opencv-python VS pycomm3

Have you ever felt like your photos needed a little extra touch to stand out? Well, get ready because we're about to learn a cool Python trick! We're going to take ordinary photos and turn them into awesome pencil sketches using Python and OpenCV. This will make your pictures look like they were drawn by hand!

There are several modules that would allow you to process images in Python. Two of the perhaps most famous ones are PIL (https://pypi.org/project/Pillow/, also known as pillow), and opencv (https://pypi.org/project/opencv-python/).

Classifying images with trained model by using OpenCV and Teachable Machine packages

opencv-python: OpenCV for Python

Tool: Data collected using Python opencv, and a rudimentary OCR built from scratch. Graphic created with Microsoft Excel.

cv2: https://pypi.org/project/opencv-python/

I would try installing opencv-python on its own to see if you can learn more: https://pypi.org/project/opencv-python/

I've been googling and reading for a while but I'm very unsure about which tools I need, which tools will help me achieve what I want the easiest way. What about (pylivestream)[https://pypi.org/project/pylivestream/] for example? Will this do the job for me? What about a lower level approach including (pyopencv)[https://pypi.org/project/opencv-python/]? What about a higher level approach using (vidgear)[https://github.com/abhiTronix/vidgear], which seems promising but I don't feel confident in assessing if it's the tool I really need?

This is likely to be buggy and frustrating, and it's very likely that you'll need to use OpenCV to preprocess the screenshot. Not my idea of a good time!

Probably best to start a discussion in the repo. https://github.com/ottowayi/pycomm3

If you want to see the code, it's on github. Everything starts with get_tag_list in pycomm3/logix_driver.py. And _parse_template_data has most of the logic for parsing the struct attribute definitions. The code is pretty complicated, hard to follow, and not something I'm particularly proud to show off. I've been meaning to refactor it, but I've been avoiding it since it took so long to get working.

To elaborate on what I think u/TheDevilsAutocorrect is getting at, don't do the data logging on the PanelView. Use [Pycomm3](https://github.com/ottowayi/pycomm3) or [pylogix](https://github.com/ottowayi/pycomm3) to log directly to the Raspberry Pi. You can log to CSV pretty easily with either library.

Here are the basic steps, if you have any questions feel free to ask there.

If you're using a MicroLogix with ethernet you can try pycomm3. It's a pure Python Ethernet/IP library I maintain. It started as a port of pycomm to Python 3, but since has changed significantly. It has "support" for MicroLogix thru the SLCDriver. You may need to refer to the pycomm documentation for addressing examples, though. When I was at an integrator we never used MicroLogix PLCs, so any testing was done against a SLC. If you try it out and run into any issues, feel free to open up a issue on GitHub.