This week I presented our group’s initial proposal presentation. The presentation went well, and I received many thought-provoking questions that have helped me realize that there were some aspects to our design that we have not considered, such as intersections that have multiple sidewalks. I began searching for suitable models that we can use to create our walk sign image classification model. One of these is an off-the-shelf YOLOv8 model that we can simply fine tune on walk sign images. Another potential solution I found is to gather as many images of walk signs as possible, as a combination of existing online datasets and self-taken images, and upload them to Edge Impulse. Then I can use Edge Impulse’s image classification model, which would be great for our project since Edge Impulse has a feature that lets you create quantized models, which use smaller data types for storing parameters and reduces the total memory required.
Progress is still on schedule. We allocated ourselves a large chunk of time for researching and making the model, and I believe that picking a suitable model at the beginning will help save time tuning and testing later. Next week I hope to be able to start the training and initial testing against validation datasets. This will give ample time for iteration if further improvements are required, which is very likely.