The Value of Visual Programming : Computer Vision in Dynamo

The Value of Visual Programming : Computer Vision in Dynamo

While developing Computer Vision functions in our custom package, I was reminded of the benefits that Visual programming brings to users. When I stumbled into OpenCV in python at the beginning, I was simply coding along with tutorials… not knowing the significance of most input variables.

Take Canny for example (See below documentation), for a layman like myself, I’d never have understood what each “threshold” parameters signified unless I spent some time researching about it. I remember changing the threshold values a number of times for comparison between the still images in my Jupyter notebook.

Canny function documentation (Source: docs.opencv.org)

Now, using Dynamo as a Visual Programming platform (See below), we can simply use a number slider to help us quickly get an intuition of each input variable. Which then allow users to determine a suitable value for it!

I believe that there’s probably other such cases where software developers can help users learn and execute more intuitively in a “visual” manner (I think Scratch is an excellent example).

On a side note, Sobel and Laplacian edge detection nodes have been added since the last post!

If you have any ideas that you hope to get implemented, please leave a comment or drop me a DM! We certainly need help from experts. You can also show your support by buying us a coffee at Patreon to help accelerate this project to realization!

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