Can you go into any detail on what technologies you used? Is there enough differentiating data in their attire to actually match agents? None of them are showing their faces so I wonder how many false positives would occur
I'm using a YOLO-WORLD-XL object detection model. Lets me detect objects using text. This is the initial filter that scans for agents - once those are detected and outlined with bounding boxes the entire image and each cropped bounding box are then sent to chatgpt to confirm if the image looks legit. Once image passes those checks - I create image embeddings of each agent using CLIP and those are stored in a vector DB, and each agent is then compared to the DB and matched.
The matching system isn't perfect - but I think good enough to get the point across and can be easily tuned with more data! Happy to take suggestions here - I just spun this up over the weekend
Ignore them? Operate outside of US reach. The tubes are global.
EDIT: Legally, you have no right to privacy in public, if your photo is captured in public (US centric), broadly speaking. You have the right to record law enforcement officers exercising their official duties in public.
So avoid being subject to the US jurisdiction, if applicable. Do not store data or operate the system from within the US, or any country within US reach.
Can you go into any detail on what technologies you used? Is there enough differentiating data in their attire to actually match agents? None of them are showing their faces so I wonder how many false positives would occur