That's a way to classify whether or not the pics are indeed dick pics, but the problem lies in how these recent diffusion models work. Typically you have two encoders, one for the text prompt and one for the image. Then you train a model to optimize where the prompt embeddings match the image embeddings. You've got to actually have some decent descriptions of the dick, like: thin, girthy, 7", 8", 4", micropenis, veiny, limp, hard, huge tip, bifurcated, foreskin, black, white, latino, asian, etc, if you want to generate with any accuracy your desired fake penis.