Cooper Weaver Status Report 8

Last week I trained and setup the endpoint for the workout classifier. This was the second batch of training that I had done, and it surpassed the metric that we had set for our classifier accuracy based on the training set of 200 images that I setup. It completed with ~95% accuracy on the dataset. This metric seems about right, as the same algorithm has been used on more complicated datasets with accuracy in the range of 92-97%. That being said there is still a decent potential that the classifier has been overtrained because I have a slightly smaller, less robust dataset so we will be tracking the accuracy of the classifier moving forward to look out for that. I have additional ideas to increase the classifier accuracy and limit overtraining that I’m prepared to implement but as we passed our metric point I’ve put those ideas on the back-burner and moved on.

Next I had to set up to endpoint to make individual predictions which has been done but currently has a bug in it that is messing up the input data and therefore not able to return a response. This is my primary task for this week, I don’t expect it to be too difficult to fix, and then our predictor will be running and integrated. At that point I will move on to helping Nakul with the backend form algorithms and Scott with the frontend. First I am going to help Scott get a testing platform up and running which will allow us to use OpenPose’s visualization tools right next to the output of our classifier as well our backend algorithms which will provide us with both key demonstration tools for how out project works as well as be hugely helpful with beta-testing and debugging.

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