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Edge Detect

Node icon
Filter

Extracts edges from an image using the Canny algorithm. Useful for creating line art, masks, or AI conditioning.

Edge Detect applies the Canny edge detection algorithm to find edges in an image. It outputs a binary image where white pixels mark detected edges. The two thresholds control sensitivity: the low threshold catches weak edges, the high threshold catches strong edges.

This node is commonly used to create line art from photographs, generate masks for compositing, or prepare reference images for AI image editing.

Parameters

Section titled “Parameters”

Pins

ImageImage
InputRequired
ImageImage
Output
AlphaMask
Output

Filter

Low ThresholdInteger
Default: 50 Range: 0–1000

Lower Canny threshold for edge rejection

High ThresholdInteger
Default: 150 Range: 0–1000

Upper Canny threshold for strong-edge acceptance

ApertureInteger
Default: 3 Range: 3–7

Sobel kernel size for gradient computation (3, 5, or 7)

L2 GradientToggle
Default: false

Use L2 norm for gradient magnitude (more accurate, slower than L1)

Pre-BlurToggle
Default: false

Apply Gaussian blur before edge detection to reduce noise

Blur Kernel (px)Integer
Default: 3 Range: 3–41
When Pre-Blur is on

Gaussian kernel size for pre-blur (odd)

InvertToggle
Default: false

Swap edge vs background pixels

Color

EdgeColor (RGBA)
Default: rgba(255, 255, 255, 255)

Edge color

BackgroundColor (RGBA)
Default: rgba(0, 0, 0, 0)

Background color

Usage Tips

Section titled “Usage Tips”
  • Enable Pre-Blur to reduce noise before detection, producing cleaner edges with fewer false positives.
  • Lower thresholds detect more edges (including noise); higher thresholds detect only strong edges.
  • Use custom edge and background colors to create colored line art.
  • Wire Edge Detect output into AI Image Edit as a reference for structure-guided generation.
Section titled “Related Nodes”