gorilla-lab-scut / dualposenet Goto Github PK

Recently, I have tried to reproduce results that was given in the DualPoseNet paper. Therefore, I used training_data_prepare.py script to generate necessary training data (for CAMERA25 and REAL275 datasets), which allowed me successfully reproduce results on CAMERA25 dataset.

However, results after training model on REAL275 were very far from the paper results. So, after that I began to wonder -- maybe, I do something wrong in case of training/evaluation on REAL275 dataset.

My pipeline of actions for REAL275 was:

1. Download NOCS data and run python training_data_prepare.py.
2. Run python main.py --phase train --dataset REAL275
3. Run python main.py --phase test --dataset REAL275

I did not save results of mine model evaluation on REAL275, but if you need it I can recalculate them for the issue investigation!

Thank you in advance!

Good afternoon, thank you for your work, I would very much like to conduct training, but today the link to the datasets does not work(
Maybe you saved the datasets on google drive or know some other workaround?
I also tried downloading as recommended in hughw19/NOCS_CVPR2019#59

Hi, Thanks for the excellent work. I am wondering how fast the inference speed is. I didn't find this kind of information in the paper.

Like the title, where is the data and how to create the dataset used in the code?

Thank you for the great work.

I have been looking to test the model on custom images. To achieve that, I was wondering on, how to create depth png files in the same format, as provided in real275 dataset. I can see pixel values ranging from 0 to ~10 in depth png files. How can I get depth in same format for my custom sample images?

I tried testing on SUNRGBD dataset, results are not as per expectation.

Thank you in advance.

I think I shuld generate result pkl files by running Testing 2 times( w/o refined, w/ refined version) and then your code will generate the pkl files and then I should run eval.py. right?

我在执行代码时遇到了这个问题 ，请问为什么会出现这个问题