ComfyUI Node: Hunyuan-Foley Sampler

Hunyuan-Foley Sampler:

The HunyuanFoleySampler is a specialized node designed to generate audio content from visual inputs, such as images or video frames, using advanced audio synthesis techniques. This node leverages the capabilities of the Hunyuan model to create synchronized audio that matches the visual content, making it particularly useful for applications in multimedia production, where audio-visual coherence is crucial. By utilizing this node, you can transform static or dynamic visual data into rich audio experiences, enhancing the overall sensory impact of your projects. The node is capable of handling various parameters to fine-tune the audio output, ensuring that the generated sound aligns with the desired artistic vision. Its integration into the ComfyUI framework allows for seamless operation within a larger workflow, making it a valuable tool for AI artists looking to expand their creative possibilities.

Hunyuan-Foley Sampler Input Parameters:

hunyuan_model

The hunyuan_model parameter specifies the pre-trained model used for generating audio from visual inputs. This model is the core component that interprets the visual data and synthesizes corresponding audio. It is crucial to select a model that aligns with your project's requirements to achieve the best results.

hunyuan_deps

The hunyuan_deps parameter refers to the dependencies required by the Hunyuan model to function correctly. These dependencies include various libraries and auxiliary models that support the main model's operations. Ensuring that all dependencies are correctly configured is essential for the node's successful execution.

image

The image parameter is the visual input from which the audio will be generated. This can be a single image or a sequence of frames from a video. The quality and content of the image significantly influence the characteristics of the generated audio.

fps

The fps (frames per second) parameter indicates the frame rate of the input video. This is important for synchronizing the audio with the visual content, especially when dealing with video inputs. A higher frame rate can lead to more detailed audio synchronization.

duration

The duration parameter defines the length of the audio to be generated. It is important to set this parameter according to the length of the visual content to ensure that the audio and video are perfectly aligned.

prompt

The prompt parameter allows you to provide textual guidance to the model, influencing the style or mood of the generated audio. This can be used to steer the audio synthesis process towards a specific artistic direction.

negative_prompt

The negative_prompt parameter serves as a counterbalance to the prompt, specifying elements or styles to avoid in the generated audio. This helps refine the output by excluding unwanted characteristics.

cfg_scale

The cfg_scale parameter controls the strength of the prompt's influence on the audio generation process. A higher value increases the prompt's impact, while a lower value allows the model more creative freedom.

steps

The steps parameter determines the number of iterations the model will perform during the audio generation process. More steps can lead to higher quality audio but may increase processing time.

sampler

The sampler parameter specifies the sampling method used during audio generation. Different samplers can produce varying audio characteristics, so selecting the appropriate one is important for achieving the desired output.

batch_size

The batch_size parameter defines the number of audio samples to generate in one batch. A larger batch size can speed up the process but may require more computational resources.

seed

The seed parameter sets the random seed for the audio generation process, ensuring reproducibility of results. Using the same seed will produce identical audio outputs for the same inputs.

force_offload

The force_offload parameter, when enabled, offloads the model to save VRAM, which is useful for managing memory usage during the audio generation process. This can be particularly beneficial when working with limited hardware resources.

Hunyuan-Foley Sampler Output Parameters:

audio_output_first

The audio_output_first parameter provides the first generated audio waveform along with its sample rate. This output is crucial for evaluating the initial results of the audio generation process and serves as a basis for further refinement or integration into multimedia projects.

Hunyuan-Foley Sampler Usage Tips:

• Ensure that the hunyuan_model and hunyuan_deps are correctly configured and compatible with your input data to avoid errors during execution.
• Use the prompt and negative_prompt parameters to guide the audio generation process towards your desired artistic outcome, balancing creativity and control.
• Adjust the cfg_scale and steps parameters to find the optimal balance between audio quality and processing time, especially when working with complex visual inputs.

Hunyuan-Foley Sampler Common Errors and Solutions:

Model Offloading Error

• Explanation: This error occurs when the model cannot be offloaded due to insufficient VRAM or incorrect configuration.
• Solution: Ensure that your system has enough VRAM available and that the force_offload parameter is set correctly. Consider reducing the batch size or using a more efficient model configuration.

Dependency Configuration Error

• Explanation: This error arises when the required dependencies for the Hunyuan model are not properly installed or configured.
• Solution: Verify that all necessary dependencies are installed and correctly configured. Check the documentation for any specific installation instructions related to the Hunyuan model.

Audio-Visual Synchronization Issue

• Explanation: This issue occurs when the generated audio does not align with the visual content, often due to incorrect fps or duration settings.
• Solution: Double-check the fps and duration parameters to ensure they match the properties of your visual input. Adjust these settings as needed to achieve proper synchronization.