Creating Dynamic Animations (QR Code Monster + Animatediff LCM in ComfyUI)
TLDRIn this tutorial, the creator demonstrates how to produce dynamic animations using a combination of QR Code Monster and Animatediff LCM within ComfyUI. The process involves avoiding common mistakes and leveraging the guidance of hro conit AI. The workflow begins with a default setup, then modifies it using LCM sampler and animate diff nodes. The VAE from a checkpoint is integrated, and the text-to-image generation is set up with a vertical orientation. The animation is controlled by a test prompt, and additional nodes are added for sampling and animation. The LCM is fine-tuned with a Lura node, and a control net workflow is applied using the QR Monster model. The final animation is influenced by a black and white illusion video, with adjustments made to control net strength for better results. The tutorial concludes with a recap of the process and a reminder to ensure the correct input model for LCM.
Takeaways
- 🎨 **Combining Tools**: The tutorial shows how to combine QR Code Monster and Animatediff LCM in ComfyUI to create dynamic animations.
- 🔍 **Avoiding Mistakes**: The speaker shares common mistakes and solutions encountered during the process, which can help avoid getting stuck.
- 🤖 **AI Assistance**: Hro Conit AI was acknowledged for guidance and sharing processes, highlighting the importance of AI collaboration.
- 📚 **Workflow Customization**: The default workflow is modified using LCM sampler and animate diff nodes, replacing the K sampler.
- 🔄 **Checkpoint Integration**: The VAE from a specific checkpoint is used, emphasizing the role of pre-trained models in the process.
- 📏 **Resolution Adjustment**: The resolution is changed to 512x896 for vertical animation generation, indicating the flexibility in output dimensions.
- 🔗 **Node Connections**: Importance of correctly connecting nodes, such as sampler LCM cycle and schulist, for the workflow to function properly.
- 🎥 **Animate Workflow**: The creation of an animation from a text prompt using the animate diff and gen two nodes is explained.
- 🔁 **Iterative Process**: The process involves testing and adjusting, such as changing the model to Dream Shaper 8 and using test prompts.
- 📈 **Optimization**: The use of Lura node and adjusting LCM settings like seed and frame duration are crucial for refining the animation.
- 📊 **Control Net Strength**: Adjusting the control net strength and weight can significantly influence the final animation's appeal.
- 🔧 **Troubleshooting**: The video demonstrates troubleshooting steps, such as lowering control net strength to achieve better results.
Q & A
What is the main focus of the tutorial?
-The tutorial focuses on creating dynamic animations using a combination of QR Code Monster and Animatediff LCM in ComfyUI.
What is the role of the QR Code Monster in this process?
-The QR Code Monster is used to influence the animation by controlling the generation process with a black and white illusion.
How does the LCM (Latent Conditioned Model) improve the animations?
-The LCM improves the animations by providing a more refined control over the generation process, allowing for better results.
What is the purpose of the 'Animate Diff' nodes?
-The 'Animate Diff' nodes are used to generate the video animation of the prompt, which is then used as an input for the LCM Schuler.
What is the significance of the 'Evolve Sampling' node?
-The 'Evolve Sampling' node is used to input the model from the checkpoint, which is then connected to the LCM Schuler node for animation generation.
How can one avoid common mistakes in this process?
-To avoid common mistakes, ensure all necessary nodes are connected correctly, use the correct input models, and adjust the control net strength and weight to achieve the desired results.
What is the recommended frame duration for a quick preview of the animation?
-For a quick preview, a frame duration of 16 frames is recommended.
How does the 'VHSo Combine' node contribute to the final animation?
-The 'VHSo Combine' node combines the VA code into the video, contributing to the final generation of the animation.
What is the importance of the 'Control Net' workflow?
-The 'Control Net' workflow is crucial as it helps to refine the animation by applying an advanced control net influenced by the QR code.
What are the recommended settings for the LCM to improve results?
-To improve results, add the Lura node, use the correct input models, and adjust the LCM Schuler settings, such as changing the seed and using a fixed setting.
How can one find inspiration for creating animations?
-One can find inspiration by checking out works on Civic AI and Instagram, as well as exploring optical illusions from sources like Motion Array.
Outlines
🎨 Creating Dynamic Animations with K UI Tools
The video script begins with the creator discussing how to produce dynamic and interesting animations within K UI. They mention using a combination of the QR code monster and animated diff LCM to generate optical illusions. The process can be tricky, with potential pitfalls that the creator had experienced. They express gratitude to Hro Conit AI for guidance and inspiration. The tutorial then moves on to loading a default workflow and modifying it with the LCM sampler and animate diff nodes. The workflow includes replacing the K sampler, using a VAE from a checkpoint, and setting up the nodes for positive and negative prompts. The creator also provides instructions for connecting the nodes to generate a vertical animation and emphasizes the importance of connecting the sampler nodes correctly.
🤖 Enhancing Animations with LCM and Control Net
The second paragraph delves into refining the animation process with the LCM and control net. The creator details how to add the Lura node for better LCM utilization and connects the model to the Lura node for the animate LCM. They also discuss adjusting the evolved sampling to use LCM and changing the LCM Schuler settings. The script then introduces the control net workflow, mentioning the use of the QR Monster version two model and the importance of a black and white video for the QR code to influence the animation. The creator guides viewers on how to select an optical illusion video from motion array and integrate it into the workflow. They also explain how to connect the nodes for the control net and adjust the frame duration and latent image space for the animation. The paragraph concludes with troubleshooting tips, such as reducing the control net strength for better results, and encourages experimentation with different prompts and settings.
📹 Finalizing the Animation and Future Tutorials
The final paragraph of the script wraps up the tutorial by showing the viewer how to finalize the animation settings. It includes changing frame rates to match video inputs, renaming the final video, and adjusting the control net strength and weight for improved aesthetics. The creator demonstrates how to compare the new results with the old ones and emphasizes the importance of playing around with the control net strength to achieve the desired outcome. They also share a new prompt inspired by Civit AI and show the results of applying this prompt to the animation. The paragraph ends with a recap of the workflow, which involves a text-to-image prompt animated by animate, controlled by a black and white illusion, and influenced by the QR code monster model. The creator reminds viewers to ensure they have the correct input model for the LCM workflow and ends with a prompt for viewers to engage with the content by liking the video and looking forward to the next tutorial.
Mindmap
Keywords
💡Dynamic Animations
💡QR Code Monster
💡Animatediff LCM
💡ComfyUI
💡LCM Sampler
💡Animate Diff Nodes
💡Optical Illusions
💡Control Net Workflow
💡VHSo Combine
💡Evolve Sampling Node
💡Motion Array
Highlights
The combination of QR code monster and animated diff LCM is used to create dynamic animations in ComfyUI.
The process can have bad results, but common mistakes can be avoided with the right guidance.
Hro Conit AI shared his process and guided the presenter, with inspiring works on Civic Ai and Instagram.
Default workflow is loaded and modified using LCM sampler and animate diff nodes.
The VAE from the checkpoint is used in the VAE node for the generation process.
Text and code Advanced are used as replacements in the workflow.
The low checkpoint is rerouted into the sampler custom node for both positive and negative prompts.
The latent image is connected to the VA de code and text prompt node for vertical animation generation.
A group is created for the 'text to image' workflow to keep the process organized.
The checkpoint model is set to 'dream shaper 8' for the test prompt.
Missing sampler notes are identified and connected to the sampler custom node.
Animate diff workflow is started with the addition of Evolve sampling and gen two nodes.
The load animate diff model node is used for the animation generation process.
The model from the checkpoint is input into the LCM scheduler node for animation.
The duration of the animation is set to 16 frames for a quick preview.
VHS combine is used to combine the VA code for the final generation.
The Lura node is added for better LCM Laura usage in the workflow.
The control net workflow is created using the QR Monster version two model.
Optical illusions from motion array are used to influence the animation.
The QR code monster model is used to control the animation generation.
The frame duration and latent image space are adjusted for better results.
Lowering the control net strength and weight improves the final animation outcome.
Different prompts can be used to create a variety of dynamic animations.
The final workflow combines text to image, animation, and control by a black and white illusion.