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Powerful node for image segmentation using CLIPSeg model, generates masks based on text prompts, offers fine-tuning parameters.
ApplyCLIPSeg+ is a powerful node designed to perform image segmentation using the CLIPSeg model. This node leverages the capabilities of the CLIPSeg model to identify and segment specific parts of an image based on a given text prompt. By processing the image and the text prompt together, it generates a mask that highlights the areas of the image that correspond to the prompt. This is particularly useful for AI artists who want to isolate or manipulate specific regions of an image without manually creating masks. The node also offers various parameters to fine-tune the segmentation results, such as thresholding, smoothing, dilation, and blurring, making it a versatile tool for detailed image editing and creative projects.
The image parameter is the input image that you want to segment. It should be provided in a tensor format, typically normalized between 0 and 1. This image will be processed by the CLIPSeg model to generate the segmentation mask.
The clip_seg parameter is a tuple containing the CLIPSeg processor and model. This is usually obtained from the LoadCLIPSegModels+ node, which loads the necessary components for the segmentation process.
The prompt parameter is a text string that describes the part of the image you want to segment. The CLIPSeg model uses this prompt to identify and highlight the relevant areas in the image. For example, if you want to segment out a "cat" in the image, you would set the prompt to "cat".
The threshold parameter is a float value that determines the cutoff for the segmentation mask. Pixels with a confidence score above this threshold will be included in the mask. The value typically ranges from 0 to 1, with a default value that balances precision and recall.
The smooth parameter is an integer that specifies the amount of Gaussian smoothing to apply to the segmentation mask. A higher value results in a smoother mask, which can help reduce noise and create more natural edges. The value should be an odd number, and if an even number is provided, it will be incremented by one.
The dilate parameter is an integer that controls the dilation of the segmentation mask. Dilation expands the mask boundaries, which can be useful for ensuring that all relevant areas are included. A positive value increases the mask size, while a negative value reduces it.
The blur parameter is an integer that specifies the amount of Gaussian blurring to apply to the final segmentation mask. Blurring can help create softer edges and a more visually appealing result. Like the smooth parameter, the value should be an odd number, and if an even number is provided, it will be incremented by one.
The outputs parameter is a tensor containing the final segmentation masks for the input images. Each mask highlights the areas of the image that correspond to the given text prompt, with optional smoothing, dilation, and blurring applied as specified by the input parameters. These masks can be used for further image processing or creative manipulation.
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