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ComfyUI Node: From SEG_ELT

Class Name

ImpactFrom_SEG_ELT

Category
ImpactPack/Util
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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From SEG_ELT Description

Extract and process segmented image elements for AI artists, enabling manipulation and analysis of image data components efficiently.

From SEG_ELT:

The ImpactFrom_SEG_ELT node is designed to extract and process various elements from a SEG_ELT object, which is a structured representation of segmented elements in an image. This node is particularly useful for AI artists who need to manipulate and analyze segmented image data for further processing or visualization. By utilizing this node, you can easily access and work with different components of the segmented element, such as the cropped image, mask, bounding box, and other metadata. This functionality allows for more precise and efficient image editing, enhancing the overall workflow in image segmentation tasks.

From SEG_ELT Input Parameters:

seg_elt

The seg_elt parameter is the primary input for this node and represents a segmented element (SEG_ELT). This object contains various attributes related to the segmented portion of an image, such as the cropped image, mask, bounding box, and additional metadata. The seg_elt parameter is essential for the node to function, as it provides the necessary data for extraction and processing. There are no specific minimum, maximum, or default values for this parameter, as it is expected to be a valid SEG_ELT object.

From SEG_ELT Output Parameters:

seg_elt

The seg_elt output is the original segmented element passed as input. This allows you to retain the original data for further use or reference.

cropped_image

The cropped_image output is a tensor representation of the cropped portion of the image corresponding to the segmented element. This output is useful for further image processing or analysis tasks.

cropped_mask

The cropped_mask output is a tensor representation of the mask associated with the cropped image. This mask highlights the segmented area within the cropped image, enabling precise editing and manipulation.

crop_region

The crop_region output provides the coordinates of the region in the original image that was cropped to obtain the cropped_image. This is represented as a tuple of four integers: (left, top, right, bottom).

bbox

The bbox output represents the bounding box of the segmented element within the cropped image. This is also a tuple of four integers: (left, top, right, bottom), and is useful for locating the segmented area within the cropped image.

control_net_wrapper

The control_net_wrapper output contains additional metadata or control information associated with the segmented element. This can be used for more advanced processing or integration with other systems.

confidence

The confidence output is a float value representing the confidence level of the segmentation. This value can be used to assess the reliability of the segmented element.

label

The label output is a string that provides a descriptive label for the segmented element. This can be useful for categorization or identification purposes.

From SEG_ELT Usage Tips:

  • Ensure that the seg_elt input is a valid SEG_ELT object to avoid errors and ensure accurate processing.
  • Utilize the cropped_image and cropped_mask outputs for precise image editing and manipulation tasks.
  • Leverage the confidence output to filter or prioritize segmented elements based on their reliability.
  • Use the label output to categorize or identify segmented elements for better organization and analysis.

From SEG_ELT Common Errors and Solutions:

Invalid SEG_ELT object

  • Explanation: The input seg_elt is not a valid SEG_ELT object.
  • Solution: Ensure that the input is a properly structured SEG_ELT object containing all necessary attributes.

Missing cropped_image attribute

  • Explanation: The seg_elt object does not contain a cropped_image attribute.
  • Solution: Verify that the seg_elt object includes a valid cropped_image attribute before passing it to the node.

Missing cropped_mask attribute

  • Explanation: The seg_elt object does not contain a cropped_mask attribute.
  • Solution: Ensure that the seg_elt object includes a valid cropped_mask attribute before using the node.

Missing crop_region attribute

  • Explanation: The seg_elt object does not contain a crop_region attribute.
  • Solution: Check that the seg_elt object includes a valid crop_region attribute before processing.

Missing bbox attribute

  • Explanation: The seg_elt object does not contain a bbox attribute.
  • Solution: Confirm that the seg_elt object includes a valid bbox attribute before passing it to the node.

From SEG_ELT Related Nodes

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