gabriel-sgama / semantic-superpoint Goto Github PK

Could you give an example for a pair of images? Thx.
And what is the difference between superpoint_coco_2017_ML22 and superpoint_coco_ssmall_ML22?

At first I'd like to thank you for this great work !
I want to test your pre-trained models in an implementation that uses .pth files instead of pth.tar. Thus, I tried your script "convert2script.py" in order to convert the weights to a pth model but it raises the following error:

RuntimeError: logs/superpoint_coco_ssmall_ML22/checkpoints/superPointNet_180000_checkpoint.pth.tar is a zip archive (did you mean to use torch.jit.load()?)

As I read, a possible reason is that the version of Pytorch that the model was trained is different with the installed Pytorch version. I'm using Pytorch 1.3.1 since this is the tested version for your implementation.
What version did you use to train the proposed pre-trained models ? Is the Pytorch=1.3.1 the recommended version ?

There are too few visulaized results in this repo. I have read the paper. Does this model only improve the keypoints' quality? Or this model predict the keypoints' label?

I would like to train the models with other datasets, but have some confusions.

1. What is the relationship between the code Train_model_frontend_all.py and Train_model_heatmap_all.py ?
2. Does *_all_ct.py in the readme means *_all_and.py?
3. ModuleNotFoundError: No module named 'utils.loss_functions.min_norm_solvers'

Thanks for the great work!!! I am interested about the implementation of the unc+ct loss for the multi-task learning, and is there any plan to release the code for the unc loss?

When I run train4.py, the error shows that no module named "Train_model_heatmap", and I change the front_end_model in "magicpoint_shapes_pair" to "Train_model_heatmap_all", and then the following error occurred:
Traceback (most recent call last).
File "semanticSP/train4.py", line 143, in
args.func(config, output_dir, args)
File "semanticSP/train4.py", line 44, in train_base
return train_joint(config, output_dir, args)
File "semanticSP/train4.py", line 83, in train_joint
train_agent = train_model_frontend(config, save_path=save_path, device=device)
File "semanticSP/Train_model_heatmap_all.py", line 108, in init
self.r = self.config["model"]["real_batch_size"] // self.config["model"]["batch_size"]
KeyError: 'real_batch_size'
What is the problem?