Inputs
| Parameter | Description | Comfy dtype |
|---|---|---|
clip_vision | Represents the CLIP vision model used for encoding visual features from the initial image, playing a crucial role in understanding the content and context of the image for video generation. | CLIP_VISION |
init_image | The initial image from which the video will be generated, serving as the starting point for the video generation process. | IMAGE |
vae | A Variational Autoencoder (VAE) model used for encoding the initial image into a latent space, facilitating the generation of coherent and continuous video frames. | VAE |
width | The desired width of the video frames to be generated, allowing for customization of the video’s resolution. | INT |
height | The desired height of the video frames, enabling control over the video’s aspect ratio and resolution. | INT |
video_frames | Specifies the number of frames to be generated for the video, determining the video’s length. | INT |
motion_bucket_id | An identifier for categorizing the type of motion to be applied in the video generation, aiding in the creation of dynamic and engaging videos. | INT |
fps | The frames per second (fps) rate for the video, influencing the smoothness and realism of the generated video. | INT |
augmentation_level | A parameter controlling the level of augmentation applied to the initial image, affecting the diversity and variability of the generated video frames. | FLOAT |
Outputs
| Parameter | Description | Comfy dtype |
|---|---|---|
positive | The positive conditioning data, consisting of encoded features and parameters for guiding the video generation process in a desired direction. | CONDITIONING |
negative | The negative conditioning data, providing a contrast to the positive conditioning, which can be used to avoid certain patterns or features in the generated video. | CONDITIONING |
latent | Latent representations generated for each frame of the video, serving as a foundational component for the video generation process. | LATENT |
This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHub