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ComfyUI Node: Simple Detector (SEGS)

Class Name

ImpactSimpleDetectorSEGS

Category
ImpactPack/Detector
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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Simple Detector (SEGS) Description

Efficient object detection and segmentation using SEGS model for AI artists, simplifying isolation and manipulation of image elements.

Simple Detector (SEGS):

The ImpactSimpleDetectorSEGS node is designed to provide a straightforward and efficient way to detect and segment objects within an image using the SEGS (Segmentation) model. This node is particularly useful for AI artists who need to isolate specific elements in their artwork or images for further manipulation or analysis. By leveraging advanced segmentation techniques, the node can accurately identify and delineate objects, making it easier to apply effects, transformations, or other creative modifications. The primary goal of this node is to simplify the segmentation process, offering a user-friendly interface that delivers precise results without requiring deep technical knowledge.

Simple Detector (SEGS) Input Parameters:

segm_detector

This parameter specifies the segmentation detector model to be used for processing the image. The model is responsible for identifying and segmenting objects within the image based on the provided threshold and dilation settings. The choice of model can significantly impact the accuracy and quality of the segmentation results.

image

The image parameter is the input image that you want to process using the segmentation detector. This image will be analyzed by the model to identify and segment objects. The quality and resolution of the input image can affect the performance and accuracy of the segmentation.

threshold

The threshold parameter is a floating-point value that determines the confidence level required for the model to consider a detected object as valid. It ranges from 0.0 to 1.0, with a default value of 0.5. A higher threshold means that only objects with higher confidence scores will be segmented, which can reduce false positives but may also miss some valid objects.

dilation

The dilation parameter is an integer value that specifies the amount of dilation to apply to the segmented masks. It ranges from -512 to 512, with a default value of 0. Dilation can help to refine the edges of the segmented objects, making them more or less pronounced depending on the value. Positive values increase the size of the segmented areas, while negative values decrease it.

Simple Detector (SEGS) Output Parameters:

mask

The mask output parameter is the resulting segmentation mask generated by the node. This mask is a binary image where the segmented objects are highlighted, allowing you to easily isolate and manipulate these objects in your artwork or further processing. The mask is returned as a tensor, which can be used in various image processing workflows.

Simple Detector (SEGS) Usage Tips:

  • Adjust the threshold parameter to balance between detecting all possible objects and minimizing false positives. A lower threshold will detect more objects but may include irrelevant ones, while a higher threshold will be more selective.
  • Use the dilation parameter to fine-tune the edges of the segmented objects. Positive dilation values can help to merge close objects, while negative values can separate them more distinctly.
  • Ensure that the input image is of good quality and resolution to achieve the best segmentation results. Blurry or low-resolution images may lead to less accurate segmentation.

Simple Detector (SEGS) Common Errors and Solutions:

"Model not found"

  • Explanation: This error occurs when the specified segmentation detector model is not available or cannot be loaded.
  • Solution: Verify that the model name is correct and that the model is properly installed and accessible in the system.

"Invalid image format"

  • Explanation: This error indicates that the input image is not in a supported format or is corrupted.
  • Solution: Ensure that the input image is in a valid format (e.g., JPEG, PNG) and is not corrupted. Try using a different image to see if the issue persists.

"Threshold out of range"

  • Explanation: This error occurs when the threshold value is set outside the allowed range of 0.0 to 1.0.
  • Solution: Adjust the threshold value to be within the valid range. The default value is 0.5, which is a good starting point.

"Dilation value out of range"

  • Explanation: This error indicates that the dilation value is set outside the allowed range of -512 to 512.
  • Solution: Set the dilation value within the valid range. The default value is 0, which means no dilation is applied.

Simple Detector (SEGS) Related Nodes

Go back to the extension to check out more related nodes.
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