Accomplishment: I have flushed out an algorithm for the post-processing of data from the OR module, which will then be redirected to the speech module. In each iteration of the OR module’s output, it will provide me with an array of all the objects (by name) identified in the frame under a specific distance threshold (2m). Along with the object’s name, there will be a confidence score and the distance measured attached to the data point. In the post-processing program, I will filter all the identified object from closest to furthest and the closest object will be reported to the user (by means of the speech module) should it pass our confidence score test (ie. confidence > 0.8). I also have created an interim method to store the past 10s of history in an array that will get referenced should the object not pass the confidence score test. However, all of this is subject to change based on the performance of the OR module that Josh is still working on. Furthermore, as we have decided to upgrade to Yolov9 we expect to have improved performance in the OR model.
Progress: I think I am relatively on track. I have decided to hold off on writing out the speech module as the post-processing of the data from the OR module precedes the speech module in the overall data flow.
Projected Deliverables: This coming week I will be working on solidifying the post-processing code and hopefully have some testing done on dummy data.