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https://issues.apache.org/jira/browse/CAMEL-20895?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Tadayoshi Sato reassigned CAMEL-20895:
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Assignee: Tadayoshi Sato
> camel-djl - The image classification predictors should not round the resulted
> probabilities
> -------------------------------------------------------------------------------------------
>
> Key: CAMEL-20895
> URL: https://issues.apache.org/jira/browse/CAMEL-20895
> Project: Camel
> Issue Type: Improvement
> Components: camel-ai
> Affects Versions: 4.6.0
> Reporter: Tadayoshi Sato
> Assignee: Tadayoshi Sato
> Priority: Major
>
> Currently, both {{ZooImageClassificationPredictor}} and
> {{CustomImageClassificationPredictor}} transform the resulted
> {{Classifications}} objects into maps of {{Map<String, Float>}}. However, the
> data type of {{Classifications}} is a map from the class name to probability
> with {{String -> Double}}, thus the precision is lost in the mapping.
> It doesn't seem to be a good transformation in the following points:
> - Sometimes rounding from double to float loses not only precision but also
> accuracy of the value
> - The [Softmax|https://en.wikipedia.org/wiki/Softmax_function] function used
> in the classification problems expects the probabilities to sum up to
> {{1.0}}, but due to the loss of accuracy above the premise seems to be broken
> to a large extent.
> - Finally, probably it's just better to simply return the {{Classifications}}
> object rather than converting it to a {{Map}} because the class already
> provides useful methods such as {{best()}}, {{topK()}}, etc. so that
> downstream components can easily extract the conclusions from the output out
> of the box; if we just provide it as a map, downstream is required to craft
> some manual calculations upon the result every time.
> In conclusion, I think it's better for {{ZooImageClassificationPredictor}}
> and {{CustomImageClassificationPredictor}} to simply return the output as
> {{Classifications}}.
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