Adrian Rosebrock of PyImageSearch recently released a brand new tutorial: Detecting Parkinson’s Disease with OpenCV, Computer Vision, and the Spiral/Wave Test which shows how to automatically detect Parkinson’s disease in hand-drawn images of spirals and waves. Adrian used classical computer vision techniques like Histogram of Oriented Gradients (HOG) for quantifying the features of the images and used them to train a Random Forest Classifier . He got an accuracy of 83.33% .
I decided to apply deep learning to this problem and see if I can push the score. It turns out that I was able to do it. You can find my notebook here.
Would you mind doing it and share the results here? The researchers actually supplied the train and test sets separately. Hence, I decided not to break that arrangement.