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ChristianEschen avatar ChristianEschen commented on May 27, 2024 1

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ChristianEschen avatar ChristianEschen commented on May 27, 2024

Hi.
First of all. I am not the owner of the code. But I have faced the same issue.
I think the work around is change the sum metric to dice score (f1). I have not managed to make it work jet.

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MStumpp avatar MStumpp commented on May 27, 2024

Hi Christian, can you reference the location in the code that you recommend to change and optionally how you recommend to change it (even if its not working right now)?

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ChristianEschen avatar ChristianEschen commented on May 27, 2024

Line 456 in voc.py defines the metric function "_get_metric()"
Currently, it uses a custem metric function "CustomMetric" defined in line 336-346 in voc.py
The F1 metric function is suitable for the case of binary segmentation. (https://github.com/dmlc/mxnet/blob/master/python/mxnet/metric.py)
The metric function should be changed to this. Alternatively, one could change to a log likelihood cost function with a greater weight class 1.

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MStumpp avatar MStumpp commented on May 27, 2024

@ChristianEschen cool i will give it a try later the day. You said "I have not managed to make it work jet." => Does it mean you didn't get the metric replaced (= programming issue) or did the training not converge (= training issue)?

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ChristianEschen avatar ChristianEschen commented on May 27, 2024

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