Next, we generate image captions for the concept that shall be edited and for the new target concept. We can use a model like Flan-T5 for this purpose. Then, “mean” prompt embeddings for both the source and target concepts are created via the text encoder. Finally, the pix2pix-zero algorithm is used to edit the synthetic image. To edit a real image, one first generates an image caption using a model like BLIP. Then one applies DDIM inversion on the prompt and image to generate “inverse” latents. Similar to before, “mean” prompt embeddings for both source and target concepts are created and finally the pix2pix-zero algorithm in combination with the “inverse” latents is used to edit the image. Pix2Pix Zero is the first model that allows “zero-shot” image editing. This means that the model