yichen928 / strl Goto Github PK

Hello,

thanks for your work. I have a question.
For the indoor semantic segmentation downstream task, it seems the pretrain task is still a classification task?
Am I right?

Hi !
Thanks for your great job for model pretraining on point clouds, I have a question about the outdoor scenes model, PVRCNN. Unlike the indoor scenes model VoteNet, the PVRCNN is a more complex model with two stages. So my question is where the max pooling is applied for the PVRCNN model, 3D backbone or 2D backbone?
Thanks for your reply!

this weight raise a error when load it to model.

 RuntimeError: unexpected EOF, expected 9781136 more bytes. The file might be corrupted.
terminate called without an active exception

https://drive.google.com/file/d/1NzFKTyw_TfZQon902IqEnldODYgWKvlG/view?usp=sharing

Thanks for your great work! Looking forward to try out this method on outdoor 3D detection task, may I ask when will you release the related codes?

Hello, I can't open your paper. Could you please check the arxiv link of your paper, please?

I'm sorry to bother you. Are the classification experiments in your paper under 2048 points?

I found it rank2 with kitti dataset,but i can't find something about kitti in your code.

Thanks for your great work! I tried to run the training experiment with dgcnn in classification task .But I only got around 70% accuarcy in SVM evaluation and 89.6% in fine-tune evaluation. During training I found my val_loss is lower than 0.2 after 10 epoch , but the checkpoint you provided has 0.513 val_loss at epoch 51 . Is there something wrong with my config ? Thanks

optimizer:
weight_decay: 0.01
lr: 1e-3
type: adam

network: DGCNN
dataset: ShapeNet # ShapeNet, ShapeNetPart, ModelNet40, ScanNet
num_points: 2048 # 2048 for ShapeNet, 4096 for ModelNet40, 4096 for ScanNet
epochs: 100
batch_size: 32
acc_batches: 1
transform_mode: both

decay_rate: 0.996
mlp_hidden_size: 4096
projection_size: 256

k: 40
emb_dims: 1024
window_length: 3
dropout: 0.5
num_workers: 32

resume_ckpt:

Sorry to bother you, I've got an error when running train.py. ShapeNet is used as a pre-training dataset and ModelNet40 is an evaluation dataset. The two datasets are downloaded and I put them in a directory as described readme file. The detail of traceback information as follows.

Traceback (most recent call last):
File "/home/jiangfan/workspace/codespace/STRL/BYOL/train.py", line 67, in
main()
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/hydra/main.py", line 20, in decorated_main
run_hydra(
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/hydra/_internal/utils.py", line 171, in run_hydra
hydra.run(
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/hydra/_internal/hydra.py", line 82, in run
return run_job(
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/hydra/plugins/common/utils.py", line 109, in run_job
ret.return_value = task_function(task_cfg)
File "/home/jiangfan/workspace/codespace/STRL/BYOL/train.py", line 63, in main
trainer.fit(model)
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 997, in fit
results = self.dp_train(model)
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/pytorch_lightning/trainer/distrib_parts.py", line 270, in dp_train
result = self.run_pretrain_routine(model)
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1185, in run_pretrain_routine
self.reset_val_dataloader(ref_model)
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py", line 343, in reset_val_dataloader
self.num_val_batches, self.val_dataloaders = self._reset_eval_dataloader(model, 'val')
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py", line 303, in _reset_eval_dataloader
num_batches = len(dataloader) if _has_len(dataloader) else float('inf')
File "/home/jiangfan/miniconda3/envs/pytorch2/lib/python3.8/site-packages/pytorch_lightning/trainer/data_loading.py", line 58, in _has_len
raise ValueError('Dataloader returned 0 length.'
ValueError: Dataloader returned 0 length. Please make sure that your Dataloader at least returns 1 batch