gap-lab-cuhk-sz / to-scene Goto Github PK
View Code? Open in Web Editor NEW(ECCV 2022 Oral) TO-Scene: A Large-scale Dataset for Understanding 3D Tabletop Scenes
License: MIT License
(ECCV 2022 Oral) TO-Scene: A Large-scale Dataset for Understanding 3D Tabletop Scenes
License: MIT License
Can you tell me where it is?
thank you !
I think the TO-scene presented in the paper constructed mesh representations.
In github, but dataset is constructed by point cloud.
Is there any plan to release mesh dataset?
Thanks
I'm sorry to bother you, I used the source code which provided for training. At the 50th round of training, the loss value was still large and had no convergence trend, and the accuracy was also very low. Can you tell me why? Alternatively, could you share your checkpoint
Thanks!
![screenshot](https://github.com/GAP-LAB-CUHK-SZ/TO-Scene/assets/115631053/9b94c836-073c-4ecb-b1ff-5b3ebce97147)
Hello, I followed the step of 3d object detection, but when I am running python main.py --mode train --config ./configs/train_heatmap.yaml, I encountered follow problem:
Loading configuration
{'resume': False, 'method': 'heatmap', 'exp_name': 'TO-crowrd_heatmap_1124', 'device': {'use_gpu': True, 'gpu_ids': '3'}, 'data': {'dataset': 'TOS_desk', 'data_dir': './data/TO-crowd-wHM', 'use_color': False, 'use_height': True, 'use_aug': True, 'batch_size': 8, 'num_workers': 8, 'ap_iou_thresh': 0.25, 'npoints': 40000}, 'model': {'input_feature_dim': 1}, 'optimizer': {'type': 'Adam', 'lr': 0.0001, 'beta1': 0.9, 'beta2': 0.999, 'eps': None, 'weight_decay': None}, 'scheduler': {'type': 'MultiStepLR', 'milestone': [50, 80], 'gamma': 0.2}, 'other': {'nepoch': 100, 'model_save_interval': 1, 'model_save_dir': './checkpoints', 'dump_result': True, 'dump_interval': 1000, 'test_interval': 10, 'log_interval': 100}, 'log': {'path': './checkpoints/TO-crowrd_heatmap_1124'}, 'config': './configs/train_heatmap.yaml', 'mode': 'train'}
Data save path: ./checkpoints/TO-crowrd_heatmap_1124
Loading device settings.
CPU mode is on.
Loading dataset.
Traceback (most recent call last):
File "/home/ray/workspace/HRI_Project/TO-Scene/obj_det/main.py", line 25, in
train.run(cfg)
File "/home/ray/workspace/HRI_Project/TO-Scene/obj_det/train.py", line 15, in run
train_loader = get_dataloader(cfg.config, mode='train')
File "/home/ray/workspace/HRI_Project/TO-Scene/obj_det/utils/train_test_utils.py", line 297, in get_dataloader
from dataset.TOS_desk_dataset import TOS_Desk_Dataloader
File "/home/ray/workspace/HRI_Project/TO-Scene/obj_det/dataset/TOS_desk_dataset.py", line 7, in
DC=DOS_desk_config()
File "/home/ray/workspace/HRI_Project/TO-Scene/obj_det/data/model_utils_DOS.py", line 32, in init
self.mean_size_arr = np.load(os.path.join('./data/doscannet_means_desklevel-axisalign-5e6.npz'))['arr_0']
File "/home/ray/anaconda3/envs/pytorch/lib/python3.9/site-packages/numpy/lib/npyio.py", line 405, in load
fid = stack.enter_context(open(os_fspath(file), "rb"))
FileNotFoundError: [Errno 2] No such file or directory: './data/doscannet_means_desklevel-axisalign-5e6.npz'
It seems that it can't find file doscannet_means_desklevel-axisalign-5e6.npz, however I don't know where the file is.
Could you please tell me how to deal with this?
Thanks very much.
I used the pointnet++ model to train the dataset, and tested the val dataset very well. However, when testing the To-real dataset, the accuracy was very low. Can you tell me why ?
thanks!
Thank you for making this dataset available!
Could you please update the TO-Real download link?
Recently, when reproducing this paper, I found that there are no labels in the test set , so I would like to ask about this situation.
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