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ClippyRebornImageLoader imports clipboard images into ComfyUI with interactive feedback.
The ClippyRebornImageLoader is a specialized node designed to seamlessly load images directly from your system's clipboard into the ComfyUI environment. This node is particularly beneficial for users who frequently work with images from various sources, such as web browsers or image editors, and need a quick and efficient way to import these images into their workflow. By simply copying an image to the clipboard, the ClippyRebornImageLoader can detect and load it, providing a smooth and user-friendly experience. The node is equipped with a playful and interactive feedback system, inspired by the nostalgic Clippy assistant, which offers humorous and supportive messages based on the success or failure of the image loading process. This feature not only adds a touch of personality to the node but also helps users understand the status of their actions in a light-hearted manner. Overall, the ClippyRebornImageLoader enhances productivity by reducing the steps needed to import images and adds an element of fun to the process.
The ClippyRebornImageLoader does not require explicit input parameters from the user, as it automatically attempts to load an image from the system clipboard. The node operates based on the presence of image data in the clipboard, making it straightforward and easy to use without the need for additional configuration.
The ui output parameter provides a structured response that includes a preview of the loaded image and a text message. The preview image is saved temporarily and displayed to the user, allowing for immediate visual confirmation of the loaded content. The accompanying text message, delivered in Clippy's signature style, offers feedback on the loading process, which can range from success confirmations to humorous commentary on the image's nature.
The result output parameter contains the image data converted into a tensor format suitable for further processing within ComfyUI. This tensor is formatted as a batch with height, width, and channel dimensions, and the pixel values are normalized to a float32 range between 0 and 1. This format ensures compatibility with subsequent nodes in the workflow, facilitating seamless integration and manipulation of the image data.
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