Awesome AnimateDiff Workflow

✨ Awesome Animation Workflow ✨

A simple animation workflow for Stable Diffusion!

╭🎨 About This Workflow 🎨╮

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Workflow Insights:

• Select v3_sd15_adapter.ckpt as one of your LoRAs for optimal performance [Link]

• Robust Video Matting is recommended for removing backgrounds from videos of human subjects, setting the stage for deeper creative exploration.

• Animation Output Options: The workflow produces four video outputs, offering flexibility in presentation and format. This includes two GIFs and two MP4s, segmented by the first and second ksampler passes for varied detail levels.

• Efficiency Tips: For those looking to streamline the process, consider bypassing the second pass and/or upscaling. These steps enhance detail but can be omitted to save time without significantly compromising quality.

╭🚀 Workflow Specifics 🚀╮

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Here's how to make the most out of Awesome Animation Workflow:

1. Initial Setup: Ensure the AnimateDiff ControlNet model is loaded for the second ksampler pass.

2. Video Outputs Explained:

• The left two videos are from the first ksampler pass; the right two are from the second.

• The top two videos are formatted as GIFs, while the bottom two are in MP4 format.

• To reduce lag, right-click on the video outputs and select "hide preview."

3. Notes on Walking Animations:

• The hair walking animation relies solely on openpose for a seamless 21-frame loop.

• The robot walking animation can incorporate both openpose and optionally depth, creating a 32-frame loop. Frames 1-24 can be skipped for alternative perspectives.

• The dancing video relies solely on openpose for an (almost) seamless 16-frame loop.

╭💡 Pro Tips 💡╮

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• Experiment with different LoRAs and settings to discover unique animation styles.

• Pay attention to the nuances of your animations by reviewing the output from both ksampler passes.