About text_probs.

[boringKey]

Hello, thank you for your contribution to anomaly detection in the zero-shot learning domain. However, I have a question that I found in the code and I hope you can explain it. During the zero-shot process, when processing normal images, as shown in line 169 of the test.py file, text_probs[0][1] is still being used to represent semantic information. According to my understanding, text_probs[0][0] should represent the semantic information of normal images, while text_probs[0][1] should represent the semantic information of abnormal images. Therefore, when processing normal images, should the code be changed to text_probs[0][0]? Thank you very much!

[ByChelsea]

Hi, for both normal and abnormal images, text_probs[0][1] represents the probability of the image being classified as abnormal. For abnormal images, this value is relatively high, while for normal images, this value is relatively low.