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View Code? Open in Web Editor NEWUnsupervised anomaly detection with generative model, keras implementation
Unsupervised anomaly detection with generative model, keras implementation
OSError: Unable to create file (unable to open file: name = 'weights/generator.h5', errno = 2, error message = 'No such file or directory', flags = 13, o_flags = 302)
Hi,
Thans for your work. I have a question about after train progress. When we send abnoamal image to the model, it can only give a abnomal score, but how can we make sure model classify this image as nomal or abnomal? And I noticed in paper, there are some evaluation index for model ,such as precision,recall,AUC and so on ,how to realize this fuction?
Thanks again for your kind reply.
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'batch_normalization_1/keras_learning_phase' with dtype bool
또 질문 드리네요..
anomaly 이미지를 생성했고 이에 대한 score 를 봤는데요..
anomaly 이미지에서 어떤 부분이 anomaly score 에 높게 반영 되는지 알고 싶습니다.
파란색 부분?? 빨간색 부분?? 아님 다른 곳??
감사합니다..
├── main.py
├── anogan.py
├── weights
├── discriminator.h5
└── generator.h5
└── result
└── save the generated images when training
However, there is no folder of "weights"
Why are we using 'mse' as the loss function for both generator and discrimator? Do we not use 'binary_crossentropy' in case of the optimizers?
Also another doubt was to know the reason behind the usage of Conv2dTranspose layers instead of Upsampling layers?
안녕하세요..
올려주신 소스코드는 잘 동작하는 것을 봤습니다.
몇가지 질문 드리고 싶습니다.
감사합니다.
hello,Is the envrionment of your computer gpu? And i want to know is the code suited the cpu.Thanks for your reply
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