My limited experience is that stable characters across a number of images are a weakness today, and I wouldn’t be confident that genAI is a great way to go about it. If you want to try it, here’s what I’d go with:

• If you can get images with consistent outlines via some other route, you can try using ControlNet to do the rest of the image.

• If you just need slight variations on a particular image, you can use inpainting to regenerate the relevant portions (e.g. an image with a series of different expressions).

• If you want to work from a prompt, try picking a real-life person or character as a starting point, that may help, as models have been trained on them. Best is if you can get them at once point in time (e.g. “actor in popularmovie”). If you have a character description that you’re slapping into each prompt, only describe elements that are actually visible in a given image.

I’ve found that a consistent theme is something that is much more achievable, in that you can add “by <artist name>” to your prompt terms for any artist that the model has been trained on a number of images from. If you’re using a model that supports prompt term weighting (e.g. Stable Diffusion), you can increase the weight here to increase the strength of the effect. Flux doesn’t support prompt term weighting (though it’s really aimed at photographic images anyway). It’s possible to blend multiple artists or genres as prompt terms.