""" @Date: 2021/09/22 @description: """ import os import json import math import numpy as np from dataset.communal.read import read_image, read_label, read_zind from dataset.communal.base_dataset import BaseDataset from utils.logger import get_logger from preprocessing.filter import filter_center, filter_boundary, filter_self_intersection from utils.boundary import calc_rotation class ZindDataset(BaseDataset): def __init__(self, root_dir, mode, shape=None, max_wall_num=0, aug=None, camera_height=1.6, logger=None, split_list=None, patch_num=256, keys=None, for_test_index=None, is_simple=True, is_ceiling_flat=False, vp_align=False): # if keys is None: # keys = ['image', 'depth', 'ratio', 'id', 'corners', 'corner_heat_map', 'object'] super().__init__(mode, shape, max_wall_num, aug, camera_height, patch_num, keys) if logger is None: logger = get_logger() self.root_dir = root_dir self.vp_align = vp_align data_dir = os.path.join(root_dir) img_dir = os.path.join(root_dir, 'image') pano_list = read_zind(partition_path=os.path.join(data_dir, f"zind_partition.json"), simplicity_path=os.path.join(data_dir, f"room_shape_simplicity_labels.json"), data_dir=data_dir, mode=mode, is_simple=is_simple, is_ceiling_flat=is_ceiling_flat) if for_test_index is not None: pano_list = pano_list[:for_test_index] if split_list: pano_list = [pano for pano in pano_list if pano['id'] in split_list] self.data = [] invalid_num = 0 for pano in pano_list: if not os.path.exists(pano['img_path']): logger.warning(f"{pano['img_path']} not exists") invalid_num += 1 continue if not filter_center(pano['corners']): # logger.warning(f"{pano['id']} camera center not in layout") # invalid_num += 1 continue if self.max_wall_num >= 10: if len(pano['corners']) < self.max_wall_num: invalid_num += 1 continue elif self.max_wall_num != 0 and len(pano['corners']) != self.max_wall_num: invalid_num += 1 continue if not filter_boundary(pano['corners']): logger.warning(f"{pano['id']} boundary cross") invalid_num += 1 continue if not filter_self_intersection(pano['corners']): logger.warning(f"{pano['id']} self_intersection") invalid_num += 1 continue self.data.append(pano) logger.info( f"Build dataset mode: {self.mode} max_wall_num: {self.max_wall_num} valid: {len(self.data)} invalid: {invalid_num}") def __getitem__(self, idx): pano = self.data[idx] rgb_path = pano['img_path'] label = pano image = read_image(rgb_path, self.shape) if self.vp_align: # Equivalent to vanishing point alignment step rotation = calc_rotation(corners=label['corners']) shift = math.modf(rotation / (2 * np.pi) + 1)[0] image = np.roll(image, round(shift * self.shape[1]), axis=1) label['corners'][:, 0] = np.modf(label['corners'][:, 0] + shift)[0] output = self.process_data(label, image, self.patch_num) return output if __name__ == "__main__": import numpy as np from PIL import Image from tqdm import tqdm from visualization.boundary import draw_boundaries, draw_object from visualization.floorplan import draw_floorplan from utils.boundary import depth2boundaries, calc_rotation from utils.conversion import uv2xyz from models.other.init_env import init_env init_env(123) modes = ['val'] for i in range(1): for mode in modes: print(mode) mp3d_dataset = ZindDataset(root_dir='../src/dataset/zind', mode=mode, aug={ 'STRETCH': False, 'ROTATE': False, 'FLIP': False, 'GAMMA': False }) # continue # save_dir = f'../src/dataset/zind/visualization/{mode}' # if not os.path.isdir(save_dir): # os.makedirs(save_dir) bar = tqdm(mp3d_dataset, ncols=100) for data in bar: # if data['id'] != '1079_pano_18': # continue bar.set_description(f"Processing {data['id']}") boundary_list = depth2boundaries(data['ratio'], data['depth'], step=None) pano_img = draw_boundaries(data['image'].transpose(1, 2, 0), boundary_list=boundary_list, show=True) # Image.fromarray((pano_img * 255).astype(np.uint8)).save( # os.path.join(save_dir, f"{data['id']}_boundary.png")) # draw_object(pano_img, heat_maps=data['object_heat_map'], depth=data['depth'], # size=data['object_size'], show=True) # pass # floorplan = draw_floorplan(uv2xyz(boundary_list[0])[..., ::2], show=True, marker_color=None, center_color=0.2) # Image.fromarray((floorplan.squeeze() * 255).astype(np.uint8)).save( # os.path.join(save_dir, f"{data['id']}_floorplan.png"))