ComfyUI Node: Animate image with UniAnimate

Animate image with UniAnimate:

The UniAnimateImage node is designed to animate images using the UniAnimate framework, which leverages advanced neural network techniques to generate smooth and realistic animations from static images. This node is particularly useful for AI artists who want to bring their static artwork to life by creating dynamic and engaging animations. The primary goal of this node is to simplify the process of animating images by providing a robust and user-friendly interface that handles complex computations and transformations internally. By using this node, you can achieve high-quality animations with minimal effort, making it an essential tool for enhancing your creative projects.

Animate image with UniAnimate Input Parameters:

x

This parameter represents the input image tensor that you want to animate. It is a multi-dimensional array containing the pixel values of the image. The quality and resolution of the input image can significantly impact the final animation, so it is recommended to use high-resolution images for the best results.

t

This parameter denotes the time steps or frames for the animation. It controls the temporal aspect of the animation, determining how the image evolves over time. Adjusting this parameter allows you to create animations of varying lengths and complexities.

y

This optional parameter can be used to provide additional context or labels for the animation process. It can help in guiding the animation to follow specific patterns or behaviors based on the provided labels.

depth

This optional parameter represents the depth information of the input image. Including depth information can enhance the realism of the animation by providing a sense of three-dimensionality.

image

This parameter is used to input an additional image that can be used for joint training with the video. It helps in creating more coherent and contextually accurate animations by leveraging multiple images.

motion

This optional parameter provides motion vectors or information that can guide the animation process. It helps in creating more dynamic and fluid animations by incorporating motion data.

local_image

This parameter allows you to input a local image that can be used for embedding and enhancing the animation. It helps in adding finer details and textures to the animated output.

single_sketch

This optional parameter can be used to input a single sketch that guides the animation process. It helps in creating animations that follow the contours and shapes defined in the sketch.

masked

This optional parameter is used to input a masked version of the image, where certain regions are highlighted or excluded. It helps in focusing the animation on specific parts of the image.

canny

This optional parameter allows you to input a Canny edge-detected version of the image. It helps in creating animations that emphasize the edges and outlines of the image.

sketch

This optional parameter is used to input a sketch version of the image. It helps in guiding the animation process by providing a simplified representation of the image.

dwpose

This parameter allows you to input pose information for the animation. It helps in creating animations that follow specific poses or movements.

randomref

This optional parameter is used to input a random reference image that can be used for embedding and enhancing the animation. It helps in adding variability and uniqueness to the animated output.

histogram

This optional parameter allows you to input histogram data that can guide the animation process. It helps in creating animations that follow specific color distributions or patterns.

fps

This parameter denotes the frames per second for the animation. It controls the speed and smoothness of the animation, with higher values resulting in smoother animations.

video_mask

This optional parameter is used to input a mask for the video frames. It helps in focusing the animation on specific parts of the video.

focus_present_mask

This optional parameter allows you to input a mask that focuses on the present frame. It helps in creating animations that emphasize the current frame while maintaining temporal coherence.

prob_focus_present

This parameter represents the probability at which a given batch sample will focus on the present. It ranges from 0 to 1, with 0 meaning no focus and 1 meaning complete focus on the present frame.

mask_last_frame_num

This parameter denotes the number of frames to mask at the end of the animation. It helps in creating smoother transitions by masking the last few frames.

Animate image with UniAnimate Output Parameters:

x

The output parameter x represents the animated image tensor. It is a multi-dimensional array containing the pixel values of the animated frames. This output can be used for further processing or directly displayed as an animation.

Animate image with UniAnimate Usage Tips:

• Ensure that your input images are of high resolution to achieve the best animation quality.
• Experiment with different values for the t parameter to create animations of varying lengths and complexities.
• Use the depth parameter to add a sense of three-dimensionality to your animations.
• Incorporate motion vectors using the motion parameter to create more dynamic and fluid animations.
• Utilize the fps parameter to control the speed and smoothness of your animations.

Animate image with UniAnimate Common Errors and Solutions:

CUDA is not available

• Explanation: This error occurs when the CUDA library is not available on your system, which is required for GPU acceleration.
• Solution: Ensure that you have a compatible NVIDIA GPU and that the CUDA library is properly installed and configured on your system.

Inpainting is not supported

• Explanation: This error occurs when the masked parameter is used without enabling inpainting.
• Solution: Ensure that inpainting is enabled if you are using the masked parameter, or avoid using this parameter if inpainting is not supported.

Invalid input dimensions

• Explanation: This error occurs when the input image tensor has incorrect dimensions.
• Solution: Ensure that your input image tensor has the correct dimensions, typically in the format (batch, channels, frames, height, width).

Missing required parameters

• Explanation: This error occurs when one or more required parameters are not provided.
• Solution: Ensure that all required parameters, such as x and t, are provided when using the node.