lyn1874 / memae Goto Github PK

--------------PyTorch VERSION: 1.4.0
..............device cpu
The training path anomaly_data/Avenue/frames/training/
The testing path anomaly_data/Avenue/frames/testing/
--There is no other augmentation except resizing, grayscale and normalization--
['training/training_video_01', 'training/training_video_02', 'training/training_video_03', 'training/training_video_04', 'training/training_video_05', 'training/training_video_06', 'training/training_video_07', 'training/training_video_08', 'training/training_video_09', 'training/training_video_10', 'training/training_video_11', 'training/training_video_12', 'training/training_video_13', 'training/training_video_14', 'training/training_video_15', 'training/training_video_16']
['testing/testing_video_01', 'testing/testing_video_02', 'testing/testing_video_03', 'testing/testing_video_04', 'testing/testing_video_05', 'testing/testing_video_06', 'testing/testing_video_07', 'testing/testing_video_08', 'testing/testing_video_09', 'testing/testing_video_10', 'testing/testing_video_11', 'testing/testing_video_12', 'testing/testing_video_13', 'testing/testing_video_14', 'testing/testing_video_15', 'testing/testing_video_16', 'testing/testing_video_17', 'testing/testing_video_18', 'testing/testing_video_19', 'testing/testing_video_20', 'testing/testing_video_21']
Training data shape 1257
Validation data shape 1250
AutoEncoderCov3DMem

When I train the model with my custom data, the train memory sparse loss increases first and then decreases. could you tell me the reason?

Traceback (most recent call last):
File "E:/PythonProjects/memAE/Train.py", line 375, in
main()
File "E:/PythonProjects/memAE/Train.py", line 256, in main
shuffle=True, num_workers=args.num_workers, drop_last=True)
File "D:\DPFS\DeepLearning\anaconda3\envs\MemAE\lib\site-packages\torch\utils\data\dataloader.py", line 213, in init
sampler = RandomSampler(dataset)
File "D:\DPFS\DeepLearning\anaconda3\envs\MemAE\lib\site-packages\torch\utils\data\sampler.py", line 94, in init
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0

And I set shuffle=false;
then.....
0it [00:03, ?it/s]
Traceback (most recent call last):
File "E:/PythonProjects/memAE/Train.py", line 375, in
main()
File "E:/PythonProjects/memAE/Train.py", line 333, in main
train_writer.add_scalar("model/train-recons-loss", tr_re_loss / len(train_batch), epoch)
ZeroDivisionError: float division by zero

Hello, why does it display this after I load the data
len(train_dataset) = 0

$ ./run.sh
--------------PyTorch VERSION: 1.4.0
..............device cpu
File "E:\PythonProjects\memAE\data\utils.py", line 22, in init
self.videos, video_string = setup(self.dir, self.videos)
File "E:\PythonProjects\memAE\data\utils.py", line 89, in setup
video_string = sorted(video_string, key=lambda s:int(s.strip().split('')[-1]))
File "E:\PythonProjects\memAE\data\utils.py", line 89, in
video_string = sorted(video_string, key=lambda s:int(s.strip().split('')[-1]))
ValueError: invalid literal for int() with base 10: 'videos'

Could you tell me how i can deal with it?

I train the models with your codes on UCSD Ped2 dataset, but I cannot get the report results.

How to visualize the experimental results, as shown in the figure below

use the .mat files?

Hi, I have test you code and found you memory loss weight is 0, when I attempt to set thie weight to 0.0002, I found the att_weight tend to all zero(under threshold）or only a same one memory item's weight is 1 for different input.This is clearly a training problem and the AUC is poor.Do you have any comment on that, is it a problem with the original paper?

hello, thank you for your work. Can you share the pretrained model of UCSD Ped2?

--------------PyTorch VERSION: 1.7.0+cu101
..............device cpu
Traceback (most recent call last):
File "/content/memAE-2/Train.py", line 76, in
args.dataset_augment_test_type)
File "/content/memAE-2/data/utils.py", line 148, in give_data_folder
return train_folder, test_folder
UnboundLocalError: local variable 'train_folder' referenced before assignment

Thanks your work!
Did your code work well on shanghaitech?
or if you have the trained model about avenue or Shanghaitech datasets .
and could you please send me the models ,my email is : [email protected]
thanks again

Traceback (most recent call last):
File "D:/python/pycharm/memAE-master/Train.py", line 81, in
train_dataset = data_utils.DataLoader(train_folder, frame_trans, time_step=args.t_length - 1, num_pred=1)
File "D:\python\pycharm\memAE-master\data\utils.py", line 22, in init
self.videos, video_string = setup(self.dir, self.videos)
File "D:\python\pycharm\memAE-master\data\utils.py", line 89, in setup
video_string = sorted(video_string, key=lambda s:int(s.strip().split('')[-1]))
File "D:\python\pycharm\memAE-master\data\utils.py", line 89, in
video_string = sorted(video_string, key=lambda s:int(s.strip().split('')[-1]))
ValueError: invalid literal for int() with base 10: 'training/01.avi'

Where can I get vidio data

in author's paper

in my results

and note: I used the pretrained model in ckpt(model-40.pt)

Hi! I wonder if I could train and test your model on pictures. My task is industrial defect detection.