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