ComfyUI Node: THRESHOLD (JOV) 📉

THRESHOLD (JOV) 📉:

The THRESHOLD (JOV) 📉 node is designed to facilitate image segmentation and feature extraction by applying various thresholding techniques. This node allows you to define a threshold value to create binary or adaptive masks, which can be used to highlight specific features within an image. You can adjust the threshold value and block size to fine-tune the results according to your needs. Additionally, the node provides an option to invert the resulting mask, making it versatile for a wide range of image processing tasks. Whether you are working on simple binary thresholding or more complex adaptive methods, this node offers the flexibility and control needed to achieve precise results.

THRESHOLD (JOV) 📉 Input Parameters:

PIXEL

This parameter accepts any image input that you want to apply the thresholding operation to. It serves as the primary image data that will be processed by the node.

ADAPT

This parameter determines the adaptive thresholding method to be used. Options include various adaptive methods such as ADAPT_NONE, which applies no adaptive thresholding. The default value is ADAPT_NONE.

FUNC

This parameter specifies the thresholding function to be applied. Options include different threshold modes like BINARY, which converts the image to a binary mask. The default value is BINARY.

THRESHOLD

This parameter sets the threshold value for the thresholding operation. It ranges from 0 to 1, with a default value of 0.5. Adjusting this value will change the sensitivity of the thresholding process.

SIZE

This parameter defines the block size for adaptive thresholding. It ranges from 3 to 103, with a default value of 3. Larger block sizes can capture more extensive features but may reduce the granularity of the thresholding.

INVERT

This boolean parameter allows you to invert the resulting mask. If set to True, the mask will be inverted. The default value is False.

THRESHOLD (JOV) 📉 Output Parameters:

torch.Tensor

The primary output is a tensor containing the thresholded image. This tensor can be used for further image processing tasks or as an input to other nodes in your workflow.

THRESHOLD (JOV) 📉 Usage Tips:

• Experiment with different THRESHOLD values to find the optimal setting for your specific image.
• Use the ADAPT parameter to apply adaptive thresholding methods for images with varying lighting conditions.
• Adjust the SIZE parameter to control the granularity of the adaptive thresholding.
• Utilize the INVERT parameter to create negative masks, which can be useful for certain types of image analysis.

THRESHOLD (JOV) 📉 Common Errors and Solutions:

"no images to stack"

• Explanation: This error occurs when no images are provided to the node for processing.
• Solution: Ensure that you have supplied a valid image input to the PIXEL parameter.

"Invalid threshold value"

• Explanation: This error occurs when the threshold value is set outside the acceptable range of 0 to 1. - Solution: Adjust the THRESHOLD parameter to a value within the range of 0 to 1.

"Block size out of range"

• Explanation: This error occurs when the block size for adaptive thresholding is set outside the acceptable range of 3 to 103.
• Solution: Set the SIZE parameter to a value within the range of 3 to 103.