facebookresearch / Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
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The architecture of Retina and batchnorm moving variance and moving mean #995

Open phamquandung opened 4 years ago

phamquandung commented 4 years ago

Dear all,

I hope that everyone stays safe!

Since this is the first time I tried on detectron, I am familiar with this framework. I would like to have 2 questions. Please help me.

  1. After downloading the pre-trained model of RetinaNet baselines R-50-FPN (https://github.com/facebookresearch/Detectron/blob/master/MODEL_ZOO.md), I extracted the weight layer by layer and I got the data like below figures. However, I do not know where these layer in Retina Net. How can I know the architecture of RetinaNet?

  2. In these data, I realized that there are bn_s and bn_b, I guess that they are batch norm. Are they variance and mean?

Thank you for your time and consideration.

Screen Shot 2020-05-09 at 10 40 44 PM Screen Shot 2020-05-09 at 10 41 12 PM