LLMs like GPT-4o have some pretty impressive image performance. It can actually pick up some of the more obvious defects on our buckets (Steph tested it out just now).
Two problems though with the OpenAI approach:
1. You'd need a cloud connection to send those images up to and get the answer back down so that's cost in terms of your round-trip latency, network infra, and the OpenAI account itself.
2. It doesn't do well with the very subtle defects - mild shape changes, loss of features from short shots, etc
It might be worth using in the offline pipeline for auto labeling though!
Two problems though with the OpenAI approach: 1. You'd need a cloud connection to send those images up to and get the answer back down so that's cost in terms of your round-trip latency, network infra, and the OpenAI account itself.
2. It doesn't do well with the very subtle defects - mild shape changes, loss of features from short shots, etc
It might be worth using in the offline pipeline for auto labeling though!