Last week I was preparing for the interim demo by displaying the preliminary matching algorithm through tkinter. This isn’t the final matching algorithm since we hope that the ML model Devon is training and working on integrating will be what will be using for the final matching algorithm. The preliminary algorithm takes in the two key point jsons OpenPose generates of the user and the clothing image. These are normalized as a value of 0 to 1 based on the x, y ratio in comparison to the entire image. The center points are matched and the points are created and the clothing image is rendered on top of the user with PIL to register PNG transparency. I’ve attached a picture of the results below. As you can see, it’s not perfect at all. So this week I’ve been working on finding what’s wrong with the normalization process I go through, since visually comparing the jsons, we’re getting a pretty accurate center point position. I’m still working on this, but I suspect it’s because the ratios are calculated from different sizes of picture. I’m not what the right way to go about correcting this is, but probably doing some more math on normalizing the size ratios.
