vijaydwivedi75 / lrgb Goto Github PK

Hi.
I found that the link for downloading PCQM-Contact seems to be broken,
which is
self.url = 'https://datasets-public-research.s3.us-east-2.amazonaws.com/PCQM4M/pcqm4m-contact.tsv.gz'
at line 294 in pcqm4mv2_contact.py. Could you please check that? Thanks.

I also open the same issue in GraphGPS repo, where you could double check this issue.
Thanks.

Or we must use this code to generate them?

Hello, I found that there are identifier attributes in the peptide dataset, but I don't seem to find them described in the paper, could you please tell me what they are?
Best regards.

Hi!
@migalkin suggested on Twitter adding your datasets to the HuggingFace hub, which I think is a super cool idea, so I'm opening this issue to see if you need any help with that!

Here is the step by step tutorial on how to do so.
Ping me if you need anything in the process 🤗

Hello,

I am getting the following assertion error when I run the jupyter notebook to generate PASCAL VOC superpixel dataset. Can you please advise on how to resolve this error? I just ran the code without any modifications.

assert n_sp_extracted == np.max(superpixels) + 1, ('superpixel indices', np.unique(superpixels))

Best regards,
Hani

I am trying to work with the Pascal superpixel dataset. To avoid reprocessing the data, I used the Dataset class provided in torch_geometric ( https://pytorch-geometric.readthedocs.io/en/latest/_modules/torch_geometric/datasets/lrgb.html ).

I am trying to overlay the graphs on top of their corresponding images in the original dataset, which I downloaded from http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/semantic_contours/benchmark.tgz . However, I cannot figure out which images in this dataset correspond to which graphs in the other dataset.

For example, the first image in the Pascal validation dataset has dimensions (333, 500), but the maximum (x, y) coordinates in the graph of the first image from the torch_geometric Dataset are (492, 367). Do these correspond to different images, or am I misunderstanding how the coordinates are calculated?

Apologies if this is the wrong place to ask this! I appreciate any help you can offer.

Hi,

So I wanted to import this repo as a module. I installed it through conda as pip install git+https://github.com/vijaydwivedi75/lrgb.git.
I've done the same with the GraphGPS repo.

When I run this simple piece of code:
import graphgps
import lrgb

I get ModuleNotFoundError: No module named 'lrgb'.

Notice that the graphgps module imports without problems which leads me to believe the problem is in the lrgb repo and for the life of me I cannot figure it out.

I'd be very happy to get any suggestion. Thanks!

I found that the feature vector of these two datasets is 14-dimension, but when I read your paper , the description in this paper is " The initial feature of each superpixel node is 12 dimensional RGB feature value (mean, std, max, min) ".
So I don't particularly understand why the features are actually fourteen-dimensional. Could you please explain to me? Thanks for your kindness.

Hello,
Thank you for the nice code and timely dataset. I wonder as the label is of dimension 11, do you jointly predict all 11 features simultaneously, or do you predict each feature individually and then average MAE? Thank you!

Hi LRGB authors,

Nice work! Curious if there is a plan to publish those datasets in the format that can be loaded by DGL? Or provide APIs similar to OGB for DGL users?

-Minjie

Hello,

Any plans for supporting later releases of PyG (e.g. 2.1)? It's a fairly new benchmark and it's not compatible with the newest PyG releases out of the box.

Best regards,
Hani