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To achieve the mAP of 77.8, which is claimed in README, how to set hyper-parameters for FSSD? Or just use the default values in train_test.py?
The README also mentioned that there is a train_RFB.py which lists parameters for RFB training, but I did not find such a script in this repo
The text was updated successfully, but these errors were encountered:
The hyper-parameter of FSSD 300 is the same with RFB300 except that the learning rate is 0.001
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And the parameters for RFB300 are the default values in train_test.py? I didn't find the train_RFB.py mentioned in Readme file.
You are right, I merged the train-RFB.py and test-RFB.py into train_test.py
Thanks!
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To achieve the mAP of 77.8, which is claimed in README, how to set hyper-parameters for FSSD? Or just use the default values in train_test.py?
The README also mentioned that there is a train_RFB.py which lists parameters for RFB training, but I did not find such a script in this repo
The text was updated successfully, but these errors were encountered: