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The Threshold Problem of GMM

Open joeyslv opened this issue 2 years ago • 2 comments

After carefully reading the article 3.4 Temporary consistency using Gaussian Mixture Model (GMM) You use a Gaussian mixture distribution for each category. Each mixture distribution contains a positive and negative Gaussian distribution. It is also a posterior probability probability of EM algorithm inference for each category. However, in model training, the Log log only has a single GMM threshold, and ultimately GMM generates a category threshold or a unified threshold Looking forward to your answer Thank you.

joeyslv avatar May 29 '23 07:05 joeyslv

Hi, Thanks for your interest. Only the mean gmm_thr value for all categories is logged to be printed out. Bounding boxes are filtered with a per-class threshold during training. Please refer to code https://github.com/Adamdad/ConsistentTeacher/blob/b49a9ce1c0ae78d13528be0a9a4eff65a627d581/ssod/models/consistent_teacher.py#LL335C25-L335C25 for details.

Johnson-Wang avatar May 29 '23 07:05 Johnson-Wang

Hi, Thanks for your interest. Only the mean gmm_thr value for all categories is logged to be printed out. Bounding boxes are filtered with a per-class threshold during training. Please refer to code https://github.com/Adamdad/ConsistentTeacher/blob/b49a9ce1c0ae78d13528be0a9a4eff65a627d581/ssod/models/consistent_teacher.py#LL335C25-L335C25 for details.

Thank you for your answer. Let me take a closer look at this code

joeyslv avatar May 29 '23 07:05 joeyslv