def test(image, char=None):
classifications = MLClassifications()
coms = connected_components(image)
com = largest_component(coms)
xs = params_from_component(com, with_one=True)
for c, ws in models.items():
s = dot(ws, Trainer.get_transformed_data(xs, polynomial_transform_order))
print c, s
classifications.add(c, s)
return classifications
