cap-ntu / fedreid Goto Github PK

We are trying to get close to the experiment, but the file "split.json" can't found in the right place. Is that something wrong with it the original code?

Thanks for your great job, I am work on federated leraning now. In your paper, in Table 2, the performance comparison of federated-by-camera scenario, federated-by-identity-scenario and local training. My confusion is:
Why the performance in federated-by-identity is better than that in local training on the CUHK03-NP but worse in Market-1501. I cannot found some anlysis in your paper.

How can I get Json File actually I need it for my research work. Kindly let me know if you can help me

https://github.com/cap-ntu/FedReID/blob/master/server.py#L45-L49

see I have N models.
the N-th model will not get fair weight, because the total_no_data is (model-0, model-N-1), which dominates.
pretty weird.

While running the command "python prepare_all_datasets.py" ,I met a bug that FileNotFoundError: [Errno 2] No such file or directory: 'data/cuhk02\meta.json''. And I can't find the file in the repository, could you please help me？ Thanks very much!

Hi!

The work on this article is really great! I hope to learn something from FedReID.

But when read the code, the function cdw_feature_distance is confusing. Although I know Python can do it, why calculate the mean of distance in for loop.

Here's what I think

         distance_lst = []
         for data in self.train_loader: 
             # do something
             distance = 1 - torch.cosine_similarity(old_out, new_out) 
             distance_lst.append(torch.mean(distance))
         return torch.mean(distance_lst)

Your reply will be greatly appreciated.

Hello,

The code is really clear and easy to read, thanks for sharing!

However, due to the dataset process is not based on the original version(the img name in meta.json is different at least) which makes it a bit hard to follow, I use different data loading processes implemented based on torchreid. And the result I achieve is lower than reported in the paper(around 10 percent on average). I just wonder if the data loading can result in the degradation of the performance.

Thanks for your reply,

hello,when I tried pip install -r requirements.txt
there is an error showed up








is there any ways to solve it ?

How do we generate log files for this and
In what format

I cannot find the split.json in small dataset, if i need to write a new one and how to do it?
Thanks

while running the command "python prepare_all_datasets.py" ,we met a bug that FileNotFoundError: [Errno 2] No such file or directory: 'data/3dpes/split.json'.Could you tell me how to solve the problem?

Hi,
Thank you for the great work,
How can we start a training on a single dataset in the federated-by-camera scenario ?
Regards

Hello.

Thank you for your wonderful paper and code work, and deeply express my admiration.

Recently, I am very interested in your work. However, I do not have the data set processed in the paper. Can you provide the application process of applying for preprocessed datasets? (the original application link has expired)

I use these datasets to run some comparative experiments and reproduce the work of this paper.

Hello, I am a graduate student implementing FedReID.
I already got zipped datasets, have a split.json from my colleague who already sent you a mail.

I am in a situation fail to implement main.py.

The reason is "FileNotFoundError: [Errno 2] No such file or directory: 'data/cuhk02/pytorch/train'".

I check that from the cuhk02.zip file, for cuhk02/pytorch, there was only the train_all folder and img.json.

Plese inform me the way how to create pytorch/train for the data/cuhk02.

Thanks.