There are many CNNs for object classification and shapes drawing (e.g., square, heart, curved line etc) classification is even simpler.
However, I haven't found yet a robust method for shape quality classification. I.e., given a drawing of a circle, I want to know how similar it is to a perfect circle.
for example,
Now, there is a SSIM index but it was designed to distinguish between photos and not drawings. This is why the position of the shape in the image (within a few pixels) can cause use SSIM differences.
I attach some result so you can see what I mean
The method Im using right now is to hand-label the shapes and perform a supervised network, but I wonder maybe there is a better way (maybe siamese networks?