You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello! This is indeed a very interesting work! I was inspired a lot. However, there is missing data in the benchmark_data of the repository, for example, the data dir is only partial. Additionally, could you possibly open source or share the code used to generate each ground truth image? This would be extremely helpful to us, thank you!
The text was updated successfully, but these errors were encountered:
Hi! Thank you for your interest in out work. As for data in the benchmark, there are no separate data files for example 1 to 75, as the data requirements are explicitly and clearly stated in the user query. Only examples ranging from 76 to 100 have separate data.csv files with the only exception of example 94, because for this example, the data requirements is stated in the user query as well. The reason is that the original data sample we adapted from Originlab GraphGallery does not contain a separate csv file.
Unfortunately, we did not save the corresponding code for the ground truths, sorry for the inconvenience. Your issue will inspire us to provide more detailed information in our benchmark in the future.
In you are really in a hurry, you could use the ground truth images as reference and find correponding Matplotlib Gallery examples from their website and adapt their code to help you generate ground truth images.
Hello! This is indeed a very interesting work! I was inspired a lot. However, there is missing data in the benchmark_data of the repository, for example, the data dir is only partial. Additionally, could you possibly open source or share the code used to generate each ground truth image? This would be extremely helpful to us, thank you!
The text was updated successfully, but these errors were encountered: