"[BUG]: NaN metric values"

[FatemehEsfahani]

Describe the bug
When a class does not show up in a batch, the corresponding row in the confusing matrix becomes zero. As a result, division by zero happens and performance metrics for that class becomes NaN.

geo-deep-learning/utils/metrics.py

Line 130 in 8c8250c

# Calculate metrics from the confusion matrix:

To Reproduce
Steps to reproduce the behavior:

1. Test with an image whose label has 3 classes including background class (i.e. class_0, class_1, class_2) in which only class_0 and class_1 are available.

Expected behavior
The metric calculation should handle division by zero and set a value (i.e., 0) when a class is absent.

Screenshots
Example of the confusion matrix for a batch:

Then, the metrics for class_2, based on the following formula becomes NaN:

Additional context
Small epsilon value can be added in the denominator of each metric calculation formua to avoid devision by zero. Something like the following: