Question on the confidence level. How does DeepStack / BI decide what to burn into the image and the final "confidence level"?
Example below, "dark model" found People @ 75% and "objects" model found person @ 44%, yet only labeled image with "person:44%".
I would have thought that the HIGHEST confidence level object would "win" and be the one burned into the image. Not that this example would really make a difference, but it could depending on the objects. If it is 55% chance it is a dog and 95% change is it s bear, I want to know "BEAR"!
It would be nice it could have a new &MACRO of something like &SUMMARY (or something more clever maybe). Let &JSON give you everything (great for troubleshooting) and then &SUMMARY be JUST the object label that had the greatest confidence level (above your set threshold of course).
FYI, no idea where it found a chair going up my stairs in the example below!
[{"api":"objects","found":{"success":true,"predictions":
[{"confidence":0.4422658,"label":"person","y_min":1219,"x_min":33,"y_max":2302,"x_max":998},
{"confidence":0.5098691,"label":"chair","y_min":1525,"x_min":5,"y_max":2304,"x_max":1001}]}},
{"api":"faces","found":{"success":true,"predictions":[]}},
{"api":"dark","found":{"success":true,"predictions":[{"confidence":0.7568857,"label":"People","y_min":1196,"x_min":27,"y_max":2300,"x_max":978}]}}]
Example below, "dark model" found People @ 75% and "objects" model found person @ 44%, yet only labeled image with "person:44%".
I would have thought that the HIGHEST confidence level object would "win" and be the one burned into the image. Not that this example would really make a difference, but it could depending on the objects. If it is 55% chance it is a dog and 95% change is it s bear, I want to know "BEAR"!
It would be nice it could have a new &MACRO of something like &SUMMARY (or something more clever maybe). Let &JSON give you everything (great for troubleshooting) and then &SUMMARY be JUST the object label that had the greatest confidence level (above your set threshold of course).
FYI, no idea where it found a chair going up my stairs in the example below!
[{"api":"objects","found":{"success":true,"predictions":
[{"confidence":0.4422658,"label":"person","y_min":1219,"x_min":33,"y_max":2302,"x_max":998},
{"confidence":0.5098691,"label":"chair","y_min":1525,"x_min":5,"y_max":2304,"x_max":1001}]}},
{"api":"faces","found":{"success":true,"predictions":[]}},
{"api":"dark","found":{"success":true,"predictions":[{"confidence":0.7568857,"label":"People","y_min":1196,"x_min":27,"y_max":2300,"x_max":978}]}}]
