Merging two separate models/datasets after training

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Please can you help me understand a fundamental of design. Let’s say that I train two seperate
detection models, “stamps” and “coins” and that both models are working great.

And now say that I’d like to detect both stamps and coins from a single video feed. How should I approach this problem? Can I somehow merge the two models? Or should I try to merge the two annotation sets, and then retrain?

A problem that I have with the datasets is that the original “stamps” training images contain unannotated coins. And the “coins” training images contain “stamps”.

2

I believe you can use a workflow to label both stamps and coins in a video. If your dataset is bad and then your model isn’t working properly then I believe you will have to retrain the model but I’m not sure about the last part.

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