I am developing an iOS app that uses YOLOv8 for object detection and aims to detect objects at 60 FPS using the UltraWide camera. My goal is to process every frame within captureOutput and utilize the detected data (such as coordinates) for each one.
I have a question regarding how background thread processing behaves in this scenario. Does the size of the YOLO model (n, s, m, etc.) or the weight of the operations inside captureOutput affect the number of frames that can be successfully processed?
Specifically, I would like to know if all frames will be processed sequentially with a delay due to heavy processing in the background, or if some frames will be dropped and not processed at all. Any insights on how to handle this would be greatly appreciated.
Thank you!
Hello @keisan1231,
Generally speaking, if you are doing some processing in captureOutput, that processing should be faster than the frame rate you are capturing at, otherwise the video data output will start dropping new frames by default. The size of the model is very likely to be a factor in whether your processing can occur at the capture frame rate or not.
Best regards,
Greg
