Tjun Jet’s Status Report for February 10, 2024
This week I mainly focused on setting up a Flask Server to stream our edge detection algorithm and also research on physics simulation methods to predict the trajectory of cue ball collisions.
The intent of using a Flask Server is because we want to be able to wirelessly communicate between our cameras and projectors. In order to do this, we will have to send a byte stream of data into our computer and output the image. The reason for this is to show the actual live stream of the camera feed into our web application, and also, it will help us with debugging when we are able to view the images on our computer. I successfully managed to set up the server to stream wirelessly between different computers, and the video feed looks very smooth when streamed wirelessly, with almost no lags.
In terms of physics simulations, I reference an online Git package called PoolTool: https://github.com/ekiefl/pooltool. There are some good resources on calculations of ball trajectories which I hope to take reference from and replicate for our use case. Once we are able to do so, it will be a good segway to integrate between the object detection algorithms and the physics trajectories.
I am currently on schedule and accomplished whatever I wanted to accomplish this week. Next week, I aim to actually implement the physics trajectory calculations on code. I am intending to pass in hard coded coordinates of circles to represent pool balls, as well as a hardcoded line that intersects with the cue ball. If we manage to get the object detection done, I want to use the object detection predictions as input to the algorithm, and see if we can get a real-time prediction of the physics trajectory. If that is not possible, I hope to be able to plot drawings of those images and see if I can output the trajectory.