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. To see if I was able to do this, I would request you to take a look at the accompanying notebook here.

Note that, the data was provided along with the PyImageSearch tutorial mentioned above. In order to make the folder structure more convenient for myself, I arranged it in the following way:

Whereas, Adrian's arrangment was a bit different:

Useful links:

• PyImageSearch Gurus
• Practical Deep Learning for Coders, v3