Metrics for object detection with bounding boxes
🚀 Feature
We could add a whole bunch of metrics for object detection (bounding boxes) by just writing a plugin that transforms the bounding boxes to multi-class label tensor representation.
Motivation & Pitch
Metrics for bounding box detection are basically just classification metrics (see here for example) - the only difference is that the inputs come as bounding boxes which then have to be interpreted as class predictions.
If we write a plugin for this "interpretation" part - and I don't even think this would be that hard - we can just plug it into the classification metrics that we already have, and voila, we suddenly cover all object detection metrics!
I think it would still be good idea to create separate classes for these metrics (ObjectDetectionAveragePrecision or something?), but on the inside they would be a simple call to the transformation plugin + usual classification metrics.
If people think this is a good idea, I am willing to create this transformation plug-in and then slowly add these metrics :)