Open akasrawa opened 3 years ago
Did you try out the step 5 in the README? That should help you out
Thanks dear for your replay.
I added one normal image in positive image folder and run the test , its come with below error. is there something wrong or mean the image is normal image.
confusion matrix (test / validation) true positive: 0 false positive: 0 true negative: 0 false negative: 4
accuracy: 0.0000 %
Traceback (most recent call last):
File "test.py", line 66, in
You have 4 false negative, that means the images which were taken from screen were incorrectly classified as normal. You would need to train you model using better datasets and use more test data for validation.
To understand the formula for which you got an error, read this: https://towardsdatascience.com/accuracy-precision-recall-or-f1-331fb37c5cb9
@akasrawa hello, did you test single image success? and can you share your tensorflow and keras version? thanks
@akasrawa hello, did you test single image success? and can you share your tensorflow and keras version? thanks
guys (@akasrawa , @tkone2018 ) anyone of you had a success implementing this.. i am trying to test a sole image but even the test(referenced in readme) is not working.. i am getting..
ValueError: Cannot assign value to variable ' dense_1/kernel:0': Shape mismatch.The variable shape (32, 2), and the assigned value shape (32, 1) are incompatible.
@amilkcar I get the same issue! did you manage to resolve it ?
May be this issue can help you.
https://github.com/AmadeusITGroup/Moire-Pattern-Detection/issues/27#issue-1518171464
@amilkcar @MarouaneSH
I did training and got dataset .h5 How i can predict for single/multi image to get result as positive(0) or negative(1).
please support to share/add the file for prediction image.
thanks in advance