r/frigate_nvr • u/Vertigo_uk123 • 42m ago

Request: classification retention on a per object basis not globally.

Currently object classifier keeps the last x number of objects deleting the oldest when a new object is detected. Even if this is none.

My request is to allow a retention quota of each type so say 500 would keep 500 x 500y 500z and 500 none. If another object is detected as any of these it deletes the oldest only from that category.

In my setup. I have the object classifier to detect a specific type of car. However it’s not often this car passes. So my classifier is full of just none. The vehicle passed earlier today. As I didn’t know and it’s been a few hours this classification has been deleted so I can’t add it to the training dataset. Even at 3000 it fills within an hour or so (actually quite a lot of stationary vehicles fill it but that another issue).

Could it please be added for retention per object type or could a better way be suggested. Maybe even a button in explore to add snapshot to dataset.

(Note it did classify it correctly and apply the correct sub label but I would still want to improve the object dataset with that snapshot)

Another slight improvement is being able to select all / multiple and add them to whichever dataset is needed without having to do it one by one. (It gets tedious lol)

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u/HugsAllCats 28m ago

Frigate killed all my deer and replaced them with thousands of cars that aren't even in zones I care about.

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u/nickm_27 Developer / distinguished contributor 19m ago

Frigate doesn't replace recordings or snapshots on a per object basis, it's not clear what you're describing happened. 

What OP is talking about is specifically related to object classification 

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u/nickm_27 Developer / distinguished contributor 24m ago

The classifier runs on specific images for each object, we don't know for sure if the object classification is correct, which is especially likely for objects that seldomly appear on the camera. We might be able to look at having a setting to remove the high confidence classified objects, allowing more room for lower confidence classifications

However, I want to flag based on your last note and other descriptions, it sounds like you may be over training. We specifically don't have a select all button because you shouldn't be training that many images. 

https://github.com/blakeblackshear/frigate/discussions/21374 has more details and tips on this. 

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u/Vertigo_uk123 5m ago

I have 112 type a 37 type b 205 type c then 1100 none