| import numpy as np |
| import networkx as nx |
| import itertools |
|
|
| import ssg_utils as utils |
|
|
|
|
| def are_furniture_aligned(furniture1, furniture2, offset_threshold): |
| x1, y1, z1 = furniture1['center'] |
| x2, y2, z2 = furniture2['center'] |
| h1 = furniture1['size'] |
| h2 = furniture2['size'] |
| rect1 = furniture1['rect'] |
| rect2 = furniture2['rect'] |
|
|
| |
| x_offset = abs(x1 - x2) |
| |
| y_offset = abs(y1 - y2) |
| |
| z_offset = abs(z1 - z2) |
|
|
| |
| volumn_diff = abs(utils.get_Poly_Area(rect1) - utils.get_Poly_Area(rect2)) |
|
|
| if volumn_diff > offset_threshold: |
| return False |
| if z_offset > offset_threshold: |
| return False |
|
|
| if x_offset > offset_threshold and y_offset > offset_threshold: |
| return False |
|
|
| if x_offset < offset_threshold: |
| return 'x' |
|
|
| if y_offset < offset_threshold: |
| return 'y' |
|
|
|
|
| def find_aligned_furniture(furniture_list, ObjNode_dict, offset_threshold): |
| aligned_furniture = [] |
|
|
| for i, object_id1 in enumerate(furniture_list): |
| obj1 = ObjNode_dict[object_id1] |
| furniture1 = {'center': np.array(obj1.position), 'size': obj1.z_max - obj1.z_min, 'rect': obj1.bottom_rect} |
|
|
| for j, object_id2 in enumerate(furniture_list[i+1:]): |
| obj2 = ObjNode_dict[object_id2] |
| furniture2 = {'center': np.array(obj2.position), 'size': obj2.z_max - obj2.z_min, 'rect': obj2.bottom_rect} |
| is_aligned = are_furniture_aligned(furniture1, furniture2, offset_threshold) |
| if is_aligned: |
| aligned_group = [obj1.id, obj2.id, is_aligned] |
| aligned_furniture.append(aligned_group) |
|
|
| aligned_furniture_merge = furniture_merge_lists(aligned_furniture) |
| return aligned_furniture_merge |
|
|
| def furniture_merge_lists(lists): |
| merged_lists = [] |
|
|
| x_list = [lst[:2] for lst in lists if 'x' in lst] |
| y_list = [lst[:2] for lst in lists if 'y' in lst] |
|
|
| merged_x_list = merge_sublists(x_list) |
| merged_y_list = merge_sublists(y_list) |
|
|
| merged_lists.extend(merged_x_list) |
| merged_lists.extend(merged_y_list) |
|
|
| return merged_lists |
|
|
|
|
| def merge_sublists(L): |
| length = len(L) |
| for i in range(1, length): |
| for j in range(i): |
| if 0 in L[i] or 0 in L[j]: |
| continue |
| x = set(L[i]).union(set(L[j])) |
| y = len(L[i]) + len(L[j]) |
| if len(x) < y: |
| L[i] = list(x) |
| L[j] = [0] |
|
|
| return [i for i in L if 0 not in i] |
|
|
|
|
| def find_middle_furniture (proximity_relations, ObjNode_dict): |
| |
| middle_relationships = [] |
| G = nx.DiGraph() |
| for (src, tgt, rel) in proximity_relations: |
| G.add_edge(src, tgt, label=rel) |
|
|
| edage_dict = G.edges.data()._adjdict |
| for src_id in ObjNode_dict: |
| if src_id not in edage_dict: continue |
| if ObjNode_dict[src_id].label == 'floor' :continue |
| neighbors = edage_dict[src_id] |
| tgt_ids = list(neighbors.keys()) |
| combinations = list(itertools.combinations(tgt_ids, 2)) |
|
|
| for group in combinations: |
| idx1, idx2 = group |
| if 'near' in neighbors[idx1]['label'] and 'near' in neighbors[idx2]['label']: |
|
|
| direction1 = int(neighbors[idx1]['label'].split(' ')[0]) |
| direction2 = int(neighbors[idx2]['label'].split(' ')[0]) |
| if abs(direction1 - direction2) == 6: |
| middle_relationships.append([[src_id,idx1,idx2], 'in the middle of']) |
|
|
| return middle_relationships |
|
|
|
|
| if __name__ == '__main__': |
| |
| lists = [['26', '36', 'x'], ['26', '30', 'x'], ['29', '28', 'y'], ['29', '30', 'y'], |
| ['28', '30', 'y'], ['28', '33', 'x'], ['35', '36', 'y'], ['35', '32', 'y'], |
| ['35', '33', 'y'], ['31', '37', 'x'], ['2', '4', 'y'], ['2', '3', 'y'], |
| ['34', '32', 'y'], ['34', '33', 'y'], ['37', '3', 'x'], ['36', '30', 'x'], |
| ['4', '3', 'y'], ['32', '33', 'y']] |
| output = furniture_merge_lists(lists) |
| print(output) |
|
|
