ComfyUI Node: MotionCLIP Text Encode

MotionCLIP Text Encode:

The MotionCLIPTextEncode node is designed to bridge the gap between textual descriptions and motion data, enabling you to generate motion conditioning based on textual prompts. This node leverages the capabilities of the MotionDiff framework to encode text descriptions into a format that can be used to condition motion generation models. By providing a textual description of an action or motion, such as "a person performs a cartwheel," this node processes the text and integrates it with motion data, allowing for the creation of dynamic and contextually relevant motion sequences. This functionality is particularly useful for AI artists looking to create animations or motion graphics that are driven by natural language descriptions, making the creative process more intuitive and accessible.

MotionCLIP Text Encode Input Parameters:

md_clip

This parameter expects an instance of the MD_CLIP model, which is responsible for encoding the text into a format that can be used for motion conditioning. The MD_CLIP model processes the textual input and integrates it with the provided motion data to generate the necessary conditioning information.

motion_data

This parameter requires MOTION_DATA, which represents the motion data that will be conditioned based on the textual description. The motion data serves as the base upon which the text encoding will be applied, allowing for the generation of motion sequences that align with the provided text.

text

This parameter is a STRING input that allows you to provide a textual description of the motion you want to generate. The default value is "a person performs a cartwheel," and it supports multiline input, enabling you to provide detailed and complex descriptions. The text you input here will be encoded and used to condition the motion data.

MotionCLIP Text Encode Output Parameters:

MD_CONDITIONING

The output of this node is MD_CONDITIONING, which represents the motion conditioning information generated from the provided text and motion data. This output can be used to drive motion generation models, ensuring that the resulting motion sequences are contextually aligned with the textual description provided.

MotionCLIP Text Encode Usage Tips:

• Ensure that your textual descriptions are clear and specific to achieve the best results in motion conditioning.
• Experiment with different text prompts to see how they influence the generated motion sequences.
• Use the motion_data parameter to provide a variety of base motions, allowing for diverse and dynamic motion generation based on the same text prompt.

MotionCLIP Text Encode Common Errors and Solutions:

"Invalid md_clip model instance"

• Explanation: This error occurs when the md_clip parameter does not receive a valid MD_CLIP model instance.
• Solution: Ensure that you are providing a correctly initialized MD_CLIP model to the md_clip parameter.

"Motion data not provided"

• Explanation: This error occurs when the motion_data parameter is missing or invalid.
• Solution: Make sure to provide valid motion data to the motion_data parameter to enable proper motion conditioning.

"Text input is empty"

• Explanation: This error occurs when the text parameter is left empty.
• Solution: Provide a non-empty textual description in the text parameter to generate motion conditioning based on the text.