Open andreipopovici opened 4 months ago
Unfortunately I've hardcoded the failure thresholds in the automation calculations. It is possible to replace the hardcoded values with an input but need to go over the whole calculation functions.
I ported the following calculation functions to the HA blueprint. You can go over these functions and update the blueprint: https://github.com/TheSpaghettiDetective/obico-server/blob/496605a62fcb790097c510c151994e9b2bf020c1/backend/lib/prediction.py
Thank you! I'll observe the normalized p
values for a while to get a sense of why it's so sensitive.
To that end, I've added a warn
mode that bypasses the pause/stop button presses: https://github.com/andreipopovici/ha-bambu-lab-p1-spaghetti-detection/blob/main/blueprints/spaghetti_detection.yaml#L50
@andreipopovici thanks, the warn feature is useful for me.
Hi there,
I'm trying to fine-tune and make the detection less sensitive. I see there's a
THRESH
constant of 0.08 in the Obico MLserver.py
, then there are a couple threshold-related number inputs in the HA integration, but those get set to something by the blueprint. I was under the mistaken assumption that we could set those inputs to our preferred values.Is there a combination of changes I could make to achieve my goal?
Could you elaborate on how the server's
THRESH
constant relates to the return values from the ML server? Thank you!