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ComfyDeploy: How ComfyUI-HunyuanVideoImagesGuider works in ComfyUI?

What is ComfyUI-HunyuanVideoImagesGuider?

A specialized node for ComfyUI that enable advanced motion and animation capabilities for image as guider for video processing In Hunyuan Video.

How to install it in ComfyDeploy?

Head over to the machine page

  1. Click on the "Create a new machine" button
  2. Select the Edit build steps
  3. Add a new step -> Custom Node
  4. Search for ComfyUI-HunyuanVideoImagesGuider and select it
  5. Close the build step dialig and then click on the "Save" button to rebuild the machine

ComfyUI-HunyuanVideoImagesGuider

A specialized node for ComfyUI that enable motion and animation capabilities for image as guider for video processing In Hunyuan Video T2V model weights.

How to use this node , you can check it out in this video : https://youtu.be/fq95OLDVCdU

Features

Hunyuan Video Image To Guider

  • Smooth camera panning effects (X and Y axis)
  • Zoom in/out animations
  • Seamless image tiling and repetition
  • Customizable frame count and motion strength
  • Support for various resize modes
  • Optional center cropping

Installation

  1. Clone this repository into your ComfyUI custom nodes directory:
cd ComfyUI/custom_nodes
git clone https://github.com/benjiyaya/ComfyUI-HunyuanVideoImagesGuider.git
  1. Restart ComfyUI to load the new nodes

Usage

Hunyuan Video Image To Guider

Parameters:

  • image: Input image
  • move_range_x: Horizontal motion range (-1.0 to 1.0) (Best range in -0.05 - 0.05)
  • move_range_y: Vertical motion range (-1.0 to 1.0) (Best range in -0.05 - 0.05)
  • zoom: Zoom effect strength (0.0 to 0.5)
  • frame_num: Number of frames to generate (2-150)
  • resize_mode: Image resize options (disabled/custom/keep_ratio)
  • target_width: Custom width for resize
  • target_height: Custom height for resize
  • center_crop: Enable/disable center cropping

*** For the sampler denoise, good range in 0.7-0.9 , below 0.5 almost no animation for object.

Technical Details

The nodes utilize PyTorch for efficient tensor operations and implement various optimization techniques:

  • Automatic mixed precision
  • Efficient memory management
  • Batched processing
  • Error handling and recovery
  • Progress tracking

showcase

https://github.com/user-attachments/assets/7701fdec-74db-4277-a883-3c204037e5ba

showcase

https://github.com/user-attachments/assets/e9bec99d-f87e-44b2-95c2-48113085e39b

showcase

https://github.com/user-attachments/assets/0b88a0d3-9071-4cb8-adae-d47776f27cdd

showcase

https://github.com/user-attachments/assets/e5a8d3bb-f43b-4a87-bdde-926afd03cd1b

9

https://github.com/user-attachments/assets/77bf3cbc-8292-466b-9fff-ae4b7ec2c835

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - feel free to use in your own projects.

Credits

Created by Benji and DeepSeek AI Copilot