We have a question about the calculation of the overlap ratio. In your paper you say "ModelNet which has 73.5% pairwise overlap on average, and ModelLoNet which contains a lower 53.6% average overlap". However, when I wrote a piece of code to test the overlap ratio, I could only get 51.35% for ModelNet and 43.16% for ModelLoNet. What is the reason? The testing code is as follows, I put it under datasets/modelnet.py
if __name__ == "__main__":
from lib.utils import setup_seed, load_config
from easydict import EasyDict as edict
import pdb
import torch
from tqdm import tqdm
config_dir = 'configs/test/modelnet.yaml'
config = load_config(config_dir)
config = edict(config)
test_dataset = get_test_datasets(config)
overlap_list = []
test_loader = torch.utils.data.DataLoader(test_dataset, batch_size=1, shuffle=False, num_workers=4)
for i, data in tqdm(enumerate(test_loader)):
# pdb.set_trace()
correspondence = data[6]
src_idx = list(set(correspondence[0][:,0].int().tolist()))
overlap_list.append(len(src_idx)/717)
print(np.mean(overlap_list))
Hi! Thank you for the amazing work!
We have a question about the calculation of the overlap ratio. In your paper you say "ModelNet which has 73.5% pairwise overlap on average, and ModelLoNet which contains a lower 53.6% average overlap". However, when I wrote a piece of code to test the overlap ratio, I could only get 51.35% for ModelNet and 43.16% for ModelLoNet. What is the reason? The testing code is as follows, I put it under datasets/modelnet.py
Thank you and look forward to your reply!