I'm working on my first model that detects bowling score screens, and I have it working with pictures no problem. But when it comes to video, I have a sizing issue.
I added my model to a small app I wrote for taking a picture of a Bowling Scoring Screen, where my model will frame the screens in the video feed from the camera. My model works, but my boxes are about 2/3 the size of the screens being detected. I don't understand the theory of the video stream the camera is feeding me. What I mean is that I don't want to make tweaks to the size of my rectangles by making them larger, and I'm not sure if the video feed is larger than what I'm detecting in code.
Questions I have are like is the video feed a certain resolution like 1980x something, or a much higher resolution in the 12 megapixel range?
On a static image of say 1920x something, My alignment is perfect.
AI says that it's my model training, that I'm training on square images but video is 16:9. Or that I'm producing 4:3 images in a 16:9 environment.
I'm missing something here but not sure what it is. I already wrote code to force it to fit, but reverted back to trying for a natural fit.
Topic:
Machine Learning & AI
SubTopic:
Core ML