A0 – AutoPuzzlr

Check out this video to see how our project came out!

Thanks for watching!

This week we have been working together on the final features of our project and the final presentation slides as well. The finger detection portion is largely complete, so I have been working on UI features and the presentation slides.

This week I worked on smoothing out the “loading” animation by averaging the tracked points to minimize the natural jitter of the user’s finger. I also worked on the outward-facing API to embed into Connor’s UI. We also worked together to integrate the individual pieces together for our demo.

This week I worked 2 goals: creating a tap & tap loading animation in OpenCV and making the API for the finger detection more friendly for Connor’s UI. The first goal has gone smoothly, although there is some jitter in the animation due to small fluctuations in the recognized fingertip position. I will be working to improve this in the following week and have a couple ideas – taking a set point to base the animation around at the start and ignoring shifts, or taking a running weighted average to minimize jitter but maintain more animation-accuracy. In regard to the second goal, I spent a lot of time reading about both OOP in Python, as I have not explicitly used Python to create and interact with user-defined classes before. I have also been doing research into how the webcam feed + OpenCV overlays can be integrated into a PyGame interface to inform my decisions about the API. Mainly, I broke what was previously a main-function loop to demonstrate and visualize the performance of the finger detection into a few different functions that represent individual “transactions” with the system (request/response for tap, initialization/calibration). This coming week I will continue to learn about OOP patterns in Python and refactor the code to create and access the module as an object within a orchestrator back-end.