Next to AI mathematical methods can be used for the detection of objects like a circle. This node is using Hough's transform for the detection of circles in an given image. The advantage of mathematical methods is that the recognised circles can be virtually predicted. I utilise this to create masks.

Usage

After installation the node can be find in the node menu

Add Node > 🧬 Circle Detection Nodes > 🔬 Circle Detection

For showing data one can use following node

Add Node > 🧬 Circle Detection Nodes > 🗃 Circle Detection

Version Previews

version 0.0.0.1

Figure 1: Preview of workflow using the circle detection node

version 0.0.0.2

Figure 2: Preview of workflow using the circle detection node

version 0.0.0.3

Figure 3: Preview of workflow using the circle detection node

Installation

Use the ComfyUI Manager for the installation of the node.

You can also move int the directory ComfyUI/custom_nodes

git clone https://github.com/zentrocdot/ComfyUI_Circle_Detection

Example

Figure 1: Original image

Figure 2: Image with circles detected

To-Do

Troubleshooting in the node programming and sanitizing up the code.

Remarks

The first image created is the one, where on can see, which circles are found. The seond image looks like a mask, but it is not for the moment. It is still an blank image, where the found circles are filled drawn. This changed in version 0.0.0.3.

References

[1] https://docs.opencv.org/3.4/d4/d70/tutorial_hough_circle.html