Stable Diffusion Animation

Animate Stable Diffusion by interpolating between two prompts

Code: https://github.com/andreasjansson/cog-stable-diffusion/tree/animate

How does it work?

Starting with noise, we then use stable diffusion to denoise for n steps towards the mid-point between the start prompt and end prompt, where n = num_inference_steps * (1 - prompt_strength). The higher the prompt strength, the fewer steps towards the mid-point.

We then denoise from that intermediate noisy output towards num_animation_frames interpolation points between the start and end prompts. By starting with an intermediate output, the model will generate samples that are similar to each other, resulting in a smoother animation.

Finally, the generated samples are interpolated with Google's FILM (Frame Interpolation for Large Scene Motion) for extra smoothness.