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Visualizing intermediate optimization steps as requested in #18

Basically, drag_diffusion_update now returns optimized latent and optimization sequence that is then denoised and decoded in run_drag. UI is modified with a checkbox (default False)

Frames are stored in a separate folder and they can be converted to a gif or mp4 with something like:

ffmpeg -framerate 10 -i iter_%d.png result.gif

Please let me know if you did anything else to produce dragging trajectories for the website.

The following are the results for some random lion stock image (30 optimization steps):

image

result

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