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""" |
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@date: 2021/6/16 |
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@description: |
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""" |
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import os |
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from dataset.pano_s2d3d_dataset import PanoS2D3DDataset |
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from utils.logger import get_logger |
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class PanoS2D3DMixDataset(PanoS2D3DDataset): |
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def __init__(self, root_dir, mode, shape=None, max_wall_num=0, aug=None, camera_height=1.6, logger=None, |
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split_list=None, patch_num=256, keys=None, for_test_index=None, subset=None): |
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assert subset == 's2d3d' or subset == 'pano', 'error subset' |
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super().__init__(root_dir, None, shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, subset) |
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if logger is None: |
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logger = get_logger() |
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self.mode = mode |
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if mode == 'train': |
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if subset == 'pano': |
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s2d3d_train_data = PanoS2D3DDataset(root_dir, 'train', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 's2d3d').data |
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s2d3d_val_data = PanoS2D3DDataset(root_dir, 'val', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 's2d3d').data |
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s2d3d_test_data = PanoS2D3DDataset(root_dir, 'test', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 's2d3d').data |
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s2d3d_all_data = s2d3d_train_data + s2d3d_val_data + s2d3d_test_data |
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pano_train_data = PanoS2D3DDataset(root_dir, 'train', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 'pano').data |
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self.data = s2d3d_all_data + pano_train_data |
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elif subset == 's2d3d': |
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pano_train_data = PanoS2D3DDataset(root_dir, 'train', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 'pano').data |
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pano_val_data = PanoS2D3DDataset(root_dir, 'val', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 'pano').data |
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pano_test_data = PanoS2D3DDataset(root_dir, 'test', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 'pano').data |
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pano_all_data = pano_train_data + pano_val_data + pano_test_data |
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s2d3d_train_data = PanoS2D3DDataset(root_dir, 'train', shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, 's2d3d').data |
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self.data = pano_all_data + s2d3d_train_data |
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else: |
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self.data = PanoS2D3DDataset(root_dir, mode, shape, max_wall_num, aug, camera_height, logger, |
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split_list, patch_num, keys, None, subset).data |
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if for_test_index is not None: |
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self.data = self.data[:for_test_index] |
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logger.info(f"Build dataset mode: {self.mode} valid: {len(self.data)}") |
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if __name__ == '__main__': |
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import numpy as np |
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from PIL import Image |
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from tqdm import tqdm |
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from visualization.boundary import draw_boundaries |
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from visualization.floorplan import draw_floorplan |
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from utils.boundary import depth2boundaries |
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from utils.conversion import uv2xyz |
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modes = ['test', 'val', 'train'] |
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for i in range(1): |
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for mode in modes: |
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print(mode) |
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mp3d_dataset = PanoS2D3DMixDataset(root_dir='../src/dataset/pano_s2d3d', mode=mode, aug={ |
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}, subset='pano') |
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continue |
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save_dir = f'../src/dataset/pano_s2d3d/visualization1/{mode}' |
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if not os.path.isdir(save_dir): |
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os.makedirs(save_dir) |
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bar = tqdm(mp3d_dataset, ncols=100) |
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for data in bar: |
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bar.set_description(f"Processing {data['id']}") |
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boundary_list = depth2boundaries(data['ratio'], data['depth'], step=None) |
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pano_img = draw_boundaries(data['image'].transpose(1, 2, 0), boundary_list=boundary_list, show=False) |
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Image.fromarray((pano_img * 255).astype(np.uint8)).save( |
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os.path.join(save_dir, f"{data['id']}_boundary.png")) |
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floorplan = draw_floorplan(uv2xyz(boundary_list[0])[..., ::2], show=False, |
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marker_color=None, center_color=0.8, show_radius=None) |
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Image.fromarray((floorplan.squeeze() * 255).astype(np.uint8)).save( |
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os.path.join(save_dir, f"{data['id']}_floorplan.png")) |
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