To rescale the prediction output to the original image, the point in encoded coordinates can be decoded with a PointScaler:
img, ref_point = ds[0]
_,_,p = learn.predict(img) # p = tensor([0.1011, 0.0861])
sclr = PointScaler()
sclr(img) # Transforming the image stores the image size in self.sz
dp = sclr.decode(TensorPoint.create(p)) # need a TensorPoint
print(dp, ref_point)