jayqine / amr Goto Github PK

FileNotFoundError: [Errno 2] No such file or directory: 'sess/res50_cam.pth.pth'
FileNotFoundError: [Errno 2] No such file or directory: 'sess/res50_irn.pth.pth'

I also want to know the complete training steps, Thanks.

Hi author,

I run your code for about 10 days on 3090. and the result of eval_cam is only 0.428.
Is there anything wrong with my running command? I was running with "python run_sample.py --train_cam_pass True --train_amr_pass True --make_cam_pass True --eval_cam_pass True"

Cheers,
yuhao

Can you download the code from Github project and check out？

Maybe, this paper propose no new methods for WSSS. Your improvement is brought by cvpr2020 anti-adv method.

Hi, I have problem about that:
UserWarning: Using a non-full backward hook when the forward contains multiple autograd Nodes is deprecated and will be removed in future versions. This hook will be missing some grad_input. Please use register_full_backward_hook to get the documented behavior.

please help!

Could you explain why the code use flip operation in the lines 67 through 69? Several papers hava also used this operation.

cam2 = F.conv2d(x2, self.classifier2.weight)# 1*1 conv cam2 = F.relu(cam2) cam2 = cam2[0] + cam2[1].flip(-1)

Hello,
thanks for the great job!
I am confusing about the model provided. Is it generated from segmentation stage or classification phase？
Thank you!

hello,i wonder how get cam image after the step 'train cam'

Hello! Thanks for your great work!

I am confused about some lines in net/resnet50_amr.py. Did you mean that the spotlight branch is not supervised by classification? Is this equal to with torch.no_grad()?

Looking forward to your reply.

Hello, there was an exception occurred when I run eval script with command line python run_sample.py --make_cam_pass True --eval_cam_pass True.

TypeError: forward() got an unexpected keyword argument 'step'

The forward method of the class CAM seemingly did not support a parameter named step.

But the make_came step had provided it.

I'm wondering what's the effect of step, and what should I do for the code.

the cam making stage is too slow

I have encountered such an error：
Traceback (most recent call last):
File "run_sample.py", line 114, in
step.train_amr.run(args)
File "/home/stuc/zhx/AMR-main/step/train_amr.py", line 49, in run
train_dataset = voc12.dataloader.VOC12ClassificationDataset(args.train_list, voc12_root=args.voc12_root,
File "/home/stuc/zhx/AMR-main/voc12/dataloader.py", line 167, in init
super().init(img_name_list_path, voc12_root,
File "/home/stuc/zhx/AMR-main/voc12/dataloader.py", line 115, in init
self.img_name_list = load_img_name_list(img_name_list_path)
File "/home/stuc/zhx/AMR-main/voc12/dataloader.py", line 60, in load_img_name_list
img_name_list = np.loadtxt(dataset_path, dtype=np.int32)
File "/home/stuc/.conda/envs/amr/lib/python3.8/site-packages/numpy/lib/npyio.py", line 1308, in loadtxt
arr = _read(fname, dtype=dtype, comment=comment, delimiter=delimiter,
File "/home/stuc/.conda/envs/amr/lib/python3.8/site-packages/numpy/lib/npyio.py", line 979, in _read
arr = _load_from_filelike(
ValueError: could not convert string '2007_000032' to int32 at row 0, column 1.
Looking forward to your reply，thank you！！！！

Hello, I want to ask which segmentation code did you use to train the pseudo-label?