Spaces:
Build error
Build error
""" | |
@date: 2021/6/16 | |
@description: | |
""" | |
import math | |
import os | |
import numpy as np | |
from dataset.communal.read import read_image, read_label | |
from dataset.communal.base_dataset import BaseDataset | |
from utils.logger import get_logger | |
class PanoS2D3DDataset(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, subset=None): | |
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 | |
if mode is None: | |
return | |
label_dir = os.path.join(root_dir, 'valid' if mode == 'val' else mode, 'label_cor') | |
img_dir = os.path.join(root_dir, 'valid' if mode == 'val' else mode, 'img') | |
if split_list is None: | |
split_list = [name.split('.')[0] for name in os.listdir(label_dir) if | |
not name.startswith('.') and name.endswith('txt')] | |
split_list.sort() | |
assert subset == 'pano' or subset == 's2d3d' or subset is None, 'error subset' | |
if subset == 'pano': | |
split_list = [name for name in split_list if 'pano_' in name] | |
logger.info(f"Use PanoContext Dataset") | |
elif subset == 's2d3d': | |
split_list = [name for name in split_list if 'camera_' in name] | |
logger.info(f"Use Stanford2D3D Dataset") | |
if for_test_index is not None: | |
split_list = split_list[:for_test_index] | |
self.data = [] | |
invalid_num = 0 | |
for name in split_list: | |
img_path = os.path.join(img_dir, f"{name}.png") | |
label_path = os.path.join(label_dir, f"{name}.txt") | |
if not os.path.exists(img_path): | |
logger.warning(f"{img_path} not exists") | |
invalid_num += 1 | |
continue | |
if not os.path.exists(label_path): | |
logger.warning(f"{label_path} not exists") | |
invalid_num += 1 | |
continue | |
with open(label_path, 'r') as f: | |
lines = [line for line in f.readlines() if | |
len([c for c in line.split(' ') if c[0].isnumeric()]) > 1] | |
if len(lines) % 2 != 0: | |
invalid_num += 1 | |
continue | |
self.data.append([img_path, label_path]) | |
logger.info( | |
f"Build dataset mode: {self.mode} valid: {len(self.data)} invalid: {invalid_num}") | |
def __getitem__(self, idx): | |
rgb_path, label_path = self.data[idx] | |
label = read_label(label_path, data_type='Pano_S2D3D') | |
image = read_image(rgb_path, self.shape) | |
output = self.process_data(label, image, self.patch_num) | |
return output | |
if __name__ == '__main__': | |
modes = ['test', 'val', 'train'] | |
for i in range(1): | |
for mode in modes: | |
print(mode) | |
mp3d_dataset = PanoS2D3DDataset(root_dir='../src/dataset/pano_s2d3d', mode=mode, aug={ | |
# 'STRETCH': True, | |
# 'ROTATE': True, | |
# 'FLIP': True, | |
# 'GAMMA': True | |
}) | |
continue | |
save_dir = f'../src/dataset/pano_s2d3d/visualization/{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")) | |