Not really, if you want a robust recognition system. In fact it's often normal in image sets to create part of your training data by transforming pictures of your training set, for example by rotating, translating, scaling etc
really depends on what exactly your doing, I'd say. Sure, variety is generally good but only in so far as it's actually required in the particular use case.
All I'm saying is this doesn't seem like an entirely implausible explanation. You can even see the old image under the rotated one - not exactly looking like a typical AI generated media glitch, from what I've seen so far.
Not really, if you want a robust recognition system. In fact it's often normal in image sets to create part of your training data by transforming pictures of your training set, for example by rotating, translating, scaling etc
really depends on what exactly your doing, I'd say. Sure, variety is generally good but only in so far as it's actually required in the particular use case.
All I'm saying is this doesn't seem like an entirely implausible explanation. You can even see the old image under the rotated one - not exactly looking like a typical AI generated media glitch, from what I've seen so far.