Jimmy’s Status Report 10/26

Accomplishments

Following this week’s meeting, a big issue was raised on which camera angle would work best to get accurate data information for making predictions. As such, this week was mainly getting the custom YOLO model to run inference on the camera, since the pre-built recognition models are not robust enough for our applications. I successfully compiled the detection model onto the camera from the .pt weight file to ONNX and then to a BLOB format. I was also able to get some depth data output by looking at the examples in the Luxonis documentation. 

Schedule and deliverables

I have caught up to schedule by making a lot of progress on the camera API area. More work needes to be done on the algorithmic side for the Kalman filter though. Since integration of the kalman filter and camera system is still in the works, I can work on the two components independently by making up some simulated points in space and time to use in the kalman filter, whilst working on the point generation on the camera side at the same time.

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