Comments (5)
Hi, there.
I don't want to guess what exactly do you mean, could you please describe your issue according to the template here:
#20
Otherwise, the issue will be marked Closed.
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Hi, there.
I don't want to guess what exactly do you mean, could you please describe your issue according to the template here:
#20
Otherwise, the issue will be marked Closed.
the multi labels mAp calculate is not exactly
from axelerate.
from axelerate.
Why the multi labels mAp is so low? but train single label mAp is high.
from axelerate.
Describe the bug
Users are not using template, which causes a waste of time - additional information is needed to be asked by contributors to find the source of the problem.
To Reproduce
Steps to reproduce the behavior:
Go to 'Issues'
Click on 'closed'
Scroll down to 'everywhere'
See all issues without templates - people are creating issues and asking "what is wrong, it doesn't work" without explaining what is the bug and what is expected behavior
Expected behavior
A clear and concise description of what you expected to happen when you run the code, what is your dataset, what is the error output in the terminal. Ideally, create a colab notebook to reproduce the error and share it here.
Screenshots
If applicable, add screenshots to help explain your problem.
Environment (please complete the following information):
Local or Google Colab/Jupyter Notebook
If Local: conda or native install/ virtual env?
If Google Colab: tensorflow version?
Additional context
Add any other context about the problem here.
from axelerate.
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