This week, I used new training and testing datasets to fine-tune the YOLO model that we previously used for our interim demo. The new model looks for an added set of features in order to reduce the amount of OCR passes needed on each image, subsequently reducing our latency. I ran a few standard tests in order to verify the functionality of this new model, and found a slight drop in accuracy, which I am currently working to reduce. In the coming week, I plan to build new custom test datasets in order to properly identify these points of error.
Krrish’s Status Report 04/12
I assembled the cameras and raspberry pi into it’s 3d printed housing. I have stereo depth working and am now integrating with the YOLO model. I’m having trouble getting the model to compile so it can run on the accelerator. I need to install a lot of drivers on an x86 machine which is proving difficult as I don’t have one and need to go to campus. The software is also prone to a lot of issues which I am in the process of figuring out