth)
            tgt_nes_loc = [(xx[0], xx[1]) \
                           for xx in mesh.neighbors(src_node)]
            tgt_nes_loc = [(xx[0] - tgt_loc[0] + xy[0], xx[1] - tgt_loc[1] + xy[1]) for xx in tgt_nes_loc \
                           if abs(xx[0] - xy[0]) == 1 and abs(xx[1] - xy[1]) == 1]
            tgt_nes_loc = [xx for xx in tgt_nes_loc if info_on_pix.get(xx) is not None]
            tgt_nes_loc.append(tgt_loc)
            if info_on_pix.get(xy) is not None and len(info_on_pix.get(xy)) > 0:
                old_depth = info_on_pix[xy][0].get('depth')
                old_node = (xy[0], xy[1], old_depth)
                mesh.remove_edges_from([(old_ne, old_node) for old_ne in mesh.neighbors(old_node)])
                mesh.add_edges_from([((zz[0], zz[1], info_on_pix[zz][0]['depth']), old_node) for zz in tgt_nes_loc])
                mapping_dict = {old_node: new_node}
                # if old_node[2] == new_node[2]:
                #     print("mapping_dict = ", mapping_dict)
                info_on_pix, mesh = update_info(mapping_dict, info_on_pix, mesh)
            else:
                info_on_pix[xy] = []
                info_on_pix[xy][0] = info_on_pix[tgt_loc][0]
                info_on_pix['color'] = image[xy[0], xy[1]]
                info_on_pix['old_color'] = image[xy[0], xy[1]]
                mesh.add_node(new_node)
                mesh.add_edges_from([((zz[0], zz[1], info_on_pix[zz][0]['depth']), new_node) for zz in tgt_nes_loc])
            mesh.nodes[new_node]['far'] = None
            mesh.nodes[new_node]['near'] = None
            if mesh.nodes[src_node].get('far') is not None:
                redundant_nodes = [ne for ne in mesh.nodes[src_node]['far'] if (ne[0], ne[1]) == xy]
                [mesh.nodes[src_node]['far'].remove(aa) for aa in redundant_nodes]
            if mesh.nodes[src_node].get('near') is not None:
                redundant_nodes = [ne for ne in mesh.nodes[src_node]['near'] if (ne[0], ne[1]) == xy]
                [mesh.nodes[src_node]['near'].remove(aa) for aa in redundant_nodes]
    for xy in corner_nodes:
        hx, hy = xy
        four_nes = [xx for xx in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] if \
                    mesh.graph['bord_up'] <= xx[0] < mesh.graph['bord_down'] and \
                    mesh.graph['bord_left'] <= xx[1] < mesh.graph['bord_right']]
        ne_nodes = []
        ne_depths = []
        for ne_loc in four_nes:
            if info_on_pix.get(ne_loc) is not None:
                ne_depths.append(info_on_pix[ne_loc][0]['depth'])
                ne_nodes.append((ne_loc[0], ne_loc[1], info_on_pix[ne_loc][0]['depth']))
        new_node = (xy[0], xy[1], float(np.mean(ne_depths)))
        if info_on_pix.get(xy) is not None and len(info_on_pix.get(xy)) > 0:
            old_depth = info_on_pix[xy][0].get('depth')
            old_node = (xy[0], xy[1], old_depth)
            mesh.remove_edges_from([(old_ne, old_node) for old_ne in mesh.neighbors(old_node)])
            mesh.add_edges_from([(zz, old_node) for zz in ne_nodes])
            mapping_dict = {old_node: new_node}
            info_on_pix, mesh = update_info(mapping_dict, info_on_pix, mesh)
        else:
            info_on_pix[xy] = []
            info_on_pix[xy][0] = info_on_pix[ne_loc[-1]][0]
            info_on_pix['color'] = image[xy[0], xy[1]]
            info_on_pix['old_color'] = image[xy[0], xy[1]]
            mesh.add_node(new_node)
            mesh.add_edges_from([(zz, new_node) for zz in ne_nodes])
        mesh.nodes[new_node]['far'] = None
        mesh.nodes[new_node]['near'] = None
    for xy in bord_nodes + corner_nodes:
        depth[xy[0], xy[1]] = abs(info_on_pix[xy][0]['depth'])
    for xy in bord_nodes:
        cur_node = (xy[0], xy[1], info_on_pix[xy][0]['depth'])
        nes = mesh.neighbors(cur_node)
        four_nes = set([(xy[0] + 1, xy[1]), (xy[0] - 1, xy[1]), (xy[0], xy[1] + 1), (xy[0], xy[1] - 1)]) - \
                   set([(ne[0], ne[1]) for ne in nes])
        four_nes = [ne for ne in four_nes if mesh.graph['bord_up'] <= ne[0] < mesh.graph['bord_down'] and \
                    mesh.graph['bord_left'] <= ne[1] < mesh.graph['bord_right']]
        four_nes = [(ne[0], ne[1], info_on_pix[(ne[0], ne[1])][0]['depth']) for ne in four_nes]
        mesh.nodes[cur_node]['far'] = []
        mesh.nodes[cur_node]['near'] = []
        for ne in four_nes:
            if abs(ne[2]) >= abs(cur_node[2]):
                mesh.nodes[cur_node]['far'].append(ne)
            else:
                mesh.nodes[cur_node]['near'].append(ne)

    return mesh, info_on_pix, depth


def depth_inpainting(
        context_cc, extend_context_cc, erode_context_cc, mask_cc, mesh,
        config, union_size, depth_feat_model, edge_output,
        given_depth_dict=False, spdb=False):
    if given_depth_dict is False:
        depth_dict = get_depth_from_nodes(context_cc | extend_context_cc, erode_context_cc, mask_cc, mesh.graph['H'],
                                          mesh.graph['W'], mesh, config['log_depth'])
        if edge_output is not None:
            depth_dict['edge'] = edge_output
    else:
        depth_dict = given_depth_dict
    patch_depth_dict = dict()
    patch_depth_dict['mask'], patch_depth_dict['context'], patch_depth_dict['depth'], \
    patch_depth_dict['zero_mean_depth'], patch_depth_dict['edge'] = \
        crop_maps_by_size(union_size, depth_dict['mask'], depth_dict['context'],
                          depth_dict['real_depth'], depth_dict['zero_mean_depth'], depth_dict['edge'])
    tensor_depth_dict = convert2tensor(patch_depth_dict)
    resize_mask = open_small_mask(tensor_depth_dict['mask'], tensor_depth_dict['context'], 3, 41)

    depth_output = depth_forward_3P(
        depth_feat_model,
        resize_mask, tensor_depth_dict['context'],
        tensor_depth_dict['zero_mean_depth'], tensor_depth_dict['edge'])

    tensor_depth_dict['output'] = \
        np.exp(depth_output + depth_dict['mean_depth']) * \
        tensor_depth_dict['mask'] + tensor_depth_dict['depth']
    patch_depth_dict['output'] = tensor_depth_dict['output'].squeeze()
    depth_dict['output'] = np.zeros((mesh.graph['H'], mesh.graph['W']))
    depth_dict['output'][union_size['x_min']:union_size['x_max'], union_size['y_min']:union_size['y_max']] = \
        patch_depth_dict['output']
    depth_output = smooth_cntsyn_gap(
        depth_dict['output'].copy() * depth_dict['mask'] + depth_dict['depth'] * depth_dict['context'],
        depth_dict['mask'], depth_dict['context'],
        init_mask_region=depth_dict['mask'])

    if spdb is True:
        f, ((ax1, ax2)) = plt.subplots(1, 2, sharex=True, sharey=True);
        ax1.imshow(depth_output * depth_dict['mask'] + depth_dict['depth']);
        ax2.imshow(depth_dict['output'] * depth_dict['mask'] + depth_dict['depth']);
        plt.show()

    depth_dict['output'] = depth_output * depth_dict['mask'] + depth_dict['depth'] * depth_dict['context']

    return depth_dict


def update_info(mapping_dict, info_on_pix, *meshes):
    rt_meshes = []
    for mesh in meshes:
        rt_meshes.append(
            relabel_node(mesh, mesh.nodes, [*mapping_dict.keys()][0], [*mapping_dict.values()][0])
        )
    x, y, _ = [*mapping_dict.keys()][0]
    info_on_pix[(x, y)][0]['depth'] = [*mapping_dict.values()][0][2]

    return [info_on_pix] + rt_meshes


def build_connection(mesh, cur_node, dst_node):
    if (abs(cur_node[0] - dst_node[0]) + abs(cur_node[1] - dst_node[1])) < 2:
        mesh.add_edge(cur_node, dst_node)
    if abs(cur_node[0] - dst_node[0]) > 1 or abs(cur_node[1] - dst_node[1]) > 1:
        return mesh
    ne_nodes = [*mesh.neighbors(cur_node)].copy()
    for ne_node in ne_nodes:
        if mesh.has_edge(ne_node, dst_node) or ne_node == dst_node:
            continue
        else:
            mesh = build_connection(mesh, ne_node, dst_node)

    return mesh


def recursive_add_edge(edge_mesh, mesh, info_on_pix, cur_node, mark):
    ne_nodes = [(x[0], x[1]) for x in edge_mesh.neighbors(cur_node)]
    for node_xy in ne_nodes:
        node = (node_xy[0], node_xy[1], info_on_pix[node_xy][0]['depth'])
        if mark[node[0], node[1]] != 3:
            continue
        else:
            mark[node[0], node[1]] = 0
            mesh.remove_edges_from([(xx, node) for xx in mesh.neighbors(node)])
            mesh = build_connection(mesh, cur_node, node)
            re_info = dict(depth=0, count=0)
            for re_ne in mesh.neighbors(node):
                re_info['depth'] += re_ne[2]
                re_info['count'] += 1.
            try:
                re_depth = re_info['depth'] / re_info['count']
            except:
                re_depth = node[2]
            re_node = (node_xy[0], node_xy[1], re_depth)
            mapping_dict = {node: re_node}
            info_on_pix, edge_mesh, mesh = update_info(mapping_dict, info_on_pix, edge_mesh, mesh)

            edge_mesh, mesh, mark, info_on_pix = recursive_add_edge(edge_mesh, mesh, info_on_pix, re_node, mark)

    return edge_mesh, mesh, mark, info_on_pix


def get_map_from_ccs(
        ccs, height, width, condition_input=None, condition=None, real_id=False, id_shift=0):
    if condition is None:
        condition = lambda x, condition_input: True

    if real_id is True:
        omap = np.zeros((height, width)) + (-1) + id_shift
    else:
        omap = np.zeros((height, width))
    for cc_id, cc in enumerate(ccs):
        for n in cc:
            if condition(n, condition_input):
                if real_id is True:
                    omap[n[0], n[1]] = cc_id + id_shift
                else:
                    omap[n[0], n[1]] = 1
    return omap


def get_depth_from_maps(context_map, mask_map, depth_map, H, W, log_depth=False):
    context = context_map.astype(np.uint8)
    mask = mask_map.astype(np.uint8).copy()
    depth = np.abs(depth_map)
    real_depth = depth.copy()
    zero_mean_depth = np.zeros((H, W))

    if log_depth is True:
        log_depth = np.log(real_depth + 1e-8) * context
        mean_depth = np.mean(log_depth[context > 0])
        zero_mean_depth = (log_depth - mean_depth) * context
    else:
        zero_mean_depth = real_depth
        mean_depth = 0
    edge = np.zeros_like(depth)

    rt_dict = {'depth': depth, 'real_depth': real_depth, 'context': context, 'mask': mask,
               'mean_depth': mean_depth, 'zero_mean_depth': zero_mean_depth, 'edge': edge}

    return rt_dict


def get_edge_from_nodes(
        context_cc, erode_context_cc, mask_cc, edge_cc, extend_edge_cc, H, W, mesh):
    context = np.zeros((H, W))
    mask = np.zeros((H, W))
    rgb = np.zeros((H, W, 3))
    disp = np.zeros((H, W))
    depth = np.zeros((H, W))
    real_depth = np.zeros((H, W))
    edge = np.zeros((H, W))
    comp_edge = np.zeros((H, W))
    fpath_map = np.zeros((H, W)) - 1
    npath_map = np.zeros((H, W)) - 1
    near_depth = np.zeros((H, W))
    for node in context_cc:
        rgb[node[0], node[1]] = np.array(mesh.nodes[node]['color'])
        disp[node[0], node[1]] = mesh.nodes[node]['disp']
        depth[node[0], node[1]] = node[2]
        context[node[0], node[1]] = 1
    for node in erode_context_cc:
        rgb[node[0], node[1]] = np.array(mesh.nodes[node]['color'])
        disp[node[0], node[1]] = mesh.nodes[node]['disp']
        depth[node[0], node[1]] = node[2]
        context[node[0], node[1]] = 1
    rgb = rgb / 255.
    disp = np.abs(disp)
    disp = disp / disp.max()
    real_depth = depth.copy()
    for node in context_cc:
        if mesh.nodes[node].get('real_depth') is not None:
            real_depth[node[0], node[1]] = mesh.nodes[node]['real_depth']
    for node in erode_context_cc:
        if mesh.nodes[node].get('real_depth') is not None:
            real_depth[node[0], node[1]] = mesh.nodes[node]['real_depth']
    for node in mask_cc:
        mask[node[0], node[1]] = 1
        near_depth[node[0], node[1]] = node[2]
    for node in edge_cc:
        edge[node[0], node[1]] = 1
    for node in extend_edge_cc:
        comp_edge[node[0], node[1]] = 1
    rt_dict = {'rgb': rgb, 'disp': disp, 'depth': depth, 'real_depth': real_depth, 'self_edge': edge,
               'context': context,
               'mask': mask, 'fpath_map': fpath_map, 'npath_map': npath_map, 'comp_edge': comp_edge,
               'valid_area': context + mask,
               'near_depth': near_depth}

    return rt_dict


def get_depth_from_nodes(
        context_cc, erode_context_cc, mask_cc, H, W, mesh, log_depth=False):
    context = np.zeros((H, W))
    mask = np.zeros((H, W))
    depth = np.zeros((H, W))
    real_depth = np.zeros((H, W))
    zero_mean_depth = np.zeros((H, W))
    for node in context_cc:
        depth[node[0], node[1]] = node[2]
        context[node[0], node[1]] = 1
    for node in erode_context_cc:
        depth[node[0], node[1]] = node[2]
        context[node[0], node[1]] = 1
    depth = np.abs(depth)
    real_depth = depth.copy()
    for node in context_cc:
        if mesh.nodes[node].get('real_depth') is not None:
            real_depth[node[0], node[1]] = mesh.nodes[node]['real_depth']
    for node in erode_context_cc:
        if mesh.nodes[node].get('real_depth') is not None:
            real_depth[node[0], node[1]] = mesh.nodes[node]['real_depth']
    real_depth = np.abs(real_depth)
    for node in mask_cc:
        mask[node[0], node[1]] = 1
    if log_depth is True:
        log_depth = np.log(real_depth + 1e-8) * context
        mean_depth = np.mean(log_depth[context > 0])
        zero_mean_depth = (log_depth - mean_depth) * context
    else:
        zero_mean_depth = real_depth
        mean_depth = 0

    rt_dict = {'depth': depth, 'real_depth': real_depth, 'context': context, 'mask': mask,
               'mean_depth': mean_depth, 'zero_mean_depth': zero_mean_depth}

    return rt_dict


def get_rgb_from_nodes(context_cc, erode_context_cc, mask_cc, H, W, mesh):
    context = np.zeros((H, W))
    mask = np.zeros((H, W))
    rgb = np.zeros((H, W, 3))
    erode_context = np.zeros((H, W))
    for node in context_cc:
        rgb[node[0], node[1]] = np.array(mesh.nodes[node]['color'])
        context[node[0], node[1]] = 1
    rgb = rgb / 255.
    for node in mask_cc:
        mask[node[0], node[1]] = 1
    for node in erode_context_cc:
        erode_context[node[0], node[1]] = 1
        mask[node[0], node[1]] = 1
    rt_dict = {'rgb': rgb, 'context': context, 'mask': mask,
               'erode': erode_context}

    return rt_dict


def crop_maps_by_size(size, *imaps):
    omaps = []
    for imap in imaps:
        omaps.append(imap[size['x_min']:size['x_max'], size['y_min']:size['y_max']].copy())

    return omaps


def convert2tensor(input_dict):
    rt_dict = {}
    for key, value in input_dict.items():
        if 'rgb' in key or 'color' in key:
            rt_dict[key] = value.transpose(2, 0, 1)[None, ...]
        else:
            rt_dict[key] = value[None, None, ...]

    return rt_dict


### mesh


def create_mesh(depth, image, int_mtx, config):
    H, W, C = image.shape
    ext_H, ext_W = H + 2 * config['extrapolation_thickness'], W + 2 * config['extrapolation_thickness']
    LDI = netx.Graph(H=ext_H, W=ext_W, noext_H=H, noext_W=W, cam_param=int_mtx)
    xy2depth = {}
    int_mtx_pix = int_mtx * np.array([[W], [H], [1.]])
    LDI.graph['cam_param_pix'], LDI.graph['cam_param_pix_inv'] = int_mtx_pix, np.linalg.inv(int_mtx_pix)
    disp = 1. / (-depth)
    LDI.graph['hoffset'], LDI.graph['woffset'] = config['extrapolation_thickness'], config['extrapolation_thickness']
    LDI.graph['bord_up'], LDI.graph['bord_down'] = LDI.graph['hoffset'] + 0, LDI.graph['hoffset'] + H
    LDI.graph['bord_left'], LDI.graph['bord_right'] = LDI.graph['woffset'] + 0, LDI.graph['woffset'] + W
    for idx in range(H):
        for idy in range(W):
            x, y = idx + LDI.graph['hoffset'], idy + LDI.graph['woffset']
            LDI.add_node((x, y, -depth[idx, idy]),
                         color=image[idx, idy],
                         disp=disp[idx, idy],
                         synthesis=False,
                         cc_id=set())
            xy2depth[(x, y)] = [-depth[idx, idy]]
    for x, y, d in LDI.nodes:
        two_nes = [ne for ne in [(x + 1, y), (x, y + 1)] if
                   ne[0] < LDI.graph['bord_down'] and ne[1] < LDI.graph['bord_right']]
        [LDI.add_edge((ne[0], ne[1], xy2depth[ne][0]), (x, y, d)) for ne in two_nes]
    LDI = calculate_fov(LDI)
    image = np.pad(image,
                   pad_width=((config['extrapolation_thickness'], config['extrapolation_thickness']),
                              (config['extrapolation_thickness'], config['extrapolation_thickness']),
                              (0, 0)),
                   mode='constant')
    depth = np.pad(depth,
                   pad_width=((config['extrapolation_thickness'], config['extrapolation_thickness']),
                              (config['extrapolation_thickness'], config['extrapolation_thickness'])),
                   mode='constant')

    return LDI, xy2depth, image, depth


def tear_edges(mesh, threshold=0.00025, xy2depth=None):
    remove_edge_list = []
    remove_horizon, remove_vertical = np.zeros((2, mesh.graph['H'], mesh.graph['W']))
    mesh_nodes = mesh.nodes
    for edge in mesh.edges:
        if abs(mesh_nodes[edge[0]]['disp'] - mesh_nodes[edge[1]]['disp']) > threshold:
            remove_edge_list.append((edge[0], edge[1]))

            near, far = edge if abs(edge[0][2]) < abs(edge[1][2]) else edge[::-1]

            mesh_nodes[far]['near'] = [] if mesh_nodes[far].get('near') is None else mesh_nodes[far]['near'].append(
                near)
            mesh_nodes[near]['far'] = [] if mesh_nodes[near].get('far') is None else mesh_nodes[near]['far'].append(far)

            if near[0] == far[0]:
                remove_horizon[near[0], np.minimum(near[1], far[1])] = 1
            elif near[1] == far[1]:
                remove_vertical[np.minimum(near[0], far[0]), near[1]] = 1
    mesh.remove_edges_from(remove_edge_list)

    remove_edge_list = []

    dang_horizon = np.where(np.roll(remove_horizon, 1, 0) + np.roll(remove_horizon, -1, 0) - remove_horizon == 2)
    dang_vertical = np.where(np.roll(remove_vertical, 1, 1) + np.roll(remove_vertical, -1, 1) - remove_vertical == 2)

    horizon_condition = lambda x, y: mesh.graph['bord_up'] + 1 <= x < mesh.graph['bord_down'] - 1
    vertical_condition = lambda x, y: mesh.graph['bord_left'] + 1 <= y < mesh.graph['bord_right'] - 1

    prjto3d = lambda x, y: (x, y, xy2depth[(x, y)][0])

    node_existence = lambda x, y: mesh.has_node(prjto3d(x, y))

    for x, y in zip(dang_horizon[0], dang_horizon[1]):
        if horizon_condition(x, y) and node_existence(x, y) and node_existence(x, y + 1):
            remove_edge_list.append((prjto3d(x, y), prjto3d(x, y + 1)))
    for x, y in zip(dang_vertical[0], dang_vertical[1]):
        if vertical_condition(x, y) and node_existence(x, y) and node_existence(x + 1, y):
            remove_edge_list.append((prjto3d(x, y), prjto3d(x + 1, y)))
    mesh.remove_edges_from(remove_edge_list)

    return mesh


def calculate_fov(mesh):
    k = mesh.graph['cam_param']
    mesh.graph['hFov'] = 2 * np.arctan(1. / (2 * k[0, 0]))
    mesh.graph['vFov'] = 2 * np.arctan(1. / (2 * k[1, 1]))
    mesh.graph['aspect'] = mesh.graph['noext_H'] / mesh.graph['noext_W']

    return mesh


def reproject_3d_int_detail(
        sx, sy, z, k_00, k_02, k_11, k_12, w_offset, h_offset):
    abs_z = abs(z)
    return [abs_z * ((sy + 0.5 - w_offset) * k_00 + k_02), abs_z * ((sx + 0.5 - h_offset) * k_11 + k_12), abs_z]


def generate_init_node(mesh, min_node_in_cc):
    mesh_nodes = mesh.nodes

    info_on_pix = {}

    ccs = sorted(netx.connected_components(mesh), key=len, reverse=True)
    remove_nodes = []

    for cc in ccs:

        remove_flag = True if len(cc) < min_node_in_cc else False
        if remove_flag is False:
            for (nx, ny, nd) in cc:
                info_on_pix[(nx, ny)] = [{'depth': nd,
                                          'color': mesh_nodes[(nx, ny, nd)]['color'],
                                          'synthesis': False,
                                          'disp': mesh_nodes[(nx, ny, nd)]['disp']}]
        else:
            [remove_nodes.append((nx, ny, nd)) for (nx, ny, nd) in cc]

    for node in remove_nodes:
        far_nodes = [] if mesh_nodes[node].get('far') is None else mesh_nodes[node]['far']
        for far_node in far_nodes:
            if mesh.has_node(far_node) and mesh_nodes[far_node].get('near') is not None and node in \
                    mesh_nodes[far_node]['near']:
                mesh_nodes[far_node]['near'].remove(node)
        near_nodes = [] if mesh_nodes[node].get('near') is None else mesh_nodes[node]['near']
        for near_node in near_nodes:
            if mesh.has_node(near_node) and mesh_nodes[near_node].get('far') is not None and node in \
                    mesh_nodes[near_node]['far']:
                mesh_nodes[near_node]['far'].remove(node)

    [mesh.remove_node(node) for node in remove_nodes]

    return mesh, info_on_pix


def get_neighbors(mesh, node):
    return [*mesh.neighbors(node)]


def generate_face(mesh, info_on_pix, config):
    H, W = mesh.graph['H'], mesh.graph['W']
    str_faces = []
    num_node = len(mesh.nodes)
    ply_flag = config.get('save_ply', False)

    def out_fmt(input, cur_id_b, cur_id_self, cur_id_a, ply_flag):
        if ply_flag is True:
            input.append(' '.join(['3', cur_id_b, cur_id_self, cur_id_a]) + '\n')
        else:
            input.append([cur_id_b, cur_id_self, cur_id_a])

    mesh_nodes = mesh.nodes
    for node in mesh_nodes:
        cur_id_self = mesh_nodes[node]['cur_id']
        ne_nodes = get_neighbors(mesh, node)
        four_dir_nes = {'up': [], 'left': [],
                        'down': [], 'right': []}
        for ne_node in ne_nodes:
            store_tuple = [ne_node, mesh_nodes[ne_node]['cur_id']]
            if ne_node[0] == node[0]:
                if ne_node[1] == ne_node[1] - 1:
                    four_dir_nes['left'].append(store_tuple)
                else:
                    four_dir_nes['right'].append(store_tuple)
            else:
                if ne_node[0] == ne_node[0] - 1:
                    four_dir_nes['up'].append(store_tuple)
                else:
                    four_dir_nes['down'].append(store_tuple)
        for node_a, cur_id_a in four_dir_nes['up']:
            for node_b, cur_id_b in four_dir_nes['right']:
                out_fmt(str_faces, cur_id_b, cur_id_self, cur_id_a, ply_flag)
        for node_a, cur_id_a in four_dir_nes['right']:
            for node_b, cur_id_b in four_dir_nes['down']:
                out_fmt(str_faces, cur_id_b, cur_id_self, cur_id_a, ply_flag)
        for node_a, cur_id_a in four_dir_nes['down']:
            for node_b, cur_id_b in four_dir_nes['left']:
                out_fmt(str_faces, cur_id_b, cur_id_self, cur_id_a, ply_flag)
        for node_a, cur_id_a in four_dir_nes['left']:
            for node_b, cur_id_b in four_dir_nes['up']:
                out_fmt(str_faces, cur_id_b, cur_id_self, cur_id_a, ply_flag)

    return str_faces


def reassign_floating_island(mesh, info_on_pix, image, depth):
    H, W = mesh.graph['H'], mesh.graph['W'],
    mesh_nodes = mesh.nodes
    bord_up, bord_down = mesh.graph['bord_up'], mesh.graph['bord_down']
    bord_left, bord_right = mesh.graph['bord_left'], mesh.graph['bord_right']
    W = mesh.graph['W']
    lost_map = np.zeros((H, W))

    '''
    (5) is_inside(x, y, xmin, xmax, ymin, ymax) : Check if a pixel(x, y) is inside the border.
    (6) get_cross_nes(x, y) : Get the four cross neighbors of pixel(x, y).
    '''
    key_exist = lambda d, k: k in d
    is_inside = lambda x, y, xmin, xmax, ymin, ymax: xmin <= x < xmax and ymin <= y < ymax
    get_cross_nes = lambda x, y: [(x + 1, y), (x - 1, y), (x, y - 1), (x, y + 1)]
    '''
    (A) Highlight the pixels on isolated floating island.
    (B) Number those isolated floating islands with connected component analysis.
    (C) For each isolated island:
        (1) Find its longest surrounded depth edge.
        (2) Propogate depth from that depth edge to the pixels on the isolated island.
        (3) Build the connection between the depth edge and that isolated island.
    '''
    for x in range(H):
        for y in range(W):
            if is_inside(x, y, bord_up, bord_down, bord_left, bord_right) and not (key_exist(info_on_pix, (x, y))):
                lost_map[x, y] = 1
    _, label_lost_map = cv2.connectedComponents(lost_map.astype(np.uint8), connectivity=4)
    mask = np.zeros((H, W))
    mask[bord_up:bord_down, bord_left:bord_right] = 1
    label_lost_map = (label_lost_map * mask).astype(int)

    for i in range(1, label_lost_map.max() + 1):
        lost_xs, lost_ys = np.where(label_lost_map == i)
        surr_edge_ids = {}
        for lost_x, lost_y in zip(lost_xs, lost_ys):
            for ne in get_cross_nes(lost_x, lost_y):
                if key_exist(info_on_pix, ne):
                    for info in info_on_pix[ne]:
                        ne_node = (ne[0], ne[1], info['depth'])
                        if key_exist(mesh_nodes[ne_node], 'edge_id'):
                            edge_id = mesh_nodes[ne_node]['edge_id']
                            surr_edge_ids[edge_id] = surr_edge_ids[edge_id] + [ne_node] if \
                                key_exist(surr_edge_ids, edge_id) else [ne_node]
        if len(surr_edge_ids) == 0:
            continue
        edge_id, edge_nodes = sorted([*surr_edge_ids.items()], key=lambda x: len(x[1]), reverse=True)[0]
        edge_depth_map = np.zeros((H, W))
        for node in edge_nodes:
            edge_depth_map[node[0], node[1]] = node[2]
        lost_xs, lost_ys = np.where(label_lost_map == i)
        while lost_xs.shape[0] > 0:
            lost_xs, lost_ys = np.where(label_lost_map == i)
            for lost_x, lost_y in zip(lost_xs, lost_ys):
                propagated_depth = []
                real_nes = []
                for ne in get_cross_nes(lost_x, lost_y):
                    if not (is_inside(ne[0], ne[1], bord_up, bord_down, bord_left, bord_right)) or \
                            edge_depth_map[ne[0], ne[1]] == 0:
                        continue
                    propagated_depth.append(edge_depth_map[ne[0], ne[1]])
                    real_nes.append(ne)
                if len(real_nes) == 0:
                    continue
                reassign_depth = np.mean(propagated_depth)
                label_lost_map[lost_x, lost_y] = 0
                edge_depth_map[lost_x, lost_y] = reassign_depth
                depth[lost_x, lost_y] = -reassign_depth
                mesh.add_node((lost_x, lost_y, reassign_depth), color=image[lost_x, lost_y],
                              synthesis=False,
                              disp=1. / reassign_depth,
                              cc_id=set())
                info_on_pix[(lost_x, lost_y)] = [{'depth': reassign_depth,
                                                  'color': image[lost_x, lost_y],
                                                  'synthesis': False,
                                                  'disp': 1. / reassign_depth}]
                new_connections = [((lost_x, lost_y, reassign_depth),
                                    (ne[0], ne[1], edge_depth_map[ne[0], ne[1]])) for ne in real_nes]
                mesh.add_edges_from(new_connections)

    return mesh, info_on_pix, depth


def remove_node_feat(mesh, *feats):
    mesh_nodes = mesh.nodes
    for node in mesh_nodes:
        for feat in feats:
            mesh_nodes[node][feat] = None

    return mesh


def update_status(mesh, info_on_pix, depth=None):
    '''
    (2) clear_node_feat(G, *fts) : Clear all the node feature on graph G.
    (6) get_cross_nes(x, y) : Get the four cross neighbors of pixel(x, y).
    '''
    key_exist = lambda d, k: d.get(k) is not None
    is_inside = lambda x, y, xmin, xmax, ymin, ymax: xmin <= x < xmax and ymin <= y < ymax
    get_cross_nes = lambda x, y: [(x + 1, y), (x - 1, y), (x, y - 1), (x, y + 1)]
    append_element = lambda d, k, x: d[k] + [x] if key_exist(d, k) else [x]

    def clear_node_feat(G, fts):
        le_nodes = G.nodes
        for k in le_nodes:
            v = le_nodes[k]
            for ft in fts:
                if ft in v:
                    v[ft] = None

    clear_node_feat(mesh, ['edge_id', 'far', 'near'])
    bord_up, bord_down = mesh.graph['bord_up'], mesh.graph['bord_down']
    bord_left, bord_right = mesh.graph['bord_left'], mesh.graph['bord_right']

    le_nodes = mesh.nodes

    for node_key in le_nodes:
        if mesh.neighbors(node_key).__length_hint__() == 4:
            continue
        four_nes = [xx for xx in get_cross_nes(node_key[0], node_key[1]) if
                    is_inside(xx[0], xx[1], bord_up, bord_down, bord_left, bord_right) and
                    xx in info_on_pix]
        [four_nes.remove((ne_node[0], ne_node[1])) for ne_node in mesh.neighbors(node_key)]
        for ne in four_nes:
            for info in info_on_pix[ne]:
                assert mesh.has_node((ne[0], ne[1], info['depth'])), "No node_key"
                ind_node = le_nodes[node_key]
                if abs(node_key[2]) > abs(info['depth']):
                    ind_node['near'] = append_element(ind_node, 'near', (ne[0], ne[1], info['depth']))
                else:
                    ind_node['far'] = append_element(ind_node, 'far', (ne[0], ne[1], info['depth']))
    if depth is not None:
        for key, value in info_on_pix.items():
            if depth[key[0], key[1]] != abs(value[0]['depth']):
                value[0]['disp'] = 1. / value[0]['depth']
                depth[key[0], key[1]] = abs(value[0]['depth'])

        return mesh, depth, info_on_pix
    else:
        return mesh


def group_edges(LDI, config, image, remove_conflict_ordinal, spdb=False):
    '''
    (1) add_new_node(G, node) : add "node" to graph "G"
    (2) add_new_edge(G, node_a, node_b) : add edge "node_a--node_b" to graph "G"
    (3) exceed_thre(x, y, thre) : Check if difference between "x" and "y" exceed threshold "thre"
    (4) key_exist(d, k) : Check if key "k' exists in dictionary "d"
    (5) comm_opp_bg(G, x, y) : Check if node "x" and "y" in graph "G" treat the same opposite node as background
    (6) comm_opp_fg(G, x, y) : Check if node "x" and "y" in graph "G" treat the same opposite node as foreground
    '''
    add_new_node = lambda G, node: None if G.has_node(node) else G.add_node(node)
    add_new_edge = lambda G, node_a, node_b: None if G.has_edge(node_a, node_b) else G.add_edge(node_a, node_b)
    exceed_thre = lambda x, y, thre: (abs(x) - abs(y)) > thre
    key_exist = lambda d, k: d.get(k) is not None
    comm_opp_bg = lambda G, x, y: key_exist(G.nodes[x], 'far') and key_exist(G.nodes[y], 'far') and \
                                  not (set(G.nodes[x]['far']).isdisjoint(set(G.nodes[y]['far'])))
    comm_opp_fg = lambda G, x, y: key_exist(G.nodes[x], 'near') and key_exist(G.nodes[y], 'near') and \
                                  not (set(G.nodes[x]['near']).isdisjoint(set(G.nodes[y]['near'])))
    discont_graph = netx.Graph()
    '''
    (A) Skip the pixel at image boundary, we don't want to deal with them.
    (B) Identify discontinuity by the number of its neighbor(degree).
        If the degree < 4(up/right/buttom/left). We will go through following steps:
        (1) Add the discontinuity pixel "node" to graph "discont_graph".
        (2) Find "node"'s cross neighbor(up/right/buttom/left) "ne_node".
            - If the cross neighbor "ne_node" is a discontinuity pixel(degree("ne_node") < 4),
                (a) add it to graph "discont_graph" and build the connection between "ne_node" and "node".
                (b) label its cross neighbor as invalid pixels "inval_diag_candi" to avoid building
                    connection between original discontinuity pixel "node" and "inval_diag_candi".
            - Otherwise, find "ne_node"'s cross neighbors, called diagonal candidate "diag_candi".
                - The "diag_candi" is diagonal to the original discontinuity pixel "node".
                - If "diag_candi" exists, go to step(3).
        (3) A diagonal candidate "diag_candi" will be :
            - added to the "discont_graph" if its degree < 4.
            - connected to the original discontinuity pixel "node" if it satisfied either
                one of following criterion:
                (a) the difference of disparity between "diag_candi" and "node" is smaller than default threshold.
                (b) the "diag_candi" and "node" face the same opposite pixel. (See. function "tear_edges")
                (c) Both of "diag_candi" and "node" must_connect to each other. (See. function "combine_end_node")
    (C) Aggregate each connected part in "discont_graph" into "discont_ccs" (A.K.A. depth edge).
    '''
    for node in LDI.nodes:
        if not (LDI.graph['bord_up'] + 1 <= node[0] <= LDI.graph['bord_down'] - 2 and \
                LDI.graph['bord_left'] + 1 <= node[1] <= LDI.graph['bord_right'] - 2):
            continue
        neighbors = [*LDI.neighbors(node)]
        if len(neighbors) < 4:
            add_new_node(discont_graph, node)
            diag_candi_anc, inval_diag_candi, discont_nes = set(), set(), set()
            for ne_node in neighbors:
                if len([*LDI.neighbors(ne_node)]) < 4:
                    add_new_node(discont_graph, ne_node)
                    add_new_edge(discont_graph, ne_node, node)
                    discont_nes.add(ne_node)
                else:
                    diag_candi_anc.add(ne_node)
            inval_diag_candi = set(
                [inval_diagonal for ne_node in discont_nes for inval_diagonal in LDI.neighbors(ne_node) if \
                 abs(inval_diagonal[0] - node[0]) < 2 and abs(inval_diagonal[1] - node[1]) < 2])
            for ne_node in diag_candi_anc:
                if ne_node[0] == node[0]:
                    diagonal_xys = [[ne_node[0] + 1, ne_node[1]], [ne_node[0] - 1, ne_node[1]]]
                elif ne_node[1] == node[1]:
                    diagonal_xys = [[ne_node[0], ne_node[1] + 1], [ne_node[0], ne_node[1] - 1]]
                for diag_candi in LDI.neighbors(ne_node):
                    if [diag_candi[0], diag_candi[1]] in diagonal_xys and LDI.degree(diag_candi) < 4:
                        if diag_candi not in inval_diag_candi:
                            if not exceed_thre(1. / node[2], 1. / diag_candi[2], config['depth_threshold']) or \
                                    (comm_opp_bg(LDI, diag_candi, node) and comm_opp_fg(LDI, diag_candi, node)):
                                add_new_node(discont_graph, diag_candi)
                                add_new_edge(discont_graph, diag_candi, node)
                        if key_exist(LDI.nodes[diag_candi], 'must_connect') and node in LDI.nodes[diag_candi][
                            'must_connect'] and \
                                key_exist(LDI.nodes[node], 'must_connect') and diag_candi in LDI.nodes[node][
                            'must_connect']:
                            add_new_node(discont_graph, diag_candi)
                            add_new_edge(discont_graph, diag_candi, node)
    discont_ccs = [*netx.connected_components(discont_graph)]
    '''
    In some corner case, a depth edge "discont_cc" will contain both
    foreground(FG) and background(BG) pixels. This violate the assumption that
    a depth edge can only composite by one type of pixel(FG or BG).
    We need to further divide this depth edge into several sub-part so that the
    assumption is satisfied.
    (A) A depth edge is invalid if both of its "far_flag"(BG) and
        "near_flag"(FG) are True.
    (B) If the depth edge is invalid, we need to do:
        (1) Find the role("oridinal") of each pixel on the depth edge.
            "-1" --> Its opposite pixels has smaller depth(near) than it.
                     It is a backgorund pixel.
            "+1" --> Its opposite pixels has larger depth(far) than it.
                     It is a foregorund pixel.
            "0"  --> Some of opposite pixels has larger depth(far) than it,
                     and some has smaller pixel than it.
                     It is an ambiguous pixel.
        (2) For each pixel "discont_node", check if its neigbhors' roles are consistent.
            - If not, break the connection between the neighbor "ne_node" that has a role
              different from "discont_node".
            - If yes, remove all the role that are inconsistent to its neighbors "ne_node".
        (3) Connected component analysis to re-identified those divided depth edge.
    (C) Aggregate each connected part in "discont_graph" into "discont_ccs" (A.K.A. depth edge).
    '''
    if remove_conflict_ordinal:
        new_discont_ccs = []
        num_new_cc = 0
        for edge_id, discont_cc in enumerate(discont_ccs):
            near_flag = False
            far_flag = False
            for discont_node in discont_cc:
                near_flag = True if key_exist(LDI.nodes[discont_node], 'far') else near_flag
                far_flag = True if key_exist(LDI.nodes[discont_node], 'near') else far_flag
                if far_flag and near_flag:
                    break
            if far_flag and near_flag:
                for discont_node in discont_cc:
                    discont_graph.nodes[discont_node]['ordinal'] = \
                        np.array([key_exist(LDI.nodes[discont_node], 'far'),
                                  key_exist(LDI.nodes[discont_node], 'near')]) * \
                        np.array([-1, 1])
                    discont_graph.nodes[discont_node]['ordinal'] = \
                        np.sum(discont_graph.nodes[discont_node]['ordinal'])
                remove_nodes, remove_edges = [], []
                for discont_node in discont_cc:
                    ordinal_relation = np.sum([discont_graph.nodes[xx]['ordinal'] \
                                               for xx in discont_graph.neighbors(discont_node)])
                    near_side = discont_graph.nodes[discont_node]['ordinal'] <= 0
                    if abs(ordinal_relation) < len([*discont_graph.neighbors(discont_node)]):
                        remove_nodes.append(discont_node)
                        for ne_node in discont_graph.neighbors(discont_node):
                            remove_flag = (near_side and not (key_exist(LDI.nodes[ne_node], 'far'))) or \
                                          (not near_side and not (key_exist(LDI.nodes[ne_node], 'near')))
                            remove_edges += [(discont_node, ne_node)] if remove_flag else []
                    else:
                        if near_side and key_exist(LDI.nodes[discont_node], 'near'):
                            LDI.nodes[discont_node].pop('near')
                        elif not (near_side) and key_exist(LDI.nodes[discont_node], 'far'):
                            LDI.nodes[discont_node].pop('far')
                discont_graph.remove_edges_from(remove_edges)
                sub_mesh = discont_graph.subgraph(list(discont_cc)).copy()
                sub_discont_ccs = [*netx.connected_components(sub_mesh)]
                is_redun_near = lambda xx: len(xx) == 1 and xx[0] in remove_nodes and key_exist(LDI.nodes[xx[0]], 'far')
                for sub_discont_cc in sub_discont_ccs:
                    if is_redun_near(list(sub_discont_cc)):
                        LDI.nodes[list(sub_discont_cc)[0]].pop('far')
                    new_discont_ccs.append(sub_discont_cc)
            else:
                new_discont_ccs.append(discont_cc)
        discont_ccs = new_discont_ccs
        new_discont_ccs = None

    for edge_id, edge_cc in enumerate(discont_ccs):
        for node in edge_cc:
            LDI.nodes[node]['edge_id'] = edge_id

    return discont_ccs, LDI, discont_graph


def combine_end_node(mesh, edge_mesh, edge_ccs, depth):
    import collections
    mesh_nodes = mesh.nodes
    connect_dict = dict()
    for valid_edge_id, valid_edge_cc in enumerate(edge_ccs):
        connect_info = []
        for valid_edge_node in valid_edge_cc:
            single_connect = set()
            for ne_node in mesh.neighbors(valid_edge_node):
                if mesh_nodes[ne_node].get('far') is not None:
                    for fn in mesh_nodes[ne_node].get('far'):
                        if mesh.has_node(fn) and mesh_nodes[fn].get('edge_id') is not None:
                            single_connect.add(mesh_nodes[fn]['edge_id'])
                if mesh_nodes[ne_node].get('near') is not None:
                    for fn in mesh_nodes[ne_node].get('near'):
                        if mesh.has_node(fn) and mesh_nodes[fn].get('edge_id') is not None:
                            single_connect.add(mesh_nodes[fn]['edge_id'])
            connect_info.extend([*single_connect])
        connect_dict[valid_edge_id] = collections.Counter(connect_info)

    end_maps = np.zeros((mesh.graph['H'], mesh.graph['W']))
    edge_maps = np.zeros((mesh.graph['H'], mesh.graph['W'])) - 1
    for valid_edge_id, valid_edge_cc in enumerate(edge_ccs):
        for valid_edge_node in valid_edge_cc:
            edge_maps[valid_edge_node[0], valid_edge_node[1]] = valid_edge_id
            if len([*edge_mesh.neighbors(valid_edge_node)]) == 1:
                num_ne = 1
                if num_ne == 1:
                    end_maps[valid_edge_node[0], valid_edge_node[1]] = valid_edge_node[2]
    nxs, nys = np.where(end_maps != 0)
    invalid_nodes = set()
    for nx, ny in zip(nxs, nys):
        if mesh.has_node((nx, ny, end_maps[nx, ny])) is False:
            invalid_nodes.add((nx, ny))
            continue
        four_nes = [xx for xx in [(nx - 1, ny), (nx + 1, ny), (nx, ny - 1), (nx, ny + 1)] \
                    if 0 <= xx[0] < mesh.graph['H'] and 0 <= xx[1] < mesh.graph['W'] and \
                    end_maps[xx[0], xx[1]] != 0]
        mesh_nes = [*mesh.neighbors((nx, ny, end_maps[nx, ny]))]
        remove_num = 0
        for fne in four_nes:
            if (fne[0], fne[1], end_maps[fne[0], fne[1]]) in mesh_nes:
                remove_num += 1
        if remove_num == len(four_nes):
            invalid_nodes.add((nx, ny))
    for invalid_node in invalid_nodes:
        end_maps[invalid_node[0], invalid_node[1]] = 0

    nxs, nys = np.where(end_maps != 0)
    invalid_nodes = set()
    for nx, ny in zip(nxs, nys):
        if mesh_nodes[(nx, ny, end_maps[nx, ny])].get('edge_id') is None:
            continue
        else:
            self_id = mesh_nodes[(nx, ny, end_maps[nx, ny])].get('edge_id')
            self_connect = connect_dict[self_id] if connect_dict.get(self_id) is not None else dict()
        four_nes = [xx for xx in [(nx - 1, ny), (nx + 1, ny), (nx, ny - 1), (nx, ny + 1)] \
                    if 0 <= xx[0] < mesh.graph['H'] and 0 <= xx[1] < mesh.graph['W'] and \
                    end_maps[xx[0], xx[1]] != 0]
        for fne in four_nes:
            if mesh_nodes[(fne[0], fne[1], end_maps[fne[0], fne[1]])].get('edge_id') is None:
                continue
            else:
                ne_id = mesh_nodes[(fne[0], fne[1], end_maps[fne[0], fne[1]])]['edge_id']
                if self_connect.get(ne_id) is None or self_connect.get(ne_id) == 1:
                    continue
                else:
                    invalid_nodes.add((nx, ny))
    for invalid_node in invalid_nodes:
        end_maps[invalid_node[0], invalid_node[1]] = 0
    nxs, nys = np.where(end_maps != 0)
    invalid_nodes = set()
    for nx, ny in zip(nxs, nys):
        four_nes = [xx for xx in [(nx - 1, ny), (nx + 1, ny), (nx, ny - 1), (nx, ny + 1)] \
                    if 0 <= xx[0] < mesh.graph['H'] and 0 <= xx[1] < mesh.graph['W'] and \
                    end_maps[xx[0], xx[1]] != 0]
        for fne in four_nes:
            if mesh.has_node((fne[0], fne[1], end_maps[fne[0], fne[1]])):
                node_a, node_b = (fne[0], fne[1], end_maps[fne[0], fne[1]]), (nx, ny, end_maps[nx, ny])
                mesh.add_edge(node_a, node_b)
                mesh_nodes[node_b]['must_connect'] = set() if mesh_nodes[node_b].get('must_connect') is None else \
                    mesh_nodes[node_b]['must_connect']
                mesh_nodes[node_b]['must_connect'].add(node_a)
                mesh_nodes[node_b]['must_connect'] |= set([xx for xx in [*edge_mesh.neighbors(node_a)] if \
                                                           (xx[0] - node_b[0]) < 2 and (xx[1] - node_b[1]) < 2])
                mesh_nodes[node_a]['must_connect'] = set() if mesh_nodes[node_a].get('must_connect') is None else \
                    mesh_nodes[node_a]['must_connect']
                mesh_nodes[node_a]['must_connect'].add(node_b)
                mesh_nodes[node_a]['must_connect'] |= set([xx for xx in [*edge_mesh.neighbors(node_b)] if \
                                                           (xx[0] - node_a[0]) < 2 and (xx[1] - node_a[1]) < 2])
                invalid_nodes.add((nx, ny))
    for invalid_node in invalid_nodes:
        end_maps[invalid_node[0], invalid_node[1]] = 0

    return mesh


def remove_redundant_edge(
        mesh, edge_mesh, edge_ccs, info_on_pix, config,
        redundant_number=1000, invalid=False, spdb=False):
    point_to_amount = {}
    point_to_id = {}
    end_maps = np.zeros((mesh.graph['H'], mesh.graph['W'])) - 1
    for valid_edge_id, valid_edge_cc in enumerate(edge_ccs):
        for valid_edge_node in valid_edge_cc:
            point_to_amount[valid_edge_node] = len(valid_edge_cc)
            point_to_id[valid_edge_node] = valid_edge_id
            if edge_mesh.has_node(valid_edge_node) is True:
                if len([*edge_mesh.neighbors(valid_edge_node)]) == 1:
                    end_maps[valid_edge_node[0], valid_edge_node[1]] = valid_edge_id
    nxs, nys = np.where(end_maps > -1)
    point_to_adjoint = {}
    for nx, ny in zip(nxs, nys):
        adjoint_edges = set([end_maps[x, y] for x, y in [(nx + 1, ny), (nx - 1, ny), (nx, ny + 1), (nx, ny - 1)] if
                             end_maps[x, y] != -1])
        point_to_adjoint[end_maps[nx, ny]] = (
                point_to_adjoint[end_maps[nx, ny]] | adjoint_edges) if point_to_adjoint.get(
            end_maps[nx, ny]) is not None else adjoint_edges
    valid_edge_ccs = filter_edge(mesh, edge_ccs, config, invalid=invalid)
    edge_canvas = np.zeros((mesh.graph['H'], mesh.graph['W'])) - 1
    for valid_edge_id, valid_edge_cc in enumerate(valid_edge_ccs):
        for valid_edge_node in valid_edge_cc:
            edge_canvas[valid_edge_node[0], valid_edge_node[1]] = valid_edge_id
    if spdb is True:
        plt.imshow(edge_canvas);
        plt.show()

    for valid_edge_id, valid_edge_cc in enumerate(valid_edge_ccs):
        end_number = 0
        four_end_number = 0
        eight_end_number = 0
        db_eight_end_number = 0
        if len(valid_edge_cc) > redundant_number:
            continue
        for valid_edge_node in valid_edge_cc:
            if len([*edge_mesh.neighbors(valid_edge_node)]) == 3:
                break
            elif len([*edge_mesh.neighbors(valid_edge_node)]) == 1:
                hx, hy, hz = valid_edge_node
                if invalid is False:
                    eight_nes = [(x, y) for x, y in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1),
                                                     (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1),
                                                     (hx + 1, hy - 1)] \
                                 if info_on_pix.get((x, y)) is not None and edge_canvas[x, y] != -1 and edge_canvas[
                                     x, y] != valid_edge_id]
                    if len(eight_nes) == 0:
                        end_number += 1
                if invalid is True:
                    four_nes = [];
                    eight_nes = [];
                    db_eight_nes = []
                    four_nes = [(x, y) for x, y in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] \
                                if info_on_pix.get((x, y)) is not None and edge_canvas[x, y] != -1 and edge_canvas[
                                    x, y] != valid_edge_id]
                    eight_nes = [(x, y) for x, y in [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1), \
                                                     (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1),
                                                     (hx + 1, hy - 1)] \
                                 if info_on_pix.get((x, y)) is not None and edge_canvas[x, y] != -1 and edge_canvas[
                                     x, y] != valid_edge_id]
                    db_eight_nes = [(x, y) for x in range(hx - 2, hx + 3) for y in range(hy - 2, hy + 3) \
                                    if info_on_pix.get((x, y)) is not None and edge_canvas[x, y] != -1 and edge_canvas[
                                        x, y] != valid_edge_id and (x, y) != (hx, hy)]
                    if len(four_nes) == 0 or len(eight_nes) == 0:
                        end_number += 1
                        if len(four_nes) == 0:
                            four_end_number += 1
                        if len(eight_nes) == 0:
                            eight_end_number += 1
                        if len(db_eight_nes) == 0:
                            db_eight_end_number += 1
            elif len([*edge_mesh.neighbors(valid_edge_node)]) == 0:
                hx, hy, hz = valid_edge_node
                four_nes = [(x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
                            [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] \
                            if info_on_pix.get((x, y)) is not None and \
                            mesh.has_edge(valid_edge_node, (x, y, info_on_pix[(x, y)][0]['depth'])) is False]
                for ne in four_nes:
                    try:
                        if invalid is True or (
                                point_to_amount.get(ne) is None or point_to_amount[ne] < redundant_number) or \
                                point_to_id[ne] in point_to_adjoint.get(point_to_id[valid_edge_node], set()):
                            mesh.add_edge(valid_edge_node, ne)
                    except:
                        raise
        if (invalid is not True and end_number >= 1) or (
                invalid is True and end_number >= 2 and eight_end_number >= 1 and db_eight_end_number >= 1):
            for valid_edge_node in valid_edge_cc:
                hx, hy, _ = valid_edge_node
                four_nes = [(x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
                            [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] \
                            if info_on_pix.get((x, y)) is not None and \
                            mesh.has_edge(valid_edge_node, (x, y, info_on_pix[(x, y)][0]['depth'])) is False and \
                            (edge_canvas[x, y] == -1 or edge_canvas[x, y] == valid_edge_id)]
                for ne in four_nes:
                    if invalid is True or (point_to_amount.get(ne) is None or point_to_amount[ne] < redundant_number) or \
                            point_to_id[ne] in point_to_adjoint.get(point_to_id[valid_edge_node], set()):
                        mesh.add_edge(valid_edge_node, ne)

    return mesh


def remove_dangling(mesh, edge_ccs, edge_mesh, info_on_pix, image, depth, config):
    tmp_edge_ccs = copy.deepcopy(edge_ccs)
    for edge_cc_id, valid_edge_cc in enumerate(tmp_edge_ccs):
        if len(valid_edge_cc) > 1 or len(valid_edge_cc) == 0:
            continue
        single_edge_node = [*valid_edge_cc][0]
        hx, hy, hz = single_edge_node
        eight_nes = set([
            (x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
            [
                (hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1),
                (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1), (hx + 1, hy - 1)
            ] if info_on_pix.get((x, y)) is not None])
        four_nes = [(x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
                    [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] \
                    if info_on_pix.get((x, y)) is not None]
        sub_mesh = mesh.subgraph(eight_nes).copy()
        ccs = netx.connected_components(sub_mesh)
        four_ccs = []
        for cc_id, _cc in enumerate(ccs):
            four_ccs.append(set())
            for cc_node in _cc:
                if abs(cc_node[0] - hx) + abs(cc_node[1] - hy) < 2:
                    four_ccs[cc_id].add(cc_node)
        largest_cc = sorted(four_ccs, key=lambda x: (len(x), -np.sum([abs(xx[2] - hz) for xx in x])))[-1]
        if len(largest_cc) < 2:
            for ne in four_nes:
                mesh.add_edge(single_edge_node, ne)
        else:
            mesh.remove_edges_from([(single_edge_node, ne) for ne in mesh.neighbors(single_edge_node)])
            new_depth = np.mean([xx[2] for xx in largest_cc])
            info_on_pix[(hx, hy)][0]['depth'] = new_depth
            info_on_pix[(hx, hy)][0]['disp'] = 1. / new_depth
            new_node = (hx, hy, new_depth)
            if netx.__name__ == "networkx":
                mesh = refresh_node(single_edge_node, mesh._node[single_edge_node], new_node, dict(), mesh)
            else:
                mesh = refresh_node(single_edge_node, mesh.node[single_edge_node], new_node, dict(), mesh)
            edge_ccs[edge_cc_id] = set([new_node])
            for ne in largest_cc:
                mesh.add_edge(new_node, ne)

    mark = np.zeros((mesh.graph['H'], mesh.graph['W']))
    for edge_idx, edge_cc in enumerate(edge_ccs):
        for edge_node in edge_cc:
            if not (mesh.graph['bord_up'] <= edge_node[0] < mesh.graph['bord_down'] - 1) or \
                    not (mesh.graph['bord_left'] <= edge_node[1] < mesh.graph['bord_right'] - 1):
                continue
            mesh_neighbors = [*mesh.neighbors(edge_node)]
            mesh_neighbors = [xx for xx in mesh_neighbors \
                              if mesh.graph['bord_up'] < xx[0] < mesh.graph['bord_down'] - 1 and \
                              mesh.graph['bord_left'] < xx[1] < mesh.graph['bord_right'] - 1]
            if len([*mesh.neighbors(edge_node)]) >= 3:
                continue
            elif len([*mesh.neighbors(edge_node)]) <= 1:
                mark[edge_node[0], edge_node[1]] += (len([*mesh.neighbors(edge_node)]) + 1)
            else:
                dan_ne_node_a = [*mesh.neighbors(edge_node)][0]
                dan_ne_node_b = [*mesh.neighbors(edge_node)][1]
                if abs(dan_ne_node_a[0] - dan_ne_node_b[0]) > 1 or \
                        abs(dan_ne_node_a[1] - dan_ne_node_b[1]) > 1:
                    mark[edge_node[0], edge_node[1]] += 3
    mxs, mys = np.where(mark == 1)
    conn_0_nodes = [(x[0], x[1], info_on_pix[(x[0], x[1])][0]['depth']) for x in zip(mxs, mys) \
                    if mesh.has_node((x[0], x[1], info_on_pix[(x[0], x[1])][0]['depth']))]
    mxs, mys = np.where(mark == 2)
    conn_1_nodes = [(x[0], x[1], info_on_pix[(x[0], x[1])][0]['depth']) for x in zip(mxs, mys) \
                    if mesh.has_node((x[0], x[1], info_on_pix[(x[0], x[1])][0]['depth']))]
    for node in conn_0_nodes:
        hx, hy = node[0], node[1]
        four_nes = [(x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
                    [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1)] \
                    if info_on_pix.get((x, y)) is not None]
        re_depth = {'value': 0, 'count': 0}
        for ne in four_nes:
            mesh.add_edge(node, ne)
            re_depth['value'] += cc_node[2]
            re_depth['count'] += 1.
        re_depth = re_depth['value'] / re_depth['count']
        mapping_dict = {node: (node[0], node[1], re_depth)}
        info_on_pix, mesh, edge_mesh = update_info(mapping_dict, info_on_pix, mesh, edge_mesh)
        depth[node[0], node[1]] = abs(re_depth)
        mark[node[0], node[1]] = 0
    for node in conn_1_nodes:
        hx, hy = node[0], node[1]
        eight_nes = set([(x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
                         [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1),
                          (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1), (hx + 1, hy - 1)] \
                         if info_on_pix.get((x, y)) is not None])
        self_nes = set([ne2 for ne1 in mesh.neighbors(node) for ne2 in mesh.neighbors(ne1) if ne2 in eight_nes])
        eight_nes = [*(eight_nes - self_nes)]
        sub_mesh = mesh.subgraph(eight_nes).copy()
        ccs = netx.connected_components(sub_mesh)
        largest_cc = \
            sorted(ccs, key=lambda x: (len(x), -np.sum([abs(xx[0] - node[0]) + abs(xx[1] - node[1]) for xx in x])))[-1]

        mesh.remove_edges_from([(xx, node) for xx in mesh.neighbors(node)])
        re_depth = {'value': 0, 'count': 0}
        for cc_node in largest_cc:
            if cc_node[0] == node[0] and cc_node[1] == node[1]:
                continue
            re_depth['value'] += cc_node[2]
            re_depth['count'] += 1.
            if abs(cc_node[0] - node[0]) + abs(cc_node[1] - node[1]) < 2:
                mesh.add_edge(cc_node, node)
        try:
            re_depth = re_depth['value'] / re_depth['count']
        except:
            re_depth = node[2]
        renode = (node[0], node[1], re_depth)
        mapping_dict = {node: renode}
        info_on_pix, mesh, edge_mesh = update_info(mapping_dict, info_on_pix, mesh, edge_mesh)
        depth[node[0], node[1]] = abs(re_depth)
        mark[node[0], node[1]] = 0
        edge_mesh, mesh, mark, info_on_pix = recursive_add_edge(edge_mesh, mesh, info_on_pix, renode, mark)
    mxs, mys = np.where(mark == 3)
    conn_2_nodes = [(x[0], x[1], info_on_pix[(x[0], x[1])][0]['depth']) for x in zip(mxs, mys) \
                    if mesh.has_node((x[0], x[1], info_on_pix[(x[0], x[1])][0]['depth'])) and \
                    mesh.degree((x[0], x[1], info_on_pix[(x[0], x[1])][0]['depth'])) == 2]
    sub_mesh = mesh.subgraph(conn_2_nodes).copy()
    ccs = netx.connected_components(sub_mesh)
    for cc in ccs:
        candidate_nodes = [xx for xx in cc if sub_mesh.degree(xx) == 1]
        for node in candidate_nodes:
            if mesh.has_node(node) is False:
                continue
            ne_node = [xx for xx in mesh.neighbors(node) if xx not in cc][0]
            hx, hy = node[0], node[1]
            eight_nes = set([(x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
                             [(hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1),
                              (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1), (hx + 1, hy - 1)] \
                             if
                             info_on_pix.get((x, y)) is not None and (x, y, info_on_pix[(x, y)][0]['depth']) not in cc])
            ne_sub_mesh = mesh.subgraph(eight_nes).copy()
            ne_ccs = netx.connected_components(ne_sub_mesh)
            try:
                ne_cc = [ne_cc for ne_cc in ne_ccs if ne_node in ne_cc][0]
            except:
                raise
            largest_cc = [xx for xx in ne_cc if abs(xx[0] - node[0]) + abs(xx[1] - node[1]) == 1]
            mesh.remove_edges_from([(xx, node) for xx in mesh.neighbors(node)])
            re_depth = {'value': 0, 'count': 0}
            for cc_node in largest_cc:
                re_depth['value'] += cc_node[2]
                re_depth['count'] += 1.
                mesh.add_edge(cc_node, node)
            try:
                re_depth = re_depth['value'] / re_depth['count']
            except:
                re_depth = node[2]
            renode = (node[0], node[1], re_depth)
            mapping_dict = {node: renode}
            info_on_pix, mesh, edge_mesh = update_info(mapping_dict, info_on_pix, mesh, edge_mesh)
            depth[node[0], node[1]] = abs(re_depth)
            mark[node[0], node[1]] = 0
            edge_mesh, mesh, mark, info_on_pix = recursive_add_edge(edge_mesh, mesh, info_on_pix, renode, mark)
            break
        if len(cc) == 1:
            node = [node for node in cc][0]
            hx, hy = node[0], node[1]
            nine_nes = set([(x, y, info_on_pix[(x, y)][0]['depth']) for x, y in
                            [(hx, hy), (hx + 1, hy), (hx - 1, hy), (hx, hy + 1), (hx, hy - 1),
                             (hx + 1, hy + 1), (hx - 1, hy - 1), (hx - 1, hy + 1), (hx + 1, hy - 1)] \
                            if info_on_pix.get((x, y)) is not None and mesh.has_node(
                    (x, y, info_on_pix[(x, y)][0]['depth']))])
            ne_sub_mesh = mesh.subgraph(nine_nes).copy()
            ne_ccs = netx.connected_components(ne_sub_mesh)
            for ne_cc in ne_ccs:
                if node in ne_cc:
                    re_depth = {'value': 0, 'count': 0}
                    for ne in ne_cc:
                        if abs(ne[0] - node[0]) + abs(ne[1] - node[1]) == 1:
                            mesh.add_edge(node, ne)
                            re_depth['value'] += ne[2]
                            re_depth['count'] += 1.
                    re_depth = re_depth['value'] / re_depth['count']
                    mapping_dict = {node: (node[0], node[1], re_depth)}
                    info_on_pix, mesh, edge_mesh = update_info(mapping_dict, info_on_pix, mesh, edge_mesh)
                    depth[node[0], node[1]] = abs(re_depth)
                    mark[node[0], node[1]] = 0

    return mesh, info_on_pix, edge_mesh, depth, mark


def context_and_holes(
        mesh, edge_ccs, config, specific_edge_id, specific_edge_loc, depth_feat_model,
        connect_points_ccs=None, inpaint_iter=0, filter_edge=False, vis_edge_id=None):
    edge_maps = np.zeros((mesh.graph['H'], mesh.graph['W'])) - 1
    for edge_id, edge_cc in enumerate(edge_ccs):
        for edge_node in edge_cc:
            edge_maps[edge_node[0], edge_node[1]] = edge_id

    context_ccs = [set() for x in range(len(edge_ccs))]
    extend_context_ccs = [set() for x in range(len(edge_ccs))]
    extend_erode_context_ccs = [set() for x in range(len(edge_ccs))]
    extend_edge_ccs = [set() for x in range(len(edge_ccs))]
    accomp_extend_context_ccs = [set() for x in range(len(edge_ccs))]
    erode_context_ccs = [set() for x in range(len(edge_ccs))]
    broken_mask_ccs = [set() for x in range(len(edge_ccs))]
    invalid_extend_edge_ccs = [set() for x in range(len(edge_ccs))]
    intouched_ccs = [set() for x in range(len(edge_ccs))]
    if inpaint_iter == 0:
        background_thickness = config['background_thickness']
        context_thickness = config['context_thickness']
    else:
        background_thickness = config['background_thickness_2']
        context_thickness = config['context_thickness_2']

    mesh_nodes = mesh.nodes
    for edge_id, edge_cc in enumerate(edge_ccs):
        if context_thickness == 0 or (len(specific_edge_id) > 0 and edge_id not in specific_edge_id):
            continue
        edge_group = {}
        for edge_node in edge_cc:
            far_nodes = mesh_nodes[edge_node].get('far')
            if far_nodes is None:
                continue
            for far_node in far_nodes:
                if far_node in edge_cc:
                    continue
                context_ccs[edge_id].add(far_node)
                if mesh_nodes[far_node].get('edge_id') is not None:
                    if edge_group.get(mesh_nodes[far_node]['edge_id']) is None:
                        edge_group[mesh_nodes[far_node]['edge_id']] = set()
                    edge_group[mesh_nodes[far_node]['edge_id']].add(far_node)
        if len(edge_cc) > 2:
            for edge_key in [*edge_group.keys()]:
                if len(edge_group[edge_key]) == 1:
                    context_ccs[edge_id].remove([*edge_group[edge_key]][0])
    for edge_id, edge_cc in enumerate(edge_ccs):
        if inpaint_iter != 0:
            continue
        tmp_intouched_nodes = set()
        for edge_node in edge_cc:
            raw_intouched_nodes = set(mesh_nodes[edge_node].get('near')) if mesh_nodes[edge_node].get(
                'near') is not None else set()
            tmp_intouched_nodes |= set(
                [xx for xx in raw_intouched_nodes if mesh_nodes[xx].get('edge_id') is not None and \
                 len(context_ccs[mesh_nodes[xx].get('edge_id')]) > 0])
        intouched_ccs[edge_id] |= tmp_intouched_nodes
        tmp_intouched_nodes = None
    mask_ccs = copy.deepcopy(edge_ccs)
    forbidden_len = 3
    forbidden_map = np.ones((mesh.graph['H'] - forbidden_len, mesh.graph['W'] - forbidden_len))
    forbidden_map = np.pad(forbidden_map, ((forbidden_len, forbidden_len), (forbidden_len, forbidden_len)),
                           mode='constant').astype(bool)
    cur_tmp_mask_map = np.zeros_like(forbidden_map).astype(bool)
    passive_background = 10 if 10 is not None else background_thickness
    passive_context = 1 if 1 is not None else context_thickness

    for edge_id, edge_cc in enumerate(edge_ccs):
        cur_mask_cc = []
        cur_context_cc = []
        cur_accomp_near_cc = []
        cur_invalid_extend_edge_cc = []
        cur_comp_far_cc = []
        tmp_erode = []
        if len(context_ccs[edge_id]) == 0 or (len(specific_edge_id) > 0 and edge_id not in specific_edge_id):
            continue
        for i in range(max(background_thickness, context_thickness)):
            cur_tmp_mask_map.fill(False)
            if i == 0:
                tmp_mask_nodes = copy.deepcopy(mask_ccs[edge_id])
                tmp_intersect_nodes = []
                tmp_intersect_context_nodes = []
                mask_map = np.zeros((mesh.graph['H'], mesh.graph['W']), dtype=bool)
                context_depth = np.zeros((mesh.graph['H'], mesh.graph['W']))
                comp_cnt_depth = np.zeros((mesh.graph['H'], mesh.graph['W']))
                connect_map = np.zeros((mesh.graph['H'], mesh.graph['W']))
                for node in tmp_mask_nodes:
                    mask_map[node[0], node[1]] = True
                    depth_count = 0
                    if mesh_nodes[node].get('far') is not None:
                        for comp_cnt_node in mesh_nodes[node]['far']:
                            comp_cnt_depth[node[0], node[1]] += abs(comp_cnt_node[2])
                            depth_count += 1
                    if depth_count > 0:
                        comp_cnt_depth[node[0], node[1]] = comp_cnt_depth[node[0], node[1]] / depth_count
                    connect_node = []
                    if mesh_nodes[node].get('connect_point_id') is not None:
                        connect_node.append(mesh_nodes[node]['connect_point_id'])
                    connect_point_id = np.bincount(connect_node).argmax() if len(connect_node) > 0 else -1
                    if connect_point_id > -1 and connect_points_ccs is not None:
                        for xx in connect_points_ccs[connect_point_id]:
                            if connect_map[xx[0], xx[1]] == 0:
                                connect_map[xx[0], xx[1]] = xx[2]
                    if mesh_nodes[node].get('connect_point_exception') is not None:
                        for xx in mesh_nodes[node]['connect_point_exception']:
                            if connect_map[xx[0], xx[1]] == 0:
                                connect_map[xx[0], xx[1]] = xx[2]
                tmp_context_nodes = [*context_ccs[edge_id]]
                tmp_erode.append([*context_ccs[edge_id]])
                context_map = np.zeros((mesh.graph['H'], mesh.graph['W']), dtype=bool)
                for node in tmp_context_nodes:
                    context_map[node[0], node[1]] = True
                    context_depth[node[0], node[1]] = node[2]
                context_map[mask_map == True] = False
                tmp_intouched_nodes = [*intouched_ccs[edge_id]]
                intouched_map = np.zeros((mesh.graph['H'], mesh.graph['W']), dtype=bool)
                for node in tmp_intouched_nodes: intouched_map[node[0], node[1]] = True
                intouched_map[mask_map == True] = False
                tmp_redundant_nodes = set()
                tmp_noncont_nodes = set()
                noncont_map = np.zeros((mesh.graph['H'], mesh.graph['W']), dtype=bool)
                intersect_map = np.zeros((mesh.graph['H'], mesh.graph['W']), dtype=bool)
                intersect_context_map = np.zeros((mesh.graph['H'], mesh.graph['W']), dtype=bool)
            if i > passive_background and inpaint_iter == 0:
                new_tmp_intersect_nodes = None
                new_tmp_intersect_nodes = []
                for node in tmp_intersect_nodes:
                    nes = mesh.neighbors(node)
                    for ne in nes:
                        if bool(context_map[ne[0], ne[1]]) is False and \
                                bool(mask_map[ne[0], ne[1]]) is False and \
                                bool(forbidden_map[ne[0], ne[1]]) is True and \
                                bool(intouched_map[ne[0], ne[1]]) is False and \
                                bool(intersect_map[ne[0], ne[1]]) is False and \
                                bool(intersect_context_map[ne[0], ne[1]]) is False:
                            break_flag = False
                            if (i - passive_background) % 2 == 0 and (i - passive_background) % 8 != 0:
                                four_nes = [xx for xx in [[ne[0] - 1, ne[1]], [ne[0] + 1, ne[1]], [ne[0], ne[1] - 1],
                                                          [ne[0], ne[1] + 1]] \
                                            if 0 <= xx[0] < mesh.graph['H'] and 0 <= xx[1] < mesh.graph['W']]
                                for fne in four_nes:
                                    if bool(mask_map[fne[0], fne[1]]) is True:
                                        break_flag = True
                                        break
                                if break_flag is True:
                                    continue
                            intersect_map[ne[0], ne[1]] = True
                            new_tmp_intersect_nodes.append(ne)
                tmp_intersect_nodes = None
                tmp_intersect_nodes = new_tmp_intersect_nodes

            if i > passive_context and inpaint_iter == 1:
                new_tmp_intersect_context_nodes = None
                new_tmp_intersect_context_nodes = []
                for node in tmp_intersect_context_nodes:
                    nes = mesh.neighbors(node)
                    for ne in nes:
                        if bool(context_map[ne[0], ne[1]]) is False and \
                                bool(mask_map[ne[0], ne[1]]) is False and \
                                bool(forbidden_map[ne[0], ne[1]]) is True and \
                                bool(intouched_map[ne[0], ne[1]]) is False and \
                                bool(intersect_map[ne[0], ne[1]]) is False and \
                                bool(intersect_context_map[ne[0], ne[1]]) is False:
                            intersect_context_map[ne[0], ne[1]] = True
                            new_tmp_intersect_context_nodes.append(ne)
                tmp_intersect_context_nodes = None
                tmp_intersect_context_nodes = new_tmp_intersect_context_nodes

            new_tmp_mask_nodes = None
            new_tmp_mask_nodes = []
            for node in tmp_mask_nodes:
                four_nes = {xx: [] for xx in [(node[0] - 1, node[1]), (node[0] + 1, node[1]), (node[0], node[1] - 1),
                                              (node[0], node[1] + 1)] if \
                            0 <= xx[0] < connect_map.shape[0] and 0 <= xx[1] < connect_map.shape[1]}
                if inpaint_iter > 0:
                    for ne in four_nes.keys():
                        if connect_map[ne[0], ne[1]] == True:
                            tmp_context_nodes.append((ne[0], ne[1], connect_map[ne[0], ne[1]]))
                            context_map[ne[0], ne[1]] = True
                nes = mesh.neighbors(node)
                if inpaint_iter > 0:
                    for ne in nes: four_nes[(ne[0], ne[1])].append(ne[2])
                    nes = []
                    for kfne, vfnes in four_nes.items(): vfnes.sort(key=lambda xx: abs(xx), reverse=True)
                    for kfne, vfnes in four_nes.items():
                        for vfne in vfnes: nes.append((kfne[0], kfne[1], vfne))
                for ne in nes:
                    if bool(context_map[ne[0], ne[1]]) is False and \
                            bool(mask_map[ne[0], ne[1]]) is False and \
                            bool(forbidden_map[ne[0], ne[1]]) is True and \
                            bool(intouched_map[ne[0], ne[1]]) is False and \
                            bool(intersect_map[ne[0], ne[1]]) is False and \
                            bool(intersect_context_map[ne[0], ne[1]]) is False:
                        if i == passive_background and inpaint_iter == 0:
                            if np.any(context_map[max(ne[0] - 1, 0):min(ne[0] + 2, mesh.graph['H']),
                                      max(ne[1] - 1, 0):min(ne[1] + 2, mesh.graph['W'])]) == True:
                                intersect_map[ne[0], ne[1]] = True
                                tmp_intersect_nodes.append(ne)
                                continue
                        if i < background_thickness:
                            if inpaint_iter == 0:
                                cur_mask_cc.append(ne)
                            elif mesh_nodes[ne].get('inpaint_id') == 1:
                                cur_mask_cc.append(ne)
                            else:
                                continue
                            mask_ccs[edge_id].add(ne)
                            if inpaint_iter == 0:
                                if comp_cnt_depth[node[0], node[1]] > 0 and comp_cnt_depth[ne[0], ne[1]] == 0:
                                    comp_cnt_depth[ne[0], ne[1]] = comp_cnt_depth[node[0], node[1]]
                                if mesh_nodes[ne].get('far') is not None:
                                    for comp_far_node in mesh_nodes[ne]['far']:
                                        cur_comp_far_cc.append(comp_far_node)
                                        cur_accomp_near_cc.append(ne)
                                        cur_invalid_extend_edge_cc.append(comp_far_node)
                                if mesh_nodes[ne].get('edge_id') is not None and \
                                        len(context_ccs[mesh_nodes[ne].get('edge_id')]) > 0:
                                    intouched_fars = set(mesh_nodes[ne].get('far')) if mesh_nodes[ne].get(
                                        'far') is not None else set()
                                    accum_intouched_fars = set(intouched_fars)
                                    for intouched_far in intouched_fars:
                                        accum_intouched_fars |= set([*mesh.neighbors(intouched_far)])
                                    for intouched_far in accum_intouched_fars:
                                        if bool(mask_map[intouched_far[0], intouched_far[1]]) is True or \
                                                bool(context_map[intouched_far[0], intouched_far[1]]) is True:
                                            continue
                                        tmp_redundant_nodes.add(intouched_far)
                                        intouched_map[intouched_far[0], intouched_far[1]] = True
                                if mesh_nodes[ne].get('near') is not None:
                                    intouched_nears = set(mesh_nodes[ne].get('near'))
                                    for intouched_near in intouched_nears:
                                        if bool(mask_map[intouched_near[0], intouched_near[1]]) is True or \
                                                bool(context_map[intouched_near[0], intouched_near[1]]) is True:
                                            continue
                                        tmp_redundant_nodes.add(intouched_near)
                                        intouched_map[intouched_near[0], intouched_near[1]] = True
                        if not (mesh_nodes[ne].get('inpaint_id') != 1 and inpaint_iter == 1):
                            new_tmp_mask_nodes.append(ne)
                            mask_map[ne[0], ne[1]] = True
            tmp_mask_nodes = new_tmp_mask_nodes

            new_tmp_context_nodes = None
            new_tmp_context_nodes = []
            for node in tmp_context_nodes:
                nes = mesh.neighbors(node)
                if inpaint_iter > 0:
                    four_nes = {(node[0] - 1, node[1]): [], (node[0] + 1, node[1]): [], (node[0], node[1] - 1): [],
                                (node[0], node[1] + 1): []}
                    for ne in nes: four_nes[(ne[0], ne[1])].append(ne[2])
                    nes = []
                    for kfne, vfnes in four_nes.items(): vfnes.sort(key=lambda xx: abs(xx), reverse=True)
                    for kfne, vfnes in four_nes.items():
                        for vfne in vfnes: nes.append((kfne[0], kfne[1], vfne))
                for ne in nes:
                    mask_flag = (bool(mask_map[ne[0], ne[1]]) is False)
                    if bool(context_map[ne[0], ne[1]]) is False and mask_flag and \
                            bool(forbidden_map[ne[0], ne[1]]) is True and bool(noncont_map[ne[0], ne[1]]) is False and \
                            bool(intersect_context_map[ne[0], ne[1]]) is False:
                        if i == passive_context and inpaint_iter == 1:
                            mnes = mesh.neighbors(ne)
                            if any([mask_map[mne[0], mne[1]] == True for mne in mnes]) is True:
                                intersect_context_map[ne[0], ne[1]] = True
                                tmp_intersect_context_nodes.append(ne)
                                continue
                        if False and mesh_nodes[ne].get('near') is not None and mesh_nodes[ne].get(
                                'edge_id') != edge_id:
                            noncont_nears = set(mesh_nodes[ne].get('near'))
                            for noncont_near in noncont_nears:
                                if bool(context_map[noncont_near[0], noncont_near[1]]) is False:
                                    tmp_noncont_nodes.add(noncont_near)
                                    noncont_map[noncont_near[0], noncont_near[1]] = True
                        new_tmp_context_nodes.append(ne)
                        context_map[ne[0], ne[1]] = True
                        context_depth[ne[0], ne[1]] = ne[2]
            cur_context_cc.extend(new_tmp_context_nodes)
            tmp_erode.append(new_tmp_context_nodes)
            tmp_context_nodes = None
            tmp_context_nodes = new_tmp_context_nodes
            new_tmp_intouched_nodes = None;
            new_tmp_intouched_nodes = []

            for node in tmp_intouched_nodes:
                if bool(context_map[node[0], node[1]]) is True or bool(mask_map[node[0], node[1]]) is True:
                    continue
                nes = mesh.neighbors(node)

                for ne in nes:
                    if bool(context_map[ne[0], ne[1]]) is False and \
                            bool(mask_map[ne[0], ne[1]]) is False and \
                            bool(intouched_map[ne[0], ne[1]]) is False and \
                            bool(forbidden_map[ne[0], ne[1]]) is True:
                        new_tmp_intouched_nodes.append(ne)
                        intouched_map[ne[0], ne[1]] = True
            tmp_intouched_nodes = None
            tmp_intouched_nodes = set(new_tmp_intouched_nodes)
            new_tmp_redundant_nodes = None;
            new_tmp_redundant_nodes = []
            for node in tmp_redundant_nodes:
                if bool(context_map[node[0], node[1]]) is True or \
                        bool(mask_map[node[0], node[1]]) is True:
                    continue
                nes = mesh.neighbors(node)

                for ne in nes:
                    if bool(context_map[ne[0], ne[1]]) is False and \
                            bool(mask_map[ne[0], ne[1]]) is False and \
                            bool(intouched_map[ne[0], ne[1]]) is False and \
                            bool(forbidden_map[ne[0], ne[1]]) is True:
                        new_tmp_redundant_nodes.append(ne)
                        intouched_map[ne[0], ne[1]] = True
            tmp_redundant_nodes = None
            tmp_redundant_nodes = set(new_tmp_redundant_nodes)
            new_tmp_noncont_nodes = None;
            new_tmp_noncont_nodes = []
            for node in tmp_noncont_nodes:
                if bool(context_map[node[0], node[1]]) is True or \
                        bool(mask_map[node[0], node[1]]) is True:
                    continue
                nes = mesh.neighbors(node)
                rmv_flag = False
                for ne in nes:
                    if bool(context_map[ne[0], ne[1]]) is False and \
                            bool(mask_map[ne[0], ne[1]]) is False and \
                            bool(noncont_map[ne[0], ne[1]]) is False and \
                            bool(forbidden_map[ne[0], ne[1]]) is True:
                        patch_context_map = context_map[max(ne[0] - 1, 0):min(ne[0] + 2, context_map.shape[0]),
                                            max(ne[1] - 1, 0):min(ne[1] + 2, context_map.shape[1])]
                        if bool(np.any(patch_context_map)) is True:
                            new_tmp_noncont_nodes.append(ne)
                            noncont_map[ne[0], ne[1]] = True
            tmp_noncont_nodes = set(new_tmp_noncont_nodes)
        if inpaint_iter == 0:
            depth_dict = get_depth_from_maps(
                context_map, mask_map, context_depth, mesh.graph['H'], mesh.graph['W'],
                log_depth=config['log_depth'])
            mask_size = get_valid_size(depth_dict['mask'])
            mask_size = dilate_valid_size(mask_size, depth_dict['mask'], dilate=[20, 20])
            context_size = get_valid_size(depth_dict['context'])
            context_size = dilate_valid_size(context_size, depth_dict['context'], dilate=[20, 20])
            union_size = size_operation(mask_size, context_size, operation='+')
            depth_dict = depth_inpainting(
                None, None, None, None, mesh, config, union_size, depth_feat_model, None,
                given_depth_dict=depth_dict, spdb=False)
            near_depth_map, raw_near_depth_map = np.zeros((mesh.graph['H'], mesh.graph['W'])), np.zeros(
                (mesh.graph['H'], mesh.graph['W']))
            filtered_comp_far_cc, filtered_accomp_near_cc = set(), set()
            for node in cur_accomp_near_cc:
                near_depth_map[node[0], node[1]] = depth_dict['output'][node[0], node[1]]
                raw_near_depth_map[node[0], node[1]] = node[2]
            for node in cur_comp_far_cc:
                four_nes = [xx for xx in [(node[0] - 1, node[1]), (node[0] + 1, node[1]), (node[0], node[1] - 1),
                                          (node[0], node[1] + 1)] \
                            if 0 <= xx[0] < mesh.graph['H'] and 0 <= xx[1] < mesh.graph['W'] and \
                            near_depth_map[xx[0], xx[1]] != 0 and \
                            abs(near_depth_map[xx[0], xx[1]]) < abs(node[2])]
                if len(four_nes) > 0:
                    filtered_comp_far_cc.add(node)
                for ne in four_nes:
                    filtered_accomp_near_cc.add((ne[0], ne[1], -abs(raw_near_depth_map[ne[0], ne[1]])))
            cur_comp_far_cc, cur_accomp_near_cc = filtered_comp_far_cc, filtered_accomp_near_cc
        mask_ccs[edge_id] |= set(cur_mask_cc)
        context_ccs[edge_id] |= set(cur_context_cc)
        accomp_extend_context_ccs[edge_id] |= set(cur_accomp_near_cc).intersection(cur_mask_cc)
        extend_edge_ccs[edge_id] |= set(cur_accomp_near_cc).intersection(cur_mask_cc)
        extend_context_ccs[edge_id] |= set(cur_comp_far_cc)
        invalid_extend_edge_ccs[edge_id] |= set(cur_invalid_extend_edge_cc)
        erode_size = [0]
        for tmp in tmp_erode:
            erode_size.append(len(tmp))
            if len(erode_size) > 1:
                erode_size[-1] += erode_size[-2]
        if inpaint_iter == 0:
            tmp_width = config['depth_edge_dilate']
        else:
            tmp_width = 0
        while float(erode_size[tmp_width]) / (erode_size[-1] + 1e-6) > 0.3:
            tmp_width = tmp_width - 1
        try:
            if tmp_width == 0:
                erode_context_ccs[edge_id] = set([])
            else:
                erode_context_ccs[edge_id] = set(
                    functools.reduce(lambda x, y: x + y, [] + tmp_erode[:tmp_width])
                )
        except:
            raise
        erode_context_cc = copy.deepcopy(erode_context_ccs[edge_id])
        for erode_context_node in erode_context_cc:
            if (inpaint_iter != 0 and (mesh_nodes[erode_context_node].get('inpaint_id') is None or
                                       mesh_nodes[erode_context_node].get('inpaint_id') == 0)):
                erode_context_ccs[edge_id].remove(erode_context_node)
            else:
                context_ccs[edge_id].remove(erode_context_node)
        context_map = np.zeros((mesh.graph['H'], mesh.graph['W']))
        for context_node in context_ccs[edge_id]:
            context_map[context_node[0], context_node[1]] = 1
        extend_context_ccs[edge_id] = extend_context_ccs[edge_id] - mask_ccs[edge_id] - accomp_extend_context_ccs[
            edge_id]
    if inpaint_iter == 0:
        all_ecnt_cc = set()
        for ecnt_id, ecnt_cc in enumerate(extend_context_ccs):
            constraint_context_ids = set()
            constraint_context_cc = set()
            constraint_erode_context_cc = set()
            tmp_mask_cc = set()
            accum_context_cc = None;
            accum_context_cc = []
            for ecnt_node in accomp_extend_context_ccs[ecnt_id]:
                if edge_maps[ecnt_node[0], ecnt_node[1]] > -1:
                    constraint_context_ids.add(int(round(edge_maps[ecnt_node[0], ecnt_node[1]])))
            constraint_erode_context_cc = erode_context_ccs[ecnt_id]
            for constraint_context_id in constraint_context_ids:
                constraint_context_cc = constraint_context_cc | context_ccs[constraint_context_id] | erode_context_ccs[
                    constraint_context_id]
                constraint_erode_context_cc = constraint_erode_context_cc | erode_context_ccs[constraint_context_id]
            for i in range(background_thickness):
                if i == 0:
                    tmp_context_nodes = copy.deepcopy(ecnt_cc)
                    tmp_invalid_context_nodes = copy.deepcopy(invalid_extend_edge_ccs[ecnt_id])
                    tmp_mask_nodes = copy.deepcopy(accomp_extend_context_ccs[ecnt_id])
                    tmp_context_map = np.zeros((mesh.graph['H'], mesh.graph['W'])).astype(bool)
                    tmp_mask_map = np.zeros((mesh.graph['H'], mesh.graph['W'])).astype(bool)
                    tmp_invalid_context_map = np.zeros((mesh.graph['H'], mesh.graph['W'])).astype(bool)
                    for node in tmp_mask_nodes:
                        tmp_mask_map[node[0], node[1]] = True
                    for node in context_ccs[ecnt_id]:
                        tmp_context_map[node[0], node[1]] = True
                    for node in erode_context_ccs[ecnt_id]:
                        tmp_context_map[node[0], node[1]] = True
                    for node in extend_context_ccs[ecnt_id]:
                        tmp_context_map[node[0], node[1]] = True
                    for node in invalid_extend_edge_ccs[ecnt_id]:
                        tmp_invalid_context_map[node[0], node[1]] = True
                    init_invalid_context_map = tmp_invalid_context_map.copy()
                    if vis_edge_id is not None and ecnt_id == vis_edge_id:
                        f, ((ax1, ax2)) = plt.subplots(1, 2, sharex=True, sharey=True)
                        ax1.imshow(tmp_context_map * 1);
                        ax2.imshow(init_invalid_context_map * 1 + tmp_context_map * 2)
                        plt.show()
                else:
                    tmp_context_nodes = new_tmp_context_nodes
                    new_tmp_context_nodes = None
                    tmp_mask_nodes = new_tmp_mask_nodes
                    new_tmp_mask_nodes = None
                    tmp_invalid_context_nodes = new_tmp_invalid_context_nodes
                    new_tmp_invalid_context_nodes = None
                new_tmp_context_nodes = None
                new_tmp_context_nodes = []
                new_tmp_invalid_context_nodes = None
                new_tmp_invalid_context_nodes = []
                new_tmp_mask_nodes = set([])
                for node in tmp_context_nodes:
                    for ne in mesh.neighbors(node):
                        if ne in constraint_context_cc and \
                                bool(tmp_mask_map[ne[0], ne[1]]) is False and \
                                bool(tmp_context_map[ne[0], ne[1]]) is False and \
                                bool(forbidden_map[ne[0], ne[1]]) is True:
                            new_tmp_context_nodes.append(ne)
                            tmp_context_map[ne[0], ne[1]] = True
                accum_context_cc.extend(new_tmp_context_nodes)
                for node in tmp_invalid_context_nodes:
                    for ne in mesh.neighbors(node):
                        if bool(tmp_mask_map[ne[0], ne[1]]) is False and \
                                bool(tmp_context_map[ne[0], ne[1]]) is False and \
                                bool(tmp_invalid_context_map[ne[0], ne[1]]) is False and \
                                bool(forbidden_map[ne[0], ne[1]]) is True:
                            tmp_invalid_context_map[ne[0], ne[1]] = True
                            new_tmp_invalid_context_nodes.append(ne)
                for node in tmp_mask_nodes:
                    for ne in mesh.neighbors(node):
                        if bool(tmp_mask_map[ne[0], ne[1]]) is False and \
                                bool(tmp_context_map[ne[0], ne[1]]) is False and \
                                bool(tmp_invalid_context_map[ne[0], ne[1]]) is False and \
                                bool(forbidden_map[ne[0], ne[1]]) is True:
                            new_tmp_mask_nodes.add(ne)
                            tmp_mask_map[ne[0], ne[1]] = True
            init_invalid_context_map[tmp_context_map] = False
            _, tmp_label_map = cv2.connectedComponents(
                (init_invalid_context_map | tmp_context_map).astype(np.uint8),
                connectivity=8)
            if vis_edge_id is not None and ecnt_id == vis_edge_id:
                f, ((ax1, ax2)) = plt.subplots(1, 2, sharex=True, sharey=True)
                ax1.imshow(tmp_label_map);
                ax2.imshow(init_invalid_context_map * 1 + tmp_context_map * 2)
                plt.show()
            extend_context_ccs[ecnt_id] |= set(accum_context_cc)
            extend_context_ccs[ecnt_id] = extend_context_ccs[ecnt_id] - mask_ccs[ecnt_id]
            extend_erode_context_ccs[ecnt_id] = extend_context_ccs[ecnt_id] & constraint_erode_context_cc
            extend_context_ccs[ecnt_id] = extend_context_ccs[ecnt_id] - extend_erode_context_ccs[ecnt_id] - \
                                          erode_context_ccs[ecnt_id]
            tmp_context_cc = context_ccs[ecnt_id] - extend_erode_context_ccs[ecnt_id] - erode_context_ccs[ecnt_id]
            if len(tmp_context_cc) > 0:
                context_ccs[ecnt_id] = tmp_context_cc
            tmp_mask_cc = tmp_mask_cc - context_ccs[ecnt_id] - erode_context_ccs[ecnt_id]
            mask_ccs[ecnt_id] = mask_ccs[ecnt_id] | tmp_mask_cc

    ret = context_ccs, mask_ccs, broken_mask_ccs, edge_ccs, \
          erode_context_ccs, invalid_extend_edge_ccs, edge_maps, \
          extend_context_ccs, extend_edge_ccs, extend_erode_context_ccs
    return ret


def DL_inpaint_edge(
        mesh,
        info_on_pix,
        config,
        image,
        depth,
        context_ccs,
        erode_context_ccs,
        extend_context_ccs,
        extend_erode_context_ccs,
        mask_ccs,
        broken_mask_ccs,
        edge_ccs,
        extend_edge_ccs,
        init_mask_connect,
        edge_maps,
        rgb_model=None,
        depth_edge_model=None,
        depth_edge_model_init=None,
        depth_feat_model=None,
        specific_edge_id=-1,
        specific_edge_loc=None,
        inpaint_iter=0):
    edge_map = np.zeros_like(depth)
    new_edge_ccs = [set() for _ in range(len(edge_ccs))]
    edge_maps_with_id = edge_maps
    edge_condition = lambda x, m: m.nodes[x].get('far') is not None and len(m.nodes[x].get('far')) > 0
    edge_map = get_map_from_ccs(edge_ccs, mesh.graph['H'], mesh.graph['W'], mesh, edge_condition)
    np_depth, np_image = depth.copy(), image.copy()
    image_c = image.shape[-1]
    image = np.expand_dims(image.transpose(2, 0, 1), axis=0)
    if depth.ndim < 3:
        depth = depth[..., None]
    depth = np.expand_dims(depth.transpose(2, 0, 1), axis=0)
    mesh.graph['max_edge_id'] = len(edge_ccs)
    connnect_points_ccs = [set() for _ in range(len(edge_ccs))]
    gp_time, tmp_mesh_time, bilateral_time = 0, 0, 0
    edges_infos = dict()
    edges_in_mask = [set() for _ in range(len(edge_ccs))]
    tmp_specific_edge_id = []
    for edge_id, (context_cc, mask_cc, erode_context_cc, extend_context_cc, edge_cc) in enumerate(
            zip(context_ccs, mask_ccs, erode_context_ccs, extend_context_ccs, edge_ccs)):
        if len(specific_edge_id) > 0:
            if edge_id not in specific_edge_id:
                continue
        if len(context_cc) < 1 or len(mask_cc) < 1:
            continue
        edge_dict = get_edge_from_nodes(
            context_cc | extend_context_cc,
            erode_context_cc | extend_erode_context_ccs[edge_id], mask_cc, edge_cc,
            extend_edge_ccs[edge_id],
            mesh.graph['H'], mesh.graph['W'], mesh)
        edge_dict['edge'], end_depth_maps, _ = \
            filter_irrelevant_edge_new(
                edge_dict['self_edge'], edge_dict['comp_edge'],
                edge_map,
                edge_maps_with_id,
                edge_id,
                edge_dict['context'],
                edge_dict['depth'], mesh,
                context_cc | erode_context_cc | \
                extend_context_cc | extend_erode_context_ccs[edge_id],
                spdb=False)
        if specific_edge_loc is not None and \
                (specific_edge_loc is not None and edge_dict['mask'][specific_edge_loc[0], specific_edge_loc[1]] == 0):
            continue
        mask_size = get_valid_size(edge_dict['mask'])
        mask_size = dilate_valid_size(mask_size, edge_dict['mask'], dilate=[20, 20])
        context_size = get_valid_size(edge_dict['context'])
        context_size = dilate_valid_size(context_size, edge_dict['context'], dilate=[20, 20])
        union_size = size_operation(mask_size, context_size, operation='+')
        patch_edge_dict = dict()
        patch_edge_dict['mask'], patch_edge_dict['context'], patch_edge_dict['rgb'], \
        patch_edge_dict['disp'], patch_edge_dict['edge'] = \
            crop_maps_by_size(union_size, edge_dict['mask'], edge_dict['context'],
                              edge_dict['rgb'], edge_dict['disp'], edge_dict['edge'])
        x_anchor, y_anchor = [union_size['x_min'], union_size['x_max']], [union_size['y_min'], union_size['y_max']]
        tensor_edge_dict = convert2tensor(patch_edge_dict)
        input_edge_feat = np.concatenate(
            (tensor_edge_dict['rgb'],
             tensor_edge_dict['disp'],
             tensor_edge_dict['edge'],
             1 - tensor_edge_dict['context'],
             tensor_edge_dict['mask']), axis=1)
        if require_depth_edge(patch_edge_dict['edge'], patch_edge_dict['mask']) and inpaint_iter == 0:
            depth_edge_output = edge_forward_3P(
                depth_edge_model,
                tensor_edge_dict['mask'], tensor_edge_dict['context'],
                tensor_edge_dict['rgb'], tensor_edge_dict['disp'],
                tensor_edge_dict['edge'])

            tensor_edge_dict['output'] = \
                (depth_edge_output > config['ext_edge_threshold']).astype(float) \
                * tensor_edge_dict['mask'] + tensor_edge_dict['edge']
        else:
            tensor_edge_dict['output'] = tensor_edge_dict['edge']
            depth_edge_output = tensor_edge_dict['edge'] + 0
        patch_edge_dict['output'] = tensor_edge_dict['output'].squeeze()
        edge_dict['output'] = np.zeros((mesh.graph['H'], mesh.graph['W']))
        edge_dict['output'][union_size['x_min']:union_size['x_max'], union_size['y_min']:union_size['y_max']] = \
            patch_edge_dict['output']
        if require_depth_edge(patch_edge_dict['edge'], patch_edge_dict['mask']) and inpaint_iter == 0:
            if ((depth_edge_output > config['ext_edge_threshold']).astype(float) * tensor_edge_dict[
                'mask']).max() > 0:
                try:
                    edge_dict['fpath_map'], edge_dict['npath_map'], break_flag, npaths, fpaths, invalid_edge_id = \
                        clean_far_edge_new(edge_dict['output'], end_depth_maps, edge_dict['mask'], edge_dict['context'],
                                           mesh, info_on_pix, edge_dict['self_edge'], inpaint_iter, config)
                except:
                    raise
                pre_npath_map = edge_dict['npath_map'].copy()
                if config.get('repeat_inpaint_edge') is True:
                    for _ in range(2):
                        tmp_input_edge = ((edge_dict['npath_map'] > -1) + edge_dict['edge']).clip(0, 1)
                        patch_tmp_input_edge = crop_maps_by_size(union_size, tmp_input_edge)[0]
                        tensor_input_edge = patch_tmp_input_edge[None, None, ...]

                        depth_edge_output = edge_forward_3P(
                            depth_edge_model,
                            tensor_edge_dict['mask'], tensor_edge_dict['context'],
                            tensor_edge_dict['rgb'], tensor_edge_dict['disp'],
                            tensor_input_edge)

                        depth_edge_output = \
                            (depth_edge_output > config['ext_edge_threshold']).astype(float) * \
                            tensor_edge_dict['mask'] + tensor_edge_dict['edge']
                        depth_edge_output = depth_edge_output.squeeze()
                        full_depth_edge_output = np.zeros((mesh.graph['H'], mesh.graph['W']))
                        full_depth_edge_output[union_size['x_min']:union_size['x_max'],
                        union_size['y_min']:union_size['y_max']] = \
                            depth_edge_output
                        edge_dict['fpath_map'], edge_dict['npath_map'], break_flag, npaths, fpaths, invalid_edge_id = \
                            clean_far_edge_new(full_depth_edge_output, end_depth_maps, edge_dict['mask'],
                                               edge_dict['context'], mesh, info_on_pix, edge_dict['self_edge'],
                                               inpaint_iter, config)
                for nid in npaths.keys():
                    npath, fpath = npaths[nid], fpaths[nid]
                    start_mx, start_my, end_mx, end_my = -1, -1, -1, -1
                    if end_depth_maps[npath[0][0], npath[0][1]] != 0:
                        start_mx, start_my = npath[0][0], npath[0][1]
                    if end_depth_maps[npath[-1][0], npath[-1][1]] != 0:
                        end_mx, end_my = npath[-1][0], npath[-1][1]
                    valid_end_pt = () if end_mx == -1 else (end_mx, end_my, info_on_pix[(end_mx, end_my)][0]['depth'])
                    new_edge_info = dict(fpath=fpath,
                                         npath=npath,
                                         cont_end_pts=valid_end_pt,
                                         mask_id=edge_id,
                                         comp_edge_id=nid,
                                         depth=end_depth_maps[start_mx, start_my])
                    if edges_infos.get((start_mx, start_my)) is None:
                        edges_infos[(start_mx, start_my)] = []
                    edges_infos[(start_mx, start_my)].append(new_edge_info)
                    edges_in_mask[edge_id].add((start_mx, start_my))
                    if len(valid_end_pt) > 0:
                        new_edge_info = dict(fpath=fpath[::-1],
                                             npath=npath[::-1],
                                             cont_end_pts=(
                                                 start_mx, start_my, info_on_pix[(start_mx, start_my)][0]['depth']),
                                             mask_id=edge_id,
                                             comp_edge_id=nid,
                                             depth=end_depth_maps[end_mx, end_my])
                        if edges_infos.get((end_mx, end_my)) is None:
                            edges_infos[(end_mx, end_my)] = []
                        edges_infos[(end_mx, end_my)].append(new_edge_info)
                        edges_in_mask[edge_id].add((end_mx, end_my))
    for edge_id, (context_cc, mask_cc, erode_context_cc, extend_context_cc, edge_cc) in enumerate(
            zip(context_ccs, mask_ccs, erode_context_ccs, extend_context_ccs, edge_ccs)):
        if len(specific_edge_id) > 0:
            if edge_id not in specific_edge_id:
                continue
        if len(context_cc) < 1 or len(mask_cc) < 1:
            continue
        edge_dict = get_edge_from_nodes(context_cc | extend_context_cc,
                                        erode_context_cc | extend_erode_context_ccs[edge_id], mask_cc, edge_cc,
                                        extend_edge_ccs[edge_id],
                                        mesh.graph['H'], mesh.graph['W'], mesh)
        if specific_edge_loc is not None and \
                (specific_edge_loc is not None and edge_dict['mask'][specific_edge_loc[0], specific_edge_loc[1]] == 0):
            continue
        else:
            tmp_specific_edge_id.append(edge_id)
        edge_dict['edge'], end_depth_maps, _ = \
            filter_irrelevant_edge_new(edge_dict['self_edge'], edge_dict['comp_edge'],
                                       edge_map,
                                       edge_maps_with_id,
                                       edge_id,
                                       edge_dict['context'],
                                       edge_dict['depth'], mesh,
                                       context_cc | erode_context_cc | extend_context_cc | extend_erode_context_ccs[
                                           edge_id], spdb=False)
        discard_map = np.zeros_like(edge_dict['edge'])
        mask_size = get_valid_size(edge_dict['mask'])
        mask_size = dilate_valid_size(mask_size, edge_dict['mask'], dilate=[20, 20])
        context_size = get_valid_size(edge_dict['context'])
        context_size = dilate_valid_size(context_size, edge_dict['context'], dilate=[20, 20])
        union_size = size_operation(mask_size, context_size, operation='+')
        patch_edge_dict = dict()
        patch_edge_dict['mask'], patch_edge_dict['context'], patch_edge_dict['rgb'], \
        patch_edge_dict['disp'], patch_edge_dict['edge'] = \
            crop_maps_by_size(union_size, edge_dict['mask'], edge_dict['context'],
                              edge_dict['rgb'], edge_dict['disp'], edge_dict['edge'])
        x_anchor, y_anchor = [union_size['x_min'], union_size['x_max']], [union_size['y_min'], union_size['y_max']]
        tensor_edge_dict = convert2tensor(patch_edge_dict)
        input_edge_feat = np.concatenate(
            (tensor_edge_dict['rgb'],
             tensor_edge_dict['disp'],
             tensor_edge_dict['edge'],
             1 - tensor_edge_dict['context'],
             tensor_edge_dict['mask']), axis=1)
        edge_dict['output'] = edge_dict['edge'].copy()

        if require_depth_edge(patch_edge_dict['edge'], patch_edge_dict['mask']) and inpaint_iter == 0:
            edge_dict['fpath_map'], edge_dict['npath_map'] = edge_dict['fpath_map'] * 0 - 1, edge_dict[
                'npath_map'] * 0 - 1
            end_pts = edges_in_mask[edge_id]
            for end_pt in end_pts:
                cur_edge_infos = edges_infos[(end_pt[0], end_pt[1])]
                cur_info = [xx for xx in cur_edge_infos if xx['mask_id'] == edge_id][0]
                other_infos = [xx for xx in cur_edge_infos if xx['mask_id'] != edge_id and len(xx['cont_end_pts']) > 0]
                if len(cur_info['cont_end_pts']) > 0 or (len(cur_info['cont_end_pts']) == 0 and len(other_infos) == 0):
                    for fnode in cur_info['fpath']:
                        edge_dict['fpath_map'][fnode[0], fnode[1]] = cur_info['comp_edge_id']
                    for fnode in cur_info['npath']:
                        edge_dict['npath_map'][fnode[0], fnode[1]] = cur_info['comp_edge_id']
            fnmap = edge_dict['fpath_map'] * 1
            fnmap[edge_dict['npath_map'] != -1] = edge_dict['npath_map'][edge_dict['npath_map'] != -1]
            for end_pt in end_pts:
                cur_edge_infos = edges_infos[(end_pt[0], end_pt[1])]
                cur_info = [xx for xx in cur_edge_infos if xx['mask_id'] == edge_id][0]
                cur_depth = cur_info['depth']
                other_infos = [xx for xx in cur_edge_infos if xx['mask_id'] != edge_id and len(xx['cont_end_pts']) > 0]
                comp_edge_id = cur_info['comp_edge_id']
                if len(cur_info['cont_end_pts']) == 0 and len(other_infos) > 0:
                    other_infos = sorted(other_infos, key=lambda aa: abs(abs(aa['cont_end_pts'][2]) - abs(cur_depth)))
                    for other_info in other_infos:
                        tmp_fmap, tmp_nmap = np.zeros((mesh.graph['H'], mesh.graph['W'])) - 1, np.zeros(
                            (mesh.graph['H'], mesh.graph['W'])) - 1
                        for fnode in other_info['fpath']:
                            if fnmap[fnode[0], fnode[1]] != -1:
                                tmp_fmap = tmp_fmap * 0 - 1
                                break
                            else:
                                tmp_fmap[fnode[0], fnode[1]] = comp_edge_id
                        if fnmap[fnode[0], fnode[1]] != -1:
                            continue
                        for fnode in other_info['npath']:
                            if fnmap[fnode[0], fnode[1]] != -1:
                                tmp_nmap = tmp_nmap * 0 - 1
                                break
                            else:
                                tmp_nmap[fnode[0], fnode[1]] = comp_edge_id
                        if fnmap[fnode[0], fnode[1]] != -1:
                            continue
                        break
                    if min(tmp_fmap.max(), tmp_nmap.max()) != -1:
                        edge_dict['fpath_map'] = tmp_fmap
                        edge_dict['fpath_map'][edge_dict['valid_area'] == 0] = -1
                        edge_dict['npath_map'] = tmp_nmap
                        edge_dict['npath_map'][edge_dict['valid_area'] == 0] = -1
                        discard_map = ((tmp_nmap != -1).astype(np.uint8) + (tmp_fmap != -1).astype(np.uint8)) * \
                                      edge_dict['mask']
                    else:
                        for fnode in cur_info['fpath']:
                            edge_dict['fpath_map'][fnode[0], fnode[1]] = cur_info['comp_edge_id']
                        for fnode in cur_info['npath']:
                            edge_dict['npath_map'][fnode[0], fnode[1]] = cur_info['comp_edge_id']
            edge_dict['output'] = (edge_dict['npath_map'] > -1) * edge_dict['mask'] + edge_dict['context'] * edge_dict[
                'edge']
        mesh, _, _, _ = create_placeholder(edge_dict['context'], edge_dict['mask'],
                                           edge_dict['depth'], edge_dict['fpath_map'],
                                           edge_dict['npath_map'], mesh, inpaint_iter,
                                           edge_ccs,
                                           extend_edge_ccs[edge_id],
                                           edge_maps_with_id,
                                           edge_id)

        dxs, dys = np.where(discard_map != 0)
        for dx, dy in zip(dxs, dys):
            mesh.nodes[(dx, dy)]['inpaint_twice'] = False
        depth_dict = depth_inpainting(context_cc, extend_context_cc,
                                      erode_context_cc | extend_erode_context_ccs[edge_id], mask_cc, mesh, config,
                                      union_size, depth_feat_model, edge_dict['output'])
        refine_depth_output = depth_dict['output'] * depth_dict['mask']
        for near_id in np.unique(edge_dict['npath_map'])[1:]:
            refine_depth_output = refine_depth_around_edge(
                refine_depth_output.copy(),
                (edge_dict['fpath_map'] == near_id).astype(np.uint8) *
                edge_dict['mask'],
                (edge_dict['fpath_map'] == near_id).astype(np.uint8),
                (edge_dict['npath_map'] == near_id).astype(np.uint8) *
                edge_dict['mask'],
                depth_dict['mask'].copy(),
                depth_dict['output'] * depth_dict['context'],
                config)
        depth_dict['output'][depth_dict['mask'] > 0] = refine_depth_output[depth_dict['mask'] > 0]
        rgb_dict = get_rgb_from_nodes(
            context_cc | extend_context_cc,
            erode_context_cc | extend_erode_context_ccs[edge_id], mask_cc, mesh.graph['H'],
            mesh.graph['W'], mesh)

        rgb_dict['edge'] = edge_dict['output']
        patch_rgb_dict = dict()
        patch_rgb_dict['mask'], patch_rgb_dict['context'], patch_rgb_dict['rgb'], \
        patch_rgb_dict['edge'] = crop_maps_by_size(
            union_size, rgb_dict['mask'],
            rgb_dict['context'], rgb_dict['rgb'],
            rgb_dict['edge'])
        tensor_rgb_dict = convert2tensor(patch_rgb_dict)
        resize_rgb_dict = {k: v.copy() for k, v in tensor_rgb_dict.items()}
        max_hw = np.array([*patch_rgb_dict['mask'].shape[-2:]]).max()
        init_frac = config['largest_size'] / (np.array([*patch_rgb_dict['mask'].shape[-2:]]).prod() ** 0.5)
        resize_hw = [patch_rgb_dict['mask'].shape[-2] * init_frac, patch_rgb_dict['mask'].shape[-1] * init_frac]
        resize_max_hw = max(resize_hw)
        frac = (np.floor(resize_max_hw / 128.) * 128.) / max_hw
        if frac < 1:
            resize_mark = cv2.resize(
                np.concatenate(
                    (resize_rgb_dict['mask'], resize_rgb_dict['context']),
                    axis=1).transpose(0, 2, 3, 1)[0],
                None,
                fx=frac, fy=frac,
                interpolation=cv2.INTER_AREA).transpose(2, 0, 1)[None, :]
            resize_rgb_dict['mask'] = (resize_mark[:, 0:1] > 0).astype(float)
            resize_rgb_dict['context'] = (np.abs(resize_mark[:, 1:2]-1) < 0.1).astype(float)
            resize_rgb_dict['context'][resize_rgb_dict['mask'] > 0] = 0
            resize_rgb_dict['rgb'] = cv2.resize(
                resize_rgb_dict['rgb'].transpose(0, 2, 3, 1)[0],
                None,
                fx=frac, fy=frac,
                interpolation=cv2.INTER_AREA).transpose(2, 0, 1)[None, :]
            resize_rgb_dict['rgb'] = resize_rgb_dict['rgb'] * resize_rgb_dict['context']
            resize_rgb_dict['edge'] = cv2.resize(
                resize_rgb_dict['edge'].transpose(0, 2, 3, 1)[0],
                None,
                fx=frac, fy=frac,
                interpolation=cv2.INTER_AREA)[None, None, :]
            resize_rgb_dict['edge'] = (resize_rgb_dict['edge'] > 0).astype(float) * 0
            resize_rgb_dict['edge'] = resize_rgb_dict['edge'] * (resize_rgb_dict['context'] + resize_rgb_dict['mask'])
        rgb_input_feat = np.concatenate((resize_rgb_dict['rgb'], resize_rgb_dict['edge']), axis=1)
        rgb_input_feat[:, 3] = 1 - rgb_input_feat[:, 3]
        resize_mask = open_small_mask(resize_rgb_dict['mask'], resize_rgb_dict['context'], 3, 41)
        specified_hole = resize_mask

        rgb_output = color_forward_3P(
            rgb_model, specified_hole, resize_rgb_dict['context'],
            resize_rgb_dict['rgb'], resize_rgb_dict['edge'])

        if config.get('gray_image') is True:
            rgb_output = rgb_output.mean(1, keepdim=True).repeat((1, 3, 1, 1))

        resize_rgb_dict['output'] = rgb_output * resize_rgb_dict['mask'] + resize_rgb_dict['rgb']
        tensor_rgb_dict['output'] = resize_rgb_dict['output']
        if frac < 1:
            tensor_rgb_dict['output'] = cv2.resize(
                tensor_rgb_dict['output'].transpose(0, 2, 3, 1)[0],
                tensor_rgb_dict['mask'].shape[-2:][::-1],
                interpolation=cv2.INTER_CUBIC).transpose(2, 0, 1)[None, :]
            tensor_rgb_dict['output'] = \
                tensor_rgb_dict['output'] * \
                tensor_rgb_dict['mask'] + (tensor_rgb_dict['rgb'] * tensor_rgb_dict['context'])
        patch_rgb_dict['output'] = tensor_rgb_dict['output'].squeeze().transpose(1, 2, 0)
        rgb_dict['output'] = np.zeros((mesh.graph['H'], mesh.graph['W'], 3))
        rgb_dict['output'][union_size['x_min']:union_size['x_max'], union_size['y_min']:union_size['y_max']] = \
            patch_rgb_dict['output']

        if require_depth_edge(patch_edge_dict['edge'], patch_edge_dict['mask']) or inpaint_iter > 0:
            edge_occlusion = True
        else:
            edge_occlusion = False
        for node in erode_context_cc:
            if rgb_dict['mask'][node[0], node[1]] > 0:
                for info in info_on_pix[(node[0], node[1])]:
                    if abs(info['depth']) == abs(node[2]):
                        info['update_color'] = (rgb_dict['output'][node[0], node[1]] * 255).astype(np.uint8)
        if frac < 1.:
            depth_edge_dilate_2_color_flag = False
        else:
            depth_edge_dilate_2_color_flag = True
        hxs, hys = np.where((rgb_dict['mask'] > 0) & (rgb_dict['erode'] == 0))
        for hx, hy in zip(hxs, hys):
            real_depth = None
            if abs(depth_dict['output'][hx, hy]) <= abs(np_depth[hx, hy]):
                depth_dict['output'][hx, hy] = np_depth[hx, hy] + 0.01
            node = (hx, hy, -depth_dict['output'][hx, hy])
            if info_on_pix.get((node[0], node[1])) is not None:
                for info in info_on_pix.get((node[0], node[1])):
                    if info.get('inpaint_id') is None or abs(info['inpaint_id'] < mesh.nodes[(hx, hy)]['inpaint_id']):
                        pre_depth = info['depth'] if info.get('real_depth') is None else info['real_depth']
                        if abs(node[2]) < abs(pre_depth):
                            node = (node[0], node[1], -(abs(pre_depth) + 0.001))
            if mesh.has_node(node):
                real_depth = node[2]
            while True:
                if mesh.has_node(node):
                    node = (node[0], node[1], -(abs(node[2]) + 0.001))
                else:
                    break
            if real_depth == node[2]:
                real_depth = None
            cur_disp = 1. / node[2]
            if not (mesh.has_node(node)):
                if not mesh.has_node((node[0], node[1])):
                    print("2D node not found.")
                if inpaint_iter == 1:
                    paint = (rgb_dict['output'][hx, hy] * 255).astype(np.uint8)
                else:
                    paint = (rgb_dict['output'][hx, hy] * 255).astype(np.uint8)
                ndict = dict(color=paint,
                             synthesis=True,
                             disp=cur_disp,
                             cc_id=set([edge_id]),
                             overlap_number=1.0,
                             refine_depth=False,
                             edge_occlusion=edge_occlusion,
                             depth_edge_dilate_2_color_flag=depth_edge_dilate_2_color_flag,
                             real_depth=real_depth)
                mesh, _, _ = refresh_node((node[0], node[1]), mesh.nodes[(node[0], node[1])], node, ndict, mesh,
                                          stime=True)
                if inpaint_iter == 0 and mesh.degree(node) < 4:
                    connnect_points_ccs[edge_id].add(node)
            if info_on_pix.get((hx, hy)) is None:
                info_on_pix[(hx, hy)] = []
            new_info = {'depth': node[2],
                        'color': paint,
                        'synthesis': True,
                        'disp': cur_disp,
                        'cc_id': set([edge_id]),
                        'inpaint_id': inpaint_iter + 1,
                        'edge_occlusion': edge_occlusion,
                        'overlap_number': 1.0,
                        'real_depth': real_depth}
            info_on_pix[(hx, hy)].append(new_info)
    specific_edge_id = tmp_specific_edge_id
    for erode_id, erode_context_cc in enumerate(erode_context_ccs):
        if len(specific_edge_id) > 0 and erode_id not in specific_edge_id:
            continue
        for erode_node in erode_context_cc:
            for info in info_on_pix[(erode_node[0], erode_node[1])]:
                if info['depth'] == erode_node[2]:
                    info['color'] = info['update_color']
                    mesh.nodes[erode_node]['color'] = info['update_color']
                    np_image[(erode_node[0], erode_node[1])] = info['update_color']
    new_edge_ccs = [set() for _ in range(mesh.graph['max_edge_id'] + 1)]
    for node in mesh.nodes:
        if len(node) == 2:
            mesh.remove_node(node)
            continue
        if mesh.nodes[node].get('edge_id') is not None and mesh.nodes[node].get('inpaint_id') == inpaint_iter + 1:
            if mesh.nodes[node].get('inpaint_twice') is False:
                continue
            try:
                new_edge_ccs[mesh.nodes[node].get('edge_id')].add(node)
            except:
                raise
    specific_mask_nodes = None
    if inpaint_iter == 0:
        mesh, info_on_pix = refine_color_around_edge(mesh, info_on_pix, new_edge_ccs, config, False)

    return mesh, info_on_pix, specific_mask_nodes, new_edge_ccs, connnect_points_ccs, np_image


def write_ply(image,
              depth,
              int_mtx,
              config,
              rgb_model,
              depth_edge_model,
              depth_edge_model_init,
              depth_feat_model):
    depth = depth.astype(np.float64)
    input_mesh, xy2depth, image, depth = create_mesh(depth, image, int_mtx, config)

    H, W = input_mesh.graph['H'], input_mesh.graph['W']
    input_mesh = tear_edges(input_mesh, config['depth_threshold'], xy2depth)
    input_mesh, info_on_pix = generate_init_node(input_mesh, min_node_in_cc=200)
    edge_ccs, input_mesh, edge_mesh = group_edges(
        input_mesh, config, image, remove_conflict_ordinal=False)

    input_mesh, info_on_pix, depth = reassign_floating_island(
        input_mesh, info_on_pix, image, depth)
    input_mesh = update_status(input_mesh, info_on_pix)

    edge_ccs, input_mesh, edge_mesh = group_edges(
        input_mesh, config, image, remove_conflict_ordinal=True)

    input_mesh, info_on_pix, edge_mesh, depth, aft_mark = \
        remove_dangling(
            input_mesh, edge_ccs, edge_mesh, info_on_pix,
            image, depth, config)

    input_mesh, depth, info_on_pix = update_status(
        input_mesh, info_on_pix, depth)
    edge_ccs, input_mesh, edge_mesh = group_edges(
        input_mesh, config, image, remove_conflict_ordinal=True)

    mesh, info_on_pix, depth = fill_missing_node(
        input_mesh, info_on_pix, image, depth)
    if config['extrapolate_border'] is True:
        input_mesh, info_on_pix, depth = refresh_bord_depth(
            input_mesh, info_on_pix, image, depth)
        input_mesh = remove_node_feat(input_mesh, 'edge_id')
        input_mesh, info_on_pix, depth, image = enlarge_border(
            input_mesh, info_on_pix, depth, image, config)
        H, W = image.shape[:2]
        input_mesh, info_on_pix = fill_dummy_bord(
            input_mesh, info_on_pix, image, depth, config)
        edge_ccs, input_mesh, edge_mesh = \
            group_edges(input_mesh, config, image, remove_conflict_ordinal=True)
        input_mesh = combine_end_node(input_mesh, edge_mesh, edge_ccs, depth)
        input_mesh, depth, info_on_pix = update_status(input_mesh, info_on_pix, depth)
        edge_ccs, input_mesh, edge_mesh = \
            group_edges(input_mesh, config, image, remove_conflict_ordinal=True, spdb=False)
        input_mesh = remove_redundant_edge(
            input_mesh, edge_mesh, edge_ccs, info_on_pix, config,
            redundant_number=config['redundant_number'], spdb=False)
        input_mesh, depth, info_on_pix = update_status(input_mesh, info_on_pix, depth)
        edge_ccs, input_mesh, edge_mesh = group_edges(input_mesh, config, image, remove_conflict_ordinal=True)
        input_mesh = combine_end_node(input_mesh, edge_mesh, edge_ccs, depth)
        input_mesh = remove_redundant_edge(
            input_mesh, edge_mesh, edge_ccs, info_on_pix, config,
            redundant_number=config['redundant_number'], invalid=True, spdb=False)
        input_mesh, depth, info_on_pix = update_status(input_mesh, info_on_pix, depth)
        edge_ccs, input_mesh, edge_mesh = group_edges(
            input_mesh, config, image, remove_conflict_ordinal=True)
        input_mesh = combine_end_node(input_mesh, edge_mesh, edge_ccs, depth)
        input_mesh, depth, info_on_pix = update_status(input_mesh, info_on_pix, depth)
        edge_ccs, input_mesh, edge_mesh = group_edges(
            input_mesh, config, image, remove_conflict_ordinal=True)
        edge_condition = lambda x, m: m.nodes[x].get('far') is not None and len(m.nodes[x].get('far')) > 0
        edge_map = get_map_from_ccs(edge_ccs, input_mesh.graph['H'], input_mesh.graph['W'], input_mesh, edge_condition)
        other_edge_with_id = get_map_from_ccs(edge_ccs, input_mesh.graph['H'], input_mesh.graph['W'], real_id=True)
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="up")
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="left")
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="down")
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="right")
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="right-up")
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="right-down")
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="left-up")
        info_on_pix, input_mesh, image, depth, edge_ccs = extrapolate(
            input_mesh, info_on_pix, image, depth,
            other_edge_with_id, edge_map, edge_ccs,
            depth_edge_model, depth_feat_model, rgb_model,
            config, direc="left-down")
    specific_edge_loc = None
    specific_edge_id = []
    vis_edge_id = None
    context_ccs, mask_ccs, broken_mask_ccs, edge_ccs, erode_context_ccs, \
    init_mask_connect, edge_maps, extend_context_ccs, extend_edge_ccs, extend_erode_context_ccs = \
        context_and_holes(
            input_mesh, edge_ccs, config,
            specific_edge_id, specific_edge_loc, depth_feat_model,
            inpaint_iter=0, vis_edge_id=vis_edge_id
        )

    specific_edge_loc = None
    input_mesh, info_on_pix, specific_edge_nodes, new_edge_ccs, connect_points_ccs, image = \
        DL_inpaint_edge(
            input_mesh,
            info_on_pix,
            config,
            image,
            depth,
            context_ccs,
            erode_context_ccs,
            extend_context_ccs,
            extend_erode_context_ccs,
            mask_ccs,
            broken_mask_ccs,
            edge_ccs,
            extend_edge_ccs,
            init_mask_connect,
            edge_maps,
            rgb_model,
            depth_edge_model,
            depth_edge_model_init,
            depth_feat_model,
            specific_edge_id,
            specific_edge_loc,
            inpaint_iter=0)

    specific_edge_id = []
    connect_points_ccs = [set() for _ in connect_points_ccs]
    context_ccs, mask_ccs, broken_mask_ccs, edge_ccs, erode_context_ccs, init_mask_connect, \
    edge_maps, extend_context_ccs, extend_edge_ccs, extend_erode_context_ccs = \
        context_and_holes(
            input_mesh, new_edge_ccs, config,
            specific_edge_id, specific_edge_loc, depth_feat_model,
            connect_points_ccs, inpaint_iter=1
        )

    specific_edge_id = []
    input_mesh, info_on_pix, specific_edge_nodes, new_edge_ccs, _, image = \
        DL_inpaint_edge(
            input_mesh,
            info_on_pix,
            config,
            image,
            depth,
            context_ccs,
            erode_context_ccs,
            extend_context_ccs,
            extend_erode_context_ccs,
            mask_ccs,
            broken_mask_ccs,
            edge_ccs,
            extend_edge_ccs,
            init_mask_connect,
            edge_maps,
            rgb_model,
            depth_edge_model,
            depth_edge_model_init,
            depth_feat_model,
            specific_edge_id,
            specific_edge_loc,
            inpaint_iter=1)
    vertex_id = 0
    input_mesh.graph['H'], input_mesh.graph['W'] = input_mesh.graph['noext_H'], input_mesh.graph['noext_W']

    ply_flag = config.get('save_ply', False)
    if ply_flag is True:
        node_str_list = []
    else:
        node_str_color = []
        node_str_point = []
    out_fmt = lambda x, x_flag: str(x) if x_flag is True else x

    k_00, k_02, k_11, k_12 = \
        input_mesh.graph['cam_param_pix_inv'][0, 0], input_mesh.graph['cam_param_pix_inv'][0, 2], \
        input_mesh.graph['cam_param_pix_inv'][1, 1], input_mesh.graph['cam_param_pix_inv'][1, 2]
    w_offset = input_mesh.graph['woffset']
    h_offset = input_mesh.graph['hoffset']
    for pix_xy, pix_list in info_on_pix.items():
        for pix_idx, pix_info in enumerate(pix_list):
            pix_depth = pix_info['depth'] if pix_info.get('real_depth') is None else pix_info['real_depth']
            str_pt = [out_fmt(x, ply_flag) for x in reproject_3d_int_detail(pix_xy[0], pix_xy[1], pix_depth,
                                                                            k_00, k_02, k_11, k_12, w_offset, h_offset)]
            if input_mesh.has_node((pix_xy[0], pix_xy[1], pix_info['depth'])) is False:
                return False
                continue
            if pix_info.get('overlap_number') is not None:
                str_color = [out_fmt(x, ply_flag) for x in
                             (pix_info['color'] / pix_info['overlap_number']).astype(np.uint8).tolist()]
            else:
                str_color = [out_fmt(x, ply_flag) for x in pix_info['color'].tolist()]
            if pix_info.get('edge_occlusion') is True:
                str_color.append(out_fmt(4, ply_flag))
            else:
                if pix_info.get('inpaint_id') is None:
                    str_color.append(out_fmt(1, ply_flag))
                else:
                    str_color.append(out_fmt(pix_info.get('inpaint_id') + 1, ply_flag))
            if pix_info.get('modified_border') is True or pix_info.get('ext_pixel') is True:
                if len(str_color) == 4:
                    str_color[-1] = out_fmt(5, ply_flag)
                else:
                    str_color.append(out_fmt(5, ply_flag))
            pix_info['cur_id'] = vertex_id
            input_mesh.nodes[(pix_xy[0], pix_xy[1], pix_info['depth'])]['cur_id'] = out_fmt(vertex_id, ply_flag)
            vertex_id += 1
            if ply_flag is True:
                node_str_list.append(' '.join(str_pt) + ' ' + ' '.join(str_color) + '\n')
            else:
                node_str_color.append(str_color)
                node_str_point.append(str_pt)
    str_faces = generate_face(input_mesh, info_on_pix, config)

    if ply_flag is True:
        ply_name = 'output.ply'
        print("Writing mesh file %s ..." % ply_name)
        with open(ply_name, 'w') as ply_fi:
            ply_fi.write('ply\n' + 'format ascii 1.0\n')
            ply_fi.write('comment H ' + str(int(input_mesh.graph['H'])) + '\n')
            ply_fi.write('comment W ' + str(int(input_mesh.graph['W'])) + '\n')
            ply_fi.write('comment hFov ' + str(float(input_mesh.graph['hFov'])) + '\n')
            ply_fi.write('comment vFov ' + str(float(input_mesh.graph['vFov'])) + '\n')
            ply_fi.write('element vertex ' + str(len(node_str_list)) + '\n')
            ply_fi.write('property float x\n' + \
                         'property float y\n' + \
                         'property float z\n' + \
                         'property uchar red\n' + \
                         'property uchar green\n' + \
                         'property uchar blue\n' + \
                         'property uchar alpha\n')
            ply_fi.write('element face ' + str(len(str_faces)) + '\n')
            ply_fi.write('property list uchar int vertex_index\n')
            ply_fi.write('end_header\n')
            ply_fi.writelines(node_str_list)
            ply_fi.writelines(str_faces)
        ply_fi.close()
        
        return input_mesh
    else:
        H = int(input_mesh.graph['H'])
        W = int(input_mesh.graph['W'])
        hFov = input_mesh.graph['hFov']
        vFov = input_mesh.graph['vFov']
        node_str_color = np.array(node_str_color).astype(np.float32)
        node_str_color[..., :3] = node_str_color[..., :3] / 255.
        node_str_point = np.array(node_str_point)
        str_faces = np.array(str_faces)

        return node_str_point, node_str_color, str_faces, H, W, hFov, vFov


def read_ply(mesh_fi):
    ply_fi = open(mesh_fi, 'r')
    Height = None
    Width = None
    hFov = None
    vFov = None
    while True:
        line = ply_fi.readline().split('\n')[0]
        if line.startswith('element vertex'):
            num_vertex = int(line.split(' ')[-1])
        elif line.startswith('element face'):
            num_face = int(line.split(' ')[-1])
        elif line.startswith('comment'):
            if line.split(' ')[1] == 'H':
                Height = int(line.split(' ')[-1].split('\n')[0])
            if line.split(' ')[1] == 'W':
                Width = int(line.split(' ')[-1].split('\n')[0])
            if line.split(' ')[1] == 'hFov':
                hFov = float(line.split(' ')[-1].split('\n')[0])
            if line.split(' ')[1] == 'vFov':
                vFov = float(line.split(' ')[-1].split('\n')[0])
        elif line.startswith('end_header'):
            break
    contents = ply_fi.readlines()
    vertex_infos = contents[:num_vertex]
    face_infos = contents[num_vertex:]
    verts = []
    colors = []
    faces = []
    for v_info in vertex_infos:
        str_info = [float(v) for v in v_info.split('\n')[0].split(' ')]
        if len(str_info) == 6:
            vx, vy, vz, r, g, b = str_info
        else:
            vx, vy, vz, r, g, b, hi = str_info
        verts.append([vx, vy, vz])
        colors.append([r, g, b, hi])
    verts = np.array(verts)
    try:
        colors = np.array(colors)
        colors[..., :3] = colors[..., :3] / 255.
    except:
        import pdb
        pdb.set_trace()

    for f_info in face_infos:
        _, v1, v2, v3 = [int(f) for f in f_info.split('\n')[0].split(' ')]
        faces.append([v1, v2, v3])
    faces = np.array(faces)

    return verts, colors, faces, Height, Width, hFov, vFov


class Canvas_view():
    def __init__(self,
                 fov,
                 verts,
                 faces,
                 colors,
                 canvas_size,
                 factor=1,
                 bgcolor='gray',
                 proj='perspective',
                 ):
        self.canvas = scene.SceneCanvas(bgcolor=bgcolor, size=(canvas_size * factor, canvas_size * factor))
        self.view = self.canvas.central_widget.add_view()
        self.view.camera = 'perspective'
        self.view.camera.fov = fov
        self.mesh = visuals.Mesh(shading=None)
        self.mesh.attach(Alpha(1.0))
        self.view.add(self.mesh)
        self.tr = self.view.camera.transform
        self.mesh.set_data(vertices=verts, faces=faces, vertex_colors=colors[:, :3])
        self.translate([0, 0, 0])
        self.rotate(axis=[1, 0, 0], angle=180)
        self.view_changed()

    def translate(self, trans=[0, 0, 0]):
        self.tr.translate(trans)

    def rotate(self, axis=[1, 0, 0], angle=0):
        self.tr.rotate(axis=axis, angle=angle)

    def view_changed(self):
        self.view.camera.view_changed()

    def render(self):
        return self.canvas.render()

    def reinit_mesh(self, verts, faces, colors):
        self.mesh.set_data(vertices=verts, faces=faces, vertex_colors=colors[:, :3])

    def reinit_camera(self, fov):
        self.view.camera.fov = fov
        self.view.camera.view_changed()


def output_3d_photo(
        verts, colors, faces, Height, Width, hFov, vFov, tgt_poses, video_traj_types, ref_pose,
        output_dir, ref_image, int_mtx, config, image, videos_poses, video_basename,
        original_H=None, original_W=None, border=None, depth=None, normal_canvas=None,
        all_canvas=None, mean_loc_depth=None):
    cam_mesh = netx.Graph()
    cam_mesh.graph['H'] = Height
    cam_mesh.graph['W'] = Width
    cam_mesh.graph['original_H'] = original_H
    cam_mesh.graph['original_W'] = original_W
    int_mtx_real_x = int_mtx[0] * Width
    int_mtx_real_y = int_mtx[1] * Height
    cam_mesh.graph['hFov'] = 2 * np.arctan((1. / 2.) * ((cam_mesh.graph['original_W']) / int_mtx_real_x[0]))
    cam_mesh.graph['vFov'] = 2 * np.arctan((1. / 2.) * ((cam_mesh.graph['original_H']) / int_mtx_real_y[1]))
    colors = colors[..., :3]

    fov_in_rad = max(cam_mesh.graph['vFov'], cam_mesh.graph['hFov'])
    fov = (fov_in_rad * 180 / np.pi)
    print("fov: " + str(fov))
    init_factor = 1
    if config.get('anti_flickering') is True:
        init_factor = 3
    if (cam_mesh.graph['original_H'] is not None) and (cam_mesh.graph['original_W'] is not None):
        canvas_w = cam_mesh.graph['original_W']
        canvas_h = cam_mesh.graph['original_H']
    else:
        canvas_w = cam_mesh.graph['W']
        canvas_h = cam_mesh.graph['H']
    canvas_size = max(canvas_h, canvas_w)
    if normal_canvas is None:
        normal_canvas = Canvas_view(fov,
                                    verts,
                                    faces,
                                    colors,
                                    canvas_size=canvas_size,
                                    factor=init_factor,
                                    bgcolor='gray',
                                    proj='perspective')
    else:
        normal_canvas.reinit_mesh(verts, faces, colors)
        normal_canvas.reinit_camera(fov)
    img = normal_canvas.render()
    backup_img, backup_all_img, all_img_wo_bound = img.copy(), img.copy() * 0, img.copy() * 0
    img = cv2.resize(img, (int(img.shape[1] / init_factor), int(img.shape[0] / init_factor)),
                     interpolation=cv2.INTER_AREA)
    if border is None:
        border = [0, img.shape[0], 0, img.shape[1]]
    H, W = cam_mesh.graph['H'], cam_mesh.graph['W']
    if (cam_mesh.graph['original_H'] is not None) and (cam_mesh.graph['original_W'] is not None):
        aspect_ratio = cam_mesh.graph['original_H'] / cam_mesh.graph['original_W']
    else:
        aspect_ratio = cam_mesh.graph['H'] / cam_mesh.graph['W']
    if aspect_ratio > 1:
        img_h_len = cam_mesh.graph['H'] if cam_mesh.graph.get('original_H') is None else cam_mesh.graph['original_H']
        img_w_len = img_h_len / aspect_ratio
        anchor = [0,
                  img.shape[0],
                  int(max(0, int((img.shape[1]) // 2 - img_w_len // 2))),
                  int(min(int((img.shape[1]) // 2 + img_w_len // 2), (img.shape[1]) - 1))]
    elif aspect_ratio <= 1:
        img_w_len = cam_mesh.graph['W'] if cam_mesh.graph.get('original_W') is None else cam_mesh.graph['original_W']
        img_h_len = img_w_len * aspect_ratio
        anchor = [int(max(0, int((img.shape[0]) // 2 - img_h_len // 2))),
                  int(min(int((img.shape[0]) // 2 + img_h_len // 2), (img.shape[0]) - 1)),
                  0,
                  img.shape[1]]
    anchor = np.array(anchor)
    plane_width = np.tan(fov_in_rad / 2.) * np.abs(mean_loc_depth)
    for video_pose, video_traj_type in zip(videos_poses, video_traj_types):
        stereos = []
        tops = [];
        buttoms = [];
        lefts = [];
        rights = []
        for tp_id, tp in enumerate(video_pose):
            rel_pose = np.linalg.inv(np.dot(tp, np.linalg.inv(ref_pose)))
            axis, angle = transforms3d.axangles.mat2axangle(rel_pose[0:3, 0:3])
            normal_canvas.rotate(axis=axis, angle=(angle * 180) / np.pi)
            normal_canvas.translate(rel_pose[:3, 3])
            new_mean_loc_depth = mean_loc_depth - float(rel_pose[2, 3])
            if 'dolly' in video_traj_type:
                new_fov = float((np.arctan2(plane_width, np.array([np.abs(new_mean_loc_depth)])) * 180. / np.pi) * 2)
                normal_canvas.reinit_camera(new_fov)
            else:
                normal_canvas.reinit_camera(fov)
            normal_canvas.view_changed()
            img = normal_canvas.render()
            img = cv2.GaussianBlur(img, (int(init_factor // 2 * 2 + 1), int(init_factor // 2 * 2 + 1)), 0)
            img = cv2.resize(img, (int(img.shape[1] / init_factor), int(img.shape[0] / init_factor)),
                             interpolation=cv2.INTER_AREA)
            img = img[anchor[0]:anchor[1], anchor[2]:anchor[3]]
            img = img[int(border[0]):int(border[1]), int(border[2]):int(border[3])]

            if any(np.array(config['crop_border']) > 0.0):
                H_c, W_c, _ = img.shape
                o_t = int(H_c * config['crop_border'][0])
                o_l = int(W_c * config['crop_border'][1])
                o_b = int(H_c * config['crop_border'][2])
                o_r = int(W_c * config['crop_border'][3])
                img = img[o_t:H_c - o_b, o_l:W_c - o_r]
                img = cv2.resize(img, (W_c, H_c), interpolation=cv2.INTER_CUBIC)

            """
            img = cv2.resize(img, (int(img.shape[1] / init_factor), int(img.shape[0] / init_factor)), interpolation=cv2.INTER_CUBIC)
            img = img[anchor[0]:anchor[1], anchor[2]:anchor[3]]
            img = img[int(border[0]):int(border[1]), int(border[2]):int(border[3])]

            if config['crop_border'] is True:
                top, buttom, left, right = find_largest_rect(img, bg_color=(128, 128, 128))
                tops.append(top); buttoms.append(buttom); lefts.append(left); rights.append(right)
            """
            stereos.append(img[..., :3])
            normal_canvas.translate(-rel_pose[:3, 3])
            normal_canvas.rotate(axis=axis, angle=-(angle * 180) / np.pi)
            normal_canvas.view_changed()
        """
        if config['crop_border'] is True:
            atop, abuttom = min(max(tops), img.shape[0]//2 - 10), max(min(buttoms), img.shape[0]//2 + 10)
            aleft, aright = min(max(lefts), img.shape[1]//2 - 10), max(min(rights), img.shape[1]//2 + 10)
            atop -= atop % 2; abuttom -= abuttom % 2; aleft -= aleft % 2; aright -= aright % 2
        else:
            atop = 0; abuttom = img.shape[0] - img.shape[0] % 2; aleft = 0; aright = img.shape[1] - img.shape[1] % 2
        """
        atop = 0;
        abuttom = img.shape[0] - img.shape[0] % 2;
        aleft = 0;
        aright = img.shape[1] - img.shape[1] % 2
        crop_stereos = []
        for stereo in stereos:
            crop_stereos.append((stereo[atop:abuttom, aleft:aright, :3] * 1).astype(np.uint8))
            stereos = crop_stereos
        clip = ImageSequenceClip(stereos, fps=config['fps'])
        if isinstance(video_basename, list):
            video_basename = video_basename[0]
        clip.write_videofile(os.path.join(output_dir, video_basename + '_' + video_traj_type + '.mp4'),
                             fps=config['fps'])

    return normal_canvas, all_canvas