Open Santana18 opened 6 years ago
Hello, Thanks for your interesting of this repository. In my experiments I took sizes of (128, 128) and (64, 64) for the input. The configuration could be customized for the specific image size and filters of the autoencoder. I used the basic autoencoder(the auther did as well) to do the anomaly detection and it looks like good for my case. However, the encoded vectors seem to contribute less to the anomaly detection. In other words, I found the key factor is still the reconstruction error in my cases. The estimated GMM did help to predict the distribution, therefore having a robust result of anomaly detection.
Are modifications necessary for larger camera images? Does your code expect any multiples of image sizes?
The network worked well for you, according to the paper content?
Thanks for your implementation and the good readme.