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License: MIT License
How to determine the threshold of the discriminant network in the inference process
Thanks for the excellent work!
Can the authors provide pre-trained models on DAGM? I tried to train on DAGM according to the settings in the paper, but the final Image-level AUC was only 91%.
May I ask if the indicators imageAUROC, pixel AUROC, and pixel AP in your paper were tested with the same or different weights?
how do create --base_model_name of own data?
how do I predict image in own data?
how to inference images with the code?
Thank you
Hello
How do I generate a heatmap in test_DRAEM.py when I predict data?
Hello, I would like to ask you for advice. I want to change the program to two GPUs for parallel processing, but it has been unsuccessful. How can I solve it?
Hi, thanks for your great work,
I have a question about data processing,
In most of the implementations in the computer vision area with PyTorch, we will apply image normalization using std and mean,
I wonder why don't you apply normalization in the data preprocessing part?
The generated image in Figure 4 of the original paper does not correspond to the code in the data loader. The correct code should delete /255 in the 124th row of data_loader. I hope that the author corrects it to avoid more misleading.
Well sorry to interrupt u, but now i have a problem in making the environment. I have tried on Centos 7 and Ubuntu, using the latest Anaconda. There are like 30 or more packages which can not be installed. I have checked online for various kinds of methods, but no one make it through. I wonder maybe u can help me solve it, please.
Hi, could you possibly provide a docker file for easy library installation? The requirements.txt is causing countless dependency conflicts. Thank you.
The format of requirement is strange and can't be used as "pip install -r" or "conda create -n -f", may be a yaml file is more suitable?
I'll appreciate it if the available environment information provided.
Thanks a lot.
What is image_score
?
I don't understand what that means.
in test_DRAEM.py
(line 107)
Line 107 in 2dbf673
in addition, Can I get F1_score in test(evaluate)?
Hello, I use the checkpoints you offered in the google drive to test the MVTEC datasets , but cannot reproduce the results in the paper. There are large gaps in some classes, but the mean result is the same. The checkpoints you offered are final checkpoints or should be finetuned?Or maybe you made some other changes?
Here are my results
Hello.
I tried to run test_DREAM.py, but CUDA out of memory occur. (I use 15.90 GiB memory)
I don't know well about all of your codes, but when i check GPU memory, memory usage continue to increase.
I think some variables need to be allocated at CPU. (by using .cpu().detach())
After many attempts, I know where i need to change.
https://github.com/VitjanZ/DRAEM/blob/main/test_DRAEM.py#L96:L99
display_images[cnt_display] = gray_rec[0]
display_gt_images[cnt_display] = gray_batch[0]
display_out_masks[cnt_display] = t_mask[0]
display_in_masks[cnt_display] = true_mask[0]
display_images[cnt_display] = gray_rec[0].cpu().detach()
display_gt_images[cnt_display] = gray_batch[0].cpu().detach()
display_out_masks[cnt_display] = t_mask[0].cpu().detach()
display_in_masks[cnt_display] = true_mask[0].cpu().detach()
I want to train my own dataset, how can I get the file of the pre-trained model?
TypeError: Caught TypeError in DataLoader worker process 0.
TypeError: 'NoneType' object is not subscriptable
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