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I am working on adding the option to save OCR training images then users can send me the training images so I can retrain the OCR model to improve accuracy. Most likely I will release a new version in a month or two.

If you want a full color option try the EmpireTech IPC-T549M-ALED-S2. This is what I have at my front door. It is not 4k but has a Min. Illumination of 0.0005 Lux@F1.0 (Color, 30IRE) like the EmpireTech IPC-Color4K-T...

Make sure you have the below settings Main AI Settings Camera AI Settings

The Yolov5.Net module should be using whatever GPU you have, try enabling GPU

This reminds me of Atlas at Rockefeller Center

It depends on what model you are using to find the car, post a screenshot of your AI settings.

Done

If the model work well I will train a YOLOv8 version. We currently do not have a YOLOv8 .NET module, I am using the YOLOv5 .NET module and are getting better performance then the YOLOv8 module.

So far the model is training well, I am using yolov5l. I am already thinking of scraping newer make and models.

I am training a model right now that will identify the make/model of vehicles. I am not sure how good it will be most of the model years are about 10+ years old. Link to Dataset I am using capstone-g7-car-detection Object Detection Dataset by Sudharsan Rengarajan CLASSES AM General Hummer SUV...

There is a code typo, it should say GPU. It is still using your GPU, it will be fix in upcoming release

Do you have some firewall blocking the install?

Did any errors show in the log?

It looks like the module did not install correctly. Try uninstalling the module then reinstall using Do not use download cache

The ALPR module uses the license-plate model first to find the license plates in the images sent. If the module does not find any license plates it returns nothing found. If it finds a license plate then it crops the plate and runs OCR on the cropped plate and send the OCR results.

Use the below AI settings

Below are the versions and test script (ChatGPT wrote the script) Pillow 9.4.0 opencv-python 4.8.1.78 import time import cv2 from PIL import Image def resize_pil(image, output_width): width_percent = (output_width / float(image.width))...

@mailseth OpenCV is faster then PIL below is a comparison resizing 100 4K image to 640 width PIL resizing time: 0.19400310516357422 seconds OpenCV resizing time: 0.010996818542480469 seconds

I have seen this before, I do not remember what the cause was. It might be the cuDNN version not matching the CUDA version

See the below link, this might fix the issue https://stackoverflow.com/questions/43184887/dll-load-failed-error-when-importing-cv2#:~:text=Add%20a%20comment-,28,Recently%20I%20have,-faced%20the%20similar

Your GPU is Compute 5.2, the ALPR module currently only supports Compute 6 and greater.

I just realized that to old camera was a IPC-T5442T-ZE not the T54IR-ZE

Below are images from IPC-T5442T-ZE and Color4K-T after replacing the the IPC-T5442T-ZE with a Color4K-T. IPC-T5442T-ZE Exposure set to 1/60 Color4K-T Exposure set to 1/120

Check your firewall if it is blocking the module from downloading and installing.

Open up Path, it should be in there.

Use the below camera AI settings

If you want to get some more performance from your Nvidia GPU change the below setting to Prefer maximum performance

What version do you want, I might have it.