ComfyUI  >  Nodes  >  ComfyUI Impact Pack >  Make Tile SEGS

ComfyUI Node: Make Tile SEGS

Class Name

ImpactMakeTileSEGS

Category
ImpactPack/__for_testing
Author
Dr.Lt.Data (Account age: 458 days)
Extension
ComfyUI Impact Pack
Latest Updated
6/19/2024
Github Stars
1.4K

How to Install ComfyUI Impact Pack

Install this extension via the ComfyUI Manager by searching for  ComfyUI Impact Pack
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter ComfyUI Impact Pack in the search bar
After installation, click the  Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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Make Tile SEGS Description

Facilitates creation of tiled segments from input images for efficient processing and localized analysis.

Make Tile SEGS:

The ImpactMakeTileSEGS node is designed to facilitate the creation of tiled segments (SEGS) from an input image, allowing for more manageable and efficient processing of large images by breaking them down into smaller, more manageable tiles. This node is particularly useful for tasks that require detailed analysis or manipulation of specific regions within an image, such as object detection, segmentation, or enhancement. By dividing the image into tiles, you can apply localized processing techniques, which can lead to more accurate and efficient results. The node also supports the use of exclusion and inclusion masks to focus on or ignore specific areas of the image, providing greater control over the tiling process. Additionally, it can handle irregular masks and compensate for overlaps, ensuring that the tiles are generated with the desired characteristics.

Make Tile SEGS Input Parameters:

filter_out_segs_opt

This parameter allows you to specify segments that should be excluded from the tiling process. It takes a list of segments and generates an exclusion mask that prevents these areas from being included in the tiles. This is useful for ignoring irrelevant or unwanted regions in the image. The exclusion mask is resized and dilated based on the input image dimensions and a specified dilation factor.

filter_in_segs_opt

This parameter allows you to specify segments that should be included in the tiling process. It takes a list of segments and generates an inclusion mask that ensures these areas are included in the tiles. This is useful for focusing on specific regions of interest within the image. The inclusion mask is resized and dilated based on the input image dimensions and a specified dilation factor.

bbox_size

This parameter defines the size of the bounding box for each tile. It determines the dimensions of the tiles that will be generated from the input image. If the bounding box size is larger than the image dimensions, it will be adjusted to fit within the image. The default value is typically set to a reasonable size for most applications.

min_overlap

This parameter specifies the minimum overlap between adjacent tiles. It ensures that there is a certain amount of overlap between tiles, which can be useful for maintaining continuity and avoiding gaps in the tiled image. If the overlap is too small compared to the bounding box size, it will be adjusted accordingly.

mask_irregularity

This parameter controls the irregularity of the mask used in the tiling process. A higher value results in a more irregular mask, which can be useful for creating more natural-looking tiles. The mask quality and cache are adjusted based on the irregularity value, and the overlap and bounding box size are compensated accordingly.

irregular_mask_mode

This parameter defines the mode for generating irregular masks. It can be set to "Reuse fast," "Reuse quality," or "All random fast," each providing different levels of mask quality and performance. The mode affects the mask quality and the way the mask is generated and cached.

Make Tile SEGS Output Parameters:

tiles

The output parameter tiles contains the generated tiles from the input image. Each tile is a segment of the original image, created based on the specified bounding box size, overlap, and masks. These tiles can be used for further processing, analysis, or manipulation, allowing for more efficient and localized operations on the image.

Make Tile SEGS Usage Tips:

  • To focus on specific regions of interest, use the filter_in_segs_opt parameter to include only the desired segments in the tiling process.
  • Adjust the bbox_size and min_overlap parameters to control the size and overlap of the tiles, ensuring they are suitable for your specific application.
  • Use the mask_irregularity parameter to create more natural-looking tiles, especially when working with images that require a more organic appearance.
  • Experiment with different irregular_mask_mode settings to find the right balance between mask quality and performance for your needs.

Make Tile SEGS Common Errors and Solutions:

bbox_size is greater than resolution

  • Explanation: The specified bounding box size is larger than the dimensions of the input image.
  • Solution: Reduce the bbox_size parameter to fit within the image dimensions.

min_overlap should be greater than bbox_size

  • Explanation: The minimum overlap is too small compared to the bounding box size.
  • Solution: Increase the min_overlap parameter to be at least half of the bbox_size.

Unexpected target '<target>'

  • Explanation: An invalid target value was specified for a parameter.
  • Solution: Ensure that the target value is one of the expected options, such as "area(=w*h)," "length_percent," "width," "height," "x1," "x2," "y1," "y2," or "confidence(0-100)."

ValueError: mask_irregularity must be non-negative

  • Explanation: The mask_irregularity parameter was set to a negative value.
  • Solution: Set the mask_irregularity parameter to a non-negative value.

Make Tile SEGS Related Nodes

Go back to the extension to check out more related nodes.
ComfyUI Impact Pack
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