akshitac8 / generative_mlzsl Goto Github PK

HI
To build jason files and extract features myself i am trying to upload data but when i run pre process files then cpu hangs. Any guideline for this issue

Hello

Hope you are doing well. I have read your article named " Generative Multi-Label Zero shot Learning" and find it interesting. I have also checked its GitHub repository and get a deep understanding of your proposed model. In your repository you have share the whole process for custom dataset downloading as well as the process of preprocessing and features extraction. I need your help in one thing as I have limited resources available and downloading the "Open Images " and "MS COCO " dataset on my system is impossible for me because of my limited internet speed and storage limit. If you can provide me the google drive link as you have shared for NUS-WIDE dataset with nus_gzsl__test_vgg19.h5,nus_seen_train_vgg19.h5 and nus_zsl__test_vgg19.h5. If you can share the same for "MS COCO" and "Open Images" as you have also performed experiments on this so this sort of pre-processed dataset you would have. It would be a great help for me as my work deadline is already near and because of limited resources I have I wouldn't be able to complete it, If I have no access to it. Please help me in this

Dear author, thanks for your code.But when I reproduced this code, I found that the memory kept increasing, and finally caused the training failure of running out of memory.What is the possible reason?

Thank you for the wonderful codebase. However, the google drive link for getting the shared folders is not working and seems to have expired. I was struggling a bit with the word embeddings file essentially.

The NUS_WIDE_pretrained_w2v_glove-wiki-gigaword-300

Thanks for your work! could you please provide a link for downloading relevant datasets?

I run train_nus_wide on a single 1080Ti, but it returns CUDA out of memory.

First of all, thanks for this repo. I have managed to train and evaluate successfully and am seeing some nice performance figures.

I now have a query regarding the production of some qualitative results, similar to those at (https://github.com/nasir6/zero_shot_detection#qualitative-results). I see these are featured in your paper:

I have tried manually reproducing these by opening up the model but as I see you have already produced some, I thought it was worth asking if code already exists to do this. I would be grateful if you could provide a link if it does, this would really help my research and demonstration of results for my academic report. Thanks in advance and apologies for all of these queries.

Hi
Thank you for the code. For a standard multi-label recognition dataset on the nuswide dataset, how to divide the training sample and the test sample.

anyone else having issues accessing the datasets? Thank you

Hi,

First of all, thanks for the project, it's really cool. In trying to reproduce the results, I have so far been able to find all other required files except the NUS_WIDE_pretrained_w2v_glove-wiki-gigaword-300 dataset. I have reproduced it but I believe it is in the wrong format. If someone could provide me with a link to the file or steps to reproduce it, I would be massively grateful.

Cheers

link: https://drive.google.com/file/d/1LaCDkLY4XnkB5901OwRTdjOxCRvtDbfP/view?usp=sharing

I am trying this but its not working please resolve if possible

1. The dataset argument given in eval.py is not defined.
2. The HYBRID FUSION SELF ATTENTION module is not defined in file you need to change it to CLF.
3. When i run the code using given pre-trained weights the accuracies are very low
4. Without pre trained wieghts accuracies are in range of mAp 20 for zsl

Thanks for code. How could i fix this problem? I also tried to reduce the number of batch size to 32 and 16 but the issue is the same.

Hi , i was wondering why the values of above mentioned extracted features are exactly similar in shape and values, Can you please verify from your training data in g drive please.

Hi, I have run the code and now i am looking forward to reproduce the classification as well as detection results , Can you provide me access to code for classification results plotting as well as detection part. Also how to test it separately for only ALF scheme or FLF scheme without CLF .Thanks alot

Hello!
I was using your 'extract_4095_features.py' binary when I realized that the 'get_extract_data' function is not imported or defined. could you please provide implementation or import for this function?