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Versatile node for inpainting images, cropping, and expanding context for AI artists to repair or modify specific areas effectively.
FL_InpaintCrop is a versatile node designed to facilitate the inpainting process by cropping and preparing images and masks for further manipulation. This node is particularly useful for AI artists who need to seamlessly repair or modify specific areas of an image. By expanding the context around the masked area, it ensures that the inpainting process has enough surrounding information to produce coherent and visually appealing results. The node offers various options to control the cropping and context expansion, making it adaptable to different inpainting scenarios. Whether you need to fill in missing parts of an image or remove unwanted elements, FL_InpaintCrop provides the necessary tools to achieve high-quality results.
The image parameter represents the input image that you want to process. This is the primary image on which the inpainting will be performed. The quality and resolution of this image will directly impact the final output.
The mask parameter is a binary mask that indicates the areas of the image that need to be inpainted. Areas marked with 1 (or white) will be inpainted, while areas marked with 0 (or black) will remain unchanged. This mask guides the inpainting process to focus on specific regions.
This parameter defines the number of pixels by which the context around the masked area should be expanded. Expanding the context helps the inpainting algorithm to have more surrounding information, leading to better results. The value should be an integer, with higher values providing more context.
The context_expand_factor parameter is a multiplier that scales the context area around the mask. This factor allows for proportional expansion based on the size of the masked area. A value greater than 1 will increase the context area, while a value less than 1 will decrease it.
The invert_mask parameter is a boolean flag that, when set to true, inverts the mask. This means that areas marked for inpainting will be swapped with areas to remain unchanged. This can be useful in scenarios where the initial mask needs to be reversed.
This boolean parameter determines whether holes in the mask should be filled before inpainting. Filling holes can help create a more contiguous area for inpainting, leading to smoother and more natural results.
The mode parameter specifies the operational mode of the node. Different modes may offer various inpainting strategies or adjustments, such as free size or fixed size. The exact modes available depend on the implementation.
This parameter allows you to force the output to a specific size. It can be useful when you need the inpainted image to match certain dimensions, regardless of the original image size.
The rescale_factor parameter is used to scale the image and mask before inpainting. This can help in scenarios where the image needs to be upscaled or downscaled to match the desired output resolution. The value should be a float, with 1.0 indicating no rescaling.
Padding adds extra space around the cropped area to ensure that the inpainting process has enough room to blend the new content seamlessly. The value should be an integer, with higher values providing more padding.
This optional parameter allows you to provide an additional context mask. If provided, it should match the dimensions of the input image. This mask can be used to further refine the context area for inpainting.
The stitch output is a dictionary containing information about the original image, the cropped mask, and the coordinates of the cropped area. This information is essential for the subsequent stitching process, ensuring that the inpainted area is correctly aligned with the original image.
The cropped_image output is the portion of the input image that has been cropped based on the mask and context expansion parameters. This image is ready for inpainting and contains the area that needs to be modified.
The cropped_mask output is the corresponding mask for the cropped image. It indicates the areas within the cropped image that need to be inpainted, ensuring that the inpainting process focuses on the correct regions.
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