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

To-Do

Troubleshooting in the node programming and sanitizing up the code.

Figure 1: Web userinterface in a web browser without image

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