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Hey HN, I’m Caleb, and I’m a maintainer of Cortex, an open source model deployment platform. Not long ago, we published this DIY license plate reader project,
by calebkaiser 6y ago
Hey HN,
I’m Caleb, and I’m a maintainer of Cortex, an open source model deployment platform. Not long ago, we published this DIY license plate reader project, and I wanted to share it here for anyone who is interested in computer vision or production machine learning in general.
The project is a web service that accepts images and, using three trained models, returns extracted license plate text, assuming there is a license plate in the image. Of the models used, two are pre-trained models from keras-ocr, while one is a fine tuned YOLOv3. All models are freely available.
You can see a video of the project in action here: https://www.youtube.com/watch?v=gsYEZtecXlA https://www.youtube.com/watch?v=gsYEZtecXlA
And read a write up by Robert Lucian, the maintainer who spearheaded this entire project, about how he built a camera system to interface with the web service using a Raspberry Pi and 5G: https://towardsdatascience.com/i-built-a-diy-license-plate-reader-with-a-raspberry-pi-and-machine-learning-7e428d3c7401 https://towardsdatascience.com/i-built-a-diy-license-plate-r...
- omgwtfbyobbq 6y agoThis looks very neat. Do you think something like a Jetson Nano would be able to handle inference locally?
- calebkaiser 6y agoThanks! The short answer is that I don't know, as it's only been run on EC2 instances, but given its current compute needs, probably not. The longer answer is that this project has a ton of room for optimization, some of which is mentioned in the repo, and with lower latency requirements + optimizations, I don't see why it wouldn't work on less powerful hardware (I've never personally worked with the Jetson Nano, so I don't want to speak with any false confidence on it specifically).
- hadeson 6y agoI guess object detection is the bottleneck of the pipeline, which highly optimized YOLOv4-tiny[0]could get to 39 FPS on Jetson Nano. Also camera decoding with Nvidia Deepstream is a lot faster than OpenCV. [0] https://github.com/pjreddie/darknet/issues/2201 https://github.com/pjreddie/darknet/issues/2201
- jmnicolas 6y agoI wonder if it would be more efficient with OpenCV?
- calebkaiser 6y agoThat's very possible. The Python interface for writing prediction APIs makes it pretty easy to switch between models, so it shouldn't be hard to test.
- bigiain 6y agoThis one uses some OpenCV: https://www.freecodecamp.org/news/remember-that-86-million-license-plate-scanner-i-replicated-heres-what-happened-next-9f3c64e8f22b/ https://www.freecodecamp.org/news/remember-that-86-million-l...
- markdown 6y ago> using a Raspberry Pi and 5G For anyone else wondering, he used a Raspberry Pi and a mobile internet connection. Any number of G's will do.