PyHa BirdNET and TweetyNET refactor local_score_visualization() adjustment
JacobGlennAyers opened this issue · 2 comments
The way that the local_score_visualization() function currently works, is that if the user desires to display automated annotations, they can set a flag true, and it will automatically call the Microfaune hybrid CNN-RNN model, and place it in a figure above a spectrogram and then display the automated annotations in yellow over the spectrogram. Since BirdNET doesn't have a local score array output being a CNN, I believe we need to refactor local_score_visualization() in a way that a user passes two dataframes of the automated annotations and the manual annotations of a desired clip, and it generates what is needed.
I am thinking that the local score array visualization is something that we may not need anymore, though it might be useful leaving it in as some legacy code that isn't on display for our personal niche use-cases. Or maybe I am just afraid of getting rid of some of the oldest code on this project (from Summer 2020)
I believe that we should add in an option to output with the microfaune local score arrays, but by default it shouldn't do this. This means that this should take in an automated, manual, or both kinds of inputs. At the end of the day it should just be our custom spectrogram function, that can display highlights of where annotations exist if we so desire.
Handled by changing local_score_visualization() to spectrogram_visualization() in the birdnet_integration branch merge